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values | gha_event_created_at timestamp[us]date 2012-06-21 16:39:19 2023-09-14 21:52:42 ⌀ | gha_created_at timestamp[us]date 2008-05-25 01:21:32 2023-06-28 13:19:12 ⌀ | gha_language stringclasses 60
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values | filename stringlengths 1 141 | content stringlengths 7 9.18M |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ad6e86471a2482089763eb07c064c67b948c9715 | afe9b94df6f6a3211ace68b127f57ca38a1965af | /R/createLink.R | 1918f45da240e0beec47a3a9cb397c5498563fee | [] | no_license | datastorm-open/antaresEditObject | d10e1f80cdcb4749a82b575ba037ddb642c183fb | 49739939a8a4e4857db94031b5e76a81ddb03f7c | refs/heads/master | 2021-07-21T14:38:29.878961 | 2017-10-31T08:41:54 | 2017-10-31T08:41:54 | 106,667,353 | 1 | 0 | null | 2017-10-12T08:42:54 | 2017-10-12T08:42:54 | null | UTF-8 | R | false | false | 5,311 | r | createLink.R | #' Create a link between two areas
#'
#' @param from The first area from which to create a link
#' @param to The second one
#' @param propertiesLink a named list containing the link properties, e.g. hurdles-cost
#' or transmission-capacities for example.
#' @param dataLink a matrix with five column corresponding to : t... |
b8f1e24355dc46b154f85c686ea7984f64a68685 | 150ddbd54cf97ddf83f614e956f9f7133e9778c0 | /tests/testthat/test-symmetrise.R | bb72b6a242945a2daee02d376d41e82c6b4224a4 | [
"CC-BY-4.0"
] | permissive | debruine/webmorphR | 1119fd3bdca5be4049e8793075b409b7caa61aad | f46a9c8e1f1b5ecd89e8ca68bb6378f83f2e41cb | refs/heads/master | 2023-04-14T22:37:58.281172 | 2022-08-14T12:26:57 | 2022-08-14T12:26:57 | 357,819,230 | 6 | 4 | CC-BY-4.0 | 2023-02-23T04:56:01 | 2021-04-14T07:47:17 | R | UTF-8 | R | false | false | 4,162 | r | test-symmetrise.R | #wm_opts(server = "https://webmorph.test")
# frl ----
test_that("frl", {
skip_on_cran()
stimuli <- demo_tems("frl")
sym_both <- symmetrize(stimuli)
sym_shape <- symmetrize(stimuli, color = 0)
sym_color <- symmetrize(stimuli, shape = 0)
sym_anti <- symmetrize(stimuli, shape = -1.0, color = 0)
# c(st... |
36fb3ae17533ad2b38942c78e7e2077171256e55 | bd8e2bb20817f4f829db6bd308ba686812b20027 | /man/neuro_install.Rd | c1121e1bd30e09250a3c0614971ba26b65fb1639 | [] | no_license | muschellij2/neurocInstall | 3a1d9524cf8785589bb58ae3a072a1aee82ca4c8 | c1792997fe2ce04679e25c1a2d3e05359cc652e8 | refs/heads/master | 2022-12-29T19:36:11.536992 | 2020-10-15T19:46:58 | 2020-10-15T19:46:58 | 66,025,383 | 0 | 4 | null | null | null | null | UTF-8 | R | false | true | 2,294 | rd | neuro_install.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/neuro_install.R
\name{neuro_install}
\alias{neuro_install}
\alias{neuroc_install}
\alias{neurocLite}
\title{Neuroconductor Installer}
\usage{
neuro_install(
repo,
release = c("stable", "current"),
release_repo = latest_neuroc_release(),... |
70fee9c0724d381e9f3dd3ee97ebe11291f91e28 | 98550ab8b21f1d86f5954886911fc01498ef7699 | /R/packageSample.R | aa6980ecc29b13654fad3c1833c130c723eab576 | [] | no_license | lindbrook/packageRank | a68ee94e0ed3621e7f10239f1eb2d12dbb7c6530 | a83ebfaa05f6ee82b7e5ae76cf0b8a4c296b4dfb | refs/heads/master | 2023-08-04T21:18:01.261280 | 2023-08-01T22:00:29 | 2023-08-01T22:00:29 | 184,319,415 | 27 | 1 | null | 2023-08-01T22:00:20 | 2019-04-30T19:25:45 | R | UTF-8 | R | false | false | 4,449 | r | packageSample.R | #' Stratified random sample of packages.
#'
#' Logs from RStudio's CRAN Mirror http://cran-logs.rstudio.com/
#' @param cran_log Object. CRAN log.
#' @param sample.pct Numeric.
#' @param multi.core Logical or Numeric. \code{TRUE} uses \code{parallel::detectCores()}. \code{FALSE} uses one, single core. You can also speci... |
c4e46b89cf13b64e4b470a21900fe6455602df18 | 5aff17c35e023029c0c7cec84f56404067826b60 | /problem/day6/kimhokyeong_191204.R | 4e8b556283d1f2946cd0a40daa1be408e2a9d39b | [] | no_license | holaho-kim/workR | 9a3bcf02ee4332b967a331f12398935930c026d2 | 7ce670de7369f90bc1beae17608e36bbe404876c | refs/heads/master | 2022-05-30T23:16:33.100793 | 2020-01-16T04:44:33 | 2020-01-16T04:44:33 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,554 | r | kimhokyeong_191204.R | # * 실습 결과를 R Script file로 제출
# * R Script file 이름은 "영문본인이름_제출일날짜.R" 부여하여 제출
# * R Script file의 처음에 주석으로 본인 이름과 작성일/제출일 기록
#
# 문1)
# 다음은 직장인 10명의 수입과 교육받은 기간을 조사한 자료이다. 산점도와 상관계수를 구하고,
# 수입과 교육기간 사이에 어떤 상관관계가 있는지 설명하시오.
#
# 수입 121 99 41 35 40 29 35 24 50 60
# 교육기간 19 20 16 16 18 12 14 12 16 17
income <- c( 121, 99... |
46cae5b38d2e765aa68edd80d0653167040ae02f | 7fe6c7028fad18327bc5e4b8eef89686de80ac7b | /plot2.R | 0c71ba271f5c2dd96defc1ad0a0b1b802befc80b | [] | no_license | vinodsrin/RepData_PeerAssessment1 | 6012f2ce73be67d8b775970a8aefff9c83c7c78e | dd74d5d1c2e83374a63cba597896434a8f50c369 | refs/heads/master | 2021-01-21T16:49:04.587892 | 2016-01-13T17:11:11 | 2016-01-13T17:11:11 | 49,567,062 | 0 | 0 | null | 2016-01-13T10:32:01 | 2016-01-13T10:32:01 | null | UTF-8 | R | false | false | 1,046 | r | plot2.R |
#Uncomment below lines to download data required is not downloaded
#download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", "./powerconsumption.zip")
#if(!file.exists("./powerconsumption")) {dir.create("./powerconsumption")}
#unzip("powerconsumption.zip", exdir = "./powe... |
8427b5411ae52937fd97edcbfa2a7e1d0822bb05 | 661a2e1bdd2eaf48c3ec7f93531821ee4e574292 | /man/getAmendments.Rd | 8f715c412030ff7e93e05ba58ad0e40970b5cbba | [] | no_license | cran/washex | dc94cae67e9654d72184e7d37bb9c1c0ce763a27 | 561ac582539d94b46c3e1020386a0712ac4c4a5d | refs/heads/master | 2023-09-04T21:38:52.121744 | 2021-11-17T15:00:02 | 2021-11-17T15:00:02 | 362,524,979 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,320 | rd | getAmendments.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getAmendments.R
\name{getAmendments}
\alias{getAmendments}
\title{Get amendments to a bill}
\usage{
getAmendments(
biennium,
billNumber,
paired = TRUE,
type = c("df", "list", "xml")
)
}
\arguments{
\item{biennium}{Charac... |
7473a5c309788517b8cb15745394b12c7bdb6e71 | cc32077bcdf07924ad31e1cf0a75d13b9194ecd7 | /testOUgeneration.R | 14ff68f04b851a800847573dcd99c6e22c283111 | [] | no_license | AndrewLJackson/nodes-networks-energy | 79ad34a08e0268f1e171d7cbc87e26342659f800 | 9770b6bde8af9aa983018c351ab07f8cd9243826 | refs/heads/master | 2020-12-24T19:27:18.059731 | 2016-03-11T12:15:39 | 2016-03-11T12:15:39 | 27,050,236 | 0 | 0 | null | 2015-10-12T20:14:11 | 2014-11-23T22:20:08 | R | UTF-8 | R | false | false | 1,908 | r | testOUgeneration.R | library(sde)
library(viridis)
palette(viridis(8))
# -----------------------------------------------------------------
# Ornstein-Uhlenbeck process
# -----------------------------------------------------------------
set.seed(1)
d <- expression(0 - 20 * x)
s <- expression(0.1)
time.max <- 100
N <- 10^3
y <- sde.sim... |
ddd4eb25f10d8cd5f11a5fb92780181060598b9a | af5841763d8f0fdd5ca28114ff78324b5dbaa36b | /R/Loader.R | 5ff671e1c98195da9aa86e20c23f7341a2968567 | [] | no_license | RJHKnight/TCALoader | fe8a56973c3303ef880450952bc9677b2074a49e | be8ea6a376c0730c6e9047df85c4ef0893a5fa48 | refs/heads/master | 2021-03-28T15:56:16.465896 | 2020-10-13T05:31:00 | 2020-10-13T05:31:00 | 247,876,192 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,076 | r | Loader.R | DEFAULT_CSV_OFFSET <- 0
DEFAULT_EXCEL_OFFSET <- 4
FILE_SEP <- "/"
#' Load Multiple Post Trades
#'
#' Load multiple post trade files (csv and excel supported) returning a single
#' data.frame.
#'
#' @param path path containing the files to read
#' @param pattern pattern for files to match
#' @param add_filename shou... |
ee9eddd07c91d898b83456828d2ea4a9991cae9d | 0405bb266387a503a59b160688d8903e4bfc850f | /11_1_Tree_mask_updater_Nigeria_v7_1.R | 939e7d43a59bea2f7ef48ecee29f891fdbd3485f | [] | no_license | HKCaesar/RemoteSensing_automated_workflow_agriculture | 6162ef0d27fc7701fc44e18b86770a112c147fca | 671c9ba2b78f7157b1b2c3da1b03687c943df822 | refs/heads/master | 2020-12-03T05:08:53.357289 | 2017-04-30T15:55:45 | 2017-04-30T15:55:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 31,961 | r | 11_1_Tree_mask_updater_Nigeria_v7_1.R | #======================================================================================
# Variable definitions, data import, preparation
#======================================================================================
#rm(list=ls(all=TRUE))
graphics.off()
require(rgdal)
require(Rcpp)
WriteLog <- TRU... |
a3664b6bfff27b4634d35dbc7998af94f03db081 | 0d725654ae06c6a2c09613789b8c46e8b7f39539 | /man/getPath.Rd | 222c13fdb2dad0e6717f058c08af30679c496bbc | [] | no_license | guillemr/robust-fpop | 904d2672b0cf9b5f70a280c75da0c4417e1e0b48 | ce49c26aa5b5eee84a835e69cbb7ca572f669792 | refs/heads/master | 2020-12-26T03:23:28.382328 | 2019-07-02T13:11:37 | 2019-07-02T13:11:37 | 68,607,744 | 10 | 3 | null | null | null | null | UTF-8 | R | false | false | 463 | rd | getPath.Rd | \name{getPath}
\alias{getPath}
\title{getPath}
\description{This function is used by the Rob_seg function to recover the best segmentation from 1:n from the C output}
\usage{getPath(path, i)}
\arguments{
\item{path}{the path vector of the "Rob_seg" function}
\item{i}{the last position to consider in the path... |
97f325e170c371a80f2d7e4822b1b08b0ed61670 | af286c8e4688c1ca310605d33d74ac6bc6f0cf5e | /man/getReactableState.Rd | 41c16c0bdd0f56641e8b3f61cb621748d2b50ab5 | [
"MIT"
] | permissive | glin/reactable | 999d3385bad36c4273f9766d8a8663b42a88cef4 | 86bd27670eac8fb330a50413f462cf1fe0ff8e88 | refs/heads/main | 2023-08-29T11:15:04.340315 | 2023-07-14T20:33:39 | 2023-07-14T20:33:39 | 178,748,690 | 594 | 84 | NOASSERTION | 2023-01-08T17:30:20 | 2019-03-31T22:22:16 | JavaScript | UTF-8 | R | false | true | 2,969 | rd | getReactableState.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shiny.R
\name{getReactableState}
\alias{getReactableState}
\title{Get the state of a reactable instance}
\usage{
getReactableState(outputId, name = NULL, session = NULL)
}
\arguments{
\item{outputId}{The Shiny output ID of the \code{reactable... |
d65e10efbdba19e0c447f8ee4a607d30609f8e60 | 2ead1fef38f9c97740374896c591e690c9577c28 | /Community/Code/ZipInTX.R | f8697372c6e152c80a2e20d4b3b4554e29816ded | [] | no_license | aditinabar/MapTheGap | 5424d025d18e3bf2ffc1c04aa10ae29899add1f9 | 3d919f30ea6bd3cc7c550ed99d68fa2922bcefdd | refs/heads/master | 2016-09-06T17:45:44.086357 | 2015-06-05T17:33:40 | 2015-06-05T17:33:40 | 31,827,298 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,168 | r | ZipInTX.R | setwd("C:/Users/naditi/Projects/MapTheGap/Community/Data/")
US <- read.table("US Zipcodes.csv", sep = ",", header = TRUE, stringsAsFactor = TRUE)
US[,which(colnames(US) == "world_region")] <- NULL
US[,which(colnames(US) == "timezone")] <- NULL
US[,which(colnames(US) == "county")] <- NULL
US[,which(colnames(US) == "are... |
0c3fb26a5219278ef37726ea557c1b0978085dba | 4344efed9e7b5b01134e2fab68587878fba8bf53 | /CASP/CASPplotter.R | 7789e63fbe15e5b3376dfe32ec268132c9607408 | [] | no_license | mrkeppler/WWU-Projects | 1d7e92e7ab7a8d575dd844c2df07ca3d6aa36d43 | 4576683fe11a69517457b6a56bca605e876a2874 | refs/heads/master | 2023-05-03T08:53:44.597702 | 2021-05-21T22:00:41 | 2021-05-21T22:00:41 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,544 | r | CASPplotter.R | setwd('D:/Bork/Desktop')
data = read.table('results.dat',header=T)
mat = sqrt(as.matrix(data))
colnames(mat) = 1:20
T0949 = mat[1:3,]
T0950 = mat[4,]
T0951 = mat[c(6,5,7),]
T0953s1 = mat[c(9,8,10),]
T0953s2 = mat[c(11,13,12),]
pdf('barplots.pdf')
barplot(T0949, xlab = 'Structure', ylab = 'MSD', main = '... |
c24b9a80fe882415f36c16f351e95562bb56ef9c | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/highfrequency/examples/rCov.Rd.R | 934f20c9b7049b7823066fc74ff239421fdb5fba | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 502 | r | rCov.Rd.R | library(highfrequency)
### Name: rCov
### Title: Realized Covariance
### Aliases: rCov
### Keywords: volatility
### ** Examples
# Realized Variance/Covariance for CTS aligned
# at 5 minutes.
data(sample_tdata);
data(sample_5minprices_jumps);
# Univariate:
rv = rCov( rdata = sample_tdata$PRICE, align.by... |
77143359120291b9d0530e277a4503f579f308d2 | dbb6c3f594656f0c990b32821e572e352278741c | /run_analysis.R | 9e4a2fdcbbd24ade713d388890e21575677188cf | [] | no_license | amirzoev/ReadAndCleanData-Assignment | 44d16eb3751b62bffb9da8df738446cc17cc2f5a | 510bb891fe2491b2c4b61cbee25f0bdbbc7bac20 | refs/heads/master | 2020-06-02T07:03:46.074115 | 2014-04-27T22:34:57 | 2014-04-27T22:34:57 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,808 | r | run_analysis.R | #Merges the training and the test sets to create one data set.
test_set<-read.table('./UCI HAR Dataset/test/X_test.txt')
train_set<-read.table('./UCI HAR Dataset/train/X_train.txt')
set<-rbind(test_set,train_set) # resulting set
act_testset<-read.table('./UCI HAR Dataset/test/y_test.txt')
act_trainset<-read.table('./UC... |
abde02fc3d9722d256cfffb5e790b1de027d93d6 | 7b74f00cd80694634e6925067aaeb6572b09aef8 | /2019/Assignment/FE8828-Iman Taleb/Assignment 4/ex2. bookoptiontrades.R | 57d5075c27e9aa1ebd645f640884ae2b8c38b899 | [] | no_license | leafyoung/fe8828 | 64c3c52f1587a8e55ef404e8cedacbb28dd10f3f | ccd569c1caed8baae8680731d4ff89699405b0f9 | refs/heads/master | 2023-01-13T00:08:13.213027 | 2020-11-08T14:08:10 | 2020-11-08T14:08:10 | 107,782,106 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 983 | r | ex2. bookoptiontrades.R | library(fOptions)
library(dplyr)
library(ggplot2)
#Valuation Calculation
callputs<-mutate(callputs,Value=`Open Interest`*(Bid+Ask)/2)
#Total Valuation of Calls and Puts alone
group_by(callputs,Type)%>%
summarise(`Total Valuation`=sum(Value))
#Total Valuation of both calls and puts
summarise(callputs,Total=sum(Valu... |
feb01a758b0446251e344462bb165a7f1c9646ad | 5fc672d84618a45c16542dc8680fa3d41937ce22 | /R/R2G2/man/Plots2GE.Rd | a55fd0e35e97dd4148948ebe36b5f12b83863c5c | [] | no_license | arrigon/R2G2 | 4dccffe82d01660b13eee54598a21de561cc1928 | f49f292c903879295ddb84c676f02f80883a9db5 | refs/heads/master | 2021-01-11T00:14:27.612052 | 2016-10-11T11:44:57 | 2016-10-11T11:44:57 | 70,573,434 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,452 | rd | Plots2GE.Rd | \name{Plots2GE}
\alias{Plots2GE}
\title{
Georeferencing custom R plots into Google Earth
}
\description{
Plots2GE: Places PNG R plots on Google Earth, as KML files.
}
\usage{
Plots2GE(data, center, nesting = 0, customfun, goo = "Plots2GE.kml", testrun = FALSE)
}
%- maybe also 'usage' for other objects documented here.
... |
6b0b49e5a97d2049f0e3106206c90dd74b216e6b | 254f9b74808e643c0802d97b9d558664af583375 | /consultas_joins/joins_varios_01.R | 483a142c72e17c042b04dcc643fbae50d72ee3a6 | [] | no_license | davgutavi/rupolab | 6ff269e6fffbfddc0beb57c0a2b1d8468ba649d8 | 9a386b694f16c53d20051d4c9856d10002b241d3 | refs/heads/master | 2022-03-30T03:29:30.480002 | 2020-01-20T13:05:10 | 2020-01-20T13:05:10 | 110,011,143 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,740 | r | joins_varios_01.R | #Joins varios 01
library(SparkR)
source("paths.R")
sparkR.session(master = "local[*]", sparkConfig = list(spark.local.dir="/mnt/datos/tempSparkR"))
conexp <- sql("
SELECT MaestroContratos.origen, MaestroContratos.cptocred, MaestroContratos.cfinca, MaestroContratos.cptoserv, MaestroContratos.cderind, Maes... |
8d7b8977002870aa537b934c3a30aae878eec1b0 | 02f8a640669a34eec542458bc3dcd4502c34bead | /R/utils.R | edf776aafd1ee4ebdc5aaedf259f7a68a34d7860 | [] | no_license | Yue-Jiang/karyoploteR | ae0bde33f7ec226fb92be9072ab69a82a132f76e | 867f7cc722d5f814806750b4fa39ce988d10b441 | refs/heads/master | 2020-03-25T22:42:59.661088 | 2018-08-10T05:23:40 | 2018-08-10T05:23:40 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,479 | r | utils.R | #internal
#Utility functions used only within the package
#Recycle the arguments as needed.
#Taken from:
# http://stackoverflow.com/questions/9335099/implementation-of-standard-recycling-rules
recycle <- function(...){
dotList <- list(...)
max.length <- max(sapply(dotList, length))
lapply(dotList, rep, length=m... |
28e4b6987a831af25e52e136ee105b17868925d4 | 3c6f49d7d20a99b1ebd27acd426a3270192f3fa6 | /code/01_build_dataset.R | b13a8defa2c6b118f505ebe8b9672385aa56e0ee | [] | no_license | ryanschmidt03/econ346honoroption | 046bb9ba4d158c7118039814f010dda65ff03c48 | 6cec20fed00e4bd1d1017f1d5ea015a04d24e7b4 | refs/heads/main | 2023-06-09T17:42:39.363334 | 2021-06-30T21:05:43 | 2021-06-30T21:05:43 | 308,104,361 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,017 | r | 01_build_dataset.R | #This script builds the dataset.
library(pacman)
p_load(tidyverse,lubridate)
#####################################
#Read in visitation
#visit_raw <- read_csv(file = "data/visitation_with_policy_day_and_month_dummies.csv")
#Read in hourly visitation (I've included the total number of devices observed
#in the panel ... |
70394269ef3bba852e53456db67ac63e34b8b623 | 091211fc733515cbcd42ad63998fcf6184bf3e77 | /man/predict.tprofile.Rd | 3a607617a159287dacf40fe57c54f1d17253eff2 | [] | no_license | AndrewYRoyal/ebase | 3560e2e4e717120357b066f27fbfa094d6bb34ec | 7decc805dc80d26a77505c8c4fb87816c63a7a24 | refs/heads/master | 2022-12-22T17:23:30.440452 | 2020-09-30T12:31:43 | 2020-09-30T12:31:43 | 168,870,979 | 3 | 0 | null | null | null | null | UTF-8 | R | false | true | 297 | rd | predict.tprofile.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/temp_profile.R
\name{predict.tprofile}
\alias{predict.tprofile}
\title{Predict site-year heating and cooling load}
\usage{
\method{predict}{tprofile}(x, dat)
}
\description{
Predict site-year heating and cooling load
}
|
642e168993f75f9f9adf087df384ff9bae9b47e9 | 5c0f37d8908d2fbd234a0cd0dddb371f4c0f2f77 | /check/rFreight.Rcheck/00_pkg_src/rFreight/man/progressStart.Rd | e647a8f0b2ec63eb48f7ca8dcd12903c9a78cfff | [] | no_license | CMAP-REPOS/cmap_freight_model | e5a1515eaf0e1861eab6ec94ea797b95e97af456 | 580f3bda1df885b1c3e169642eb483c2d92d7e3d | refs/heads/master | 2023-05-01T10:26:36.170941 | 2021-02-10T18:24:57 | 2021-02-10T18:24:57 | 73,124,375 | 5 | 4 | null | null | null | null | UTF-8 | R | false | false | 733 | rd | progressStart.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/progressStart.R
\name{progressStart}
\alias{progressStart}
\title{Starts a model step: progress bar, timing, loading inputs}
\usage{
progressStart(steplist, steps, modellist = model)
}
\arguments{
\item{steplist}{List object for the c... |
4d83d6f40b209d41f09cb6c0b476ade4a8d9bbda | 5d3d1b0916535dad8a83a9dad9e23ed77b982d8e | /man/dsquared.Rd | 50b9dda8b3144574f898b22ac47fadb8181445ea | [] | no_license | cran/agrmt | 3d280f0d45e7dcc141556269548296131f2c43cc | 849caf12caabffb97aba71b2b2a54d2d36d2ec4a | refs/heads/master | 2021-11-25T02:48:56.040559 | 2021-11-17T21:20:02 | 2021-11-17T21:20:02 | 17,694,324 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 781 | rd | dsquared.Rd | \name{dsquared}
\alias{dsquared}
\title{Calculate d-squared}
\description{Calculate Blair and Lacy's d-squared.}
\usage{dsquared(V)}
\arguments{
\item{V}{A frequency vector}
}
\details{This function calculates Blair and Lacy's d-squared, a measure of concentration based on squared Euclidean distances. This function f... |
a76448a67586f90aa90b9bacb71866087d9a1569 | 34ff60d1b274e0c4cf41d9f548b44b9792766939 | /Maria/SentimentAnalysis/sentiment_day6.R | 69f5bceaacb2693570aaa838e2dc748023dd4be3 | [] | no_license | thepanacealab/Hurricane-Analysis | 6581f04e71dd2e29986cb15ef45b262eae1901e3 | 87eca0475ce16f8ffb680fd696f2a838ff44bc03 | refs/heads/master | 2020-05-23T15:46:35.195506 | 2019-08-20T02:14:37 | 2019-08-20T02:14:37 | 186,833,715 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,781 | r | sentiment_day6.R |
#Getting all the tweets with geocoded information
allTweetsDay6<-dbGetQuery(conn,
"SELECT
CAST(tweetuser AS varchar(1000)),
date(tweetcreated),
TRIM (LEADING '['
FROM split_part(tweetgeocoord, ',', 1)
) as lat,
TRIM (TRAILING ']'
FROM split_part(tweetgeocoord, ',', 2)
) as long,
t... |
3405aec690bc55a9bad2609fd337d61178e3c4ff | 3d59091d775a71d6bd645e0089be0c1dc4a7ff09 | /cachematrix.R | dcdff5be4cf65a93fcfe6b0c030a3438bfd4340f | [] | no_license | rajeevkmenon/ProgrammingAssignment2 | 044da26760b8fbde7b55c3bc2b96b86e6f6c3bdf | 7edc4b86b9dfab4494556feb37d168ea3c4278ad | refs/heads/master | 2021-01-09T07:03:39.125610 | 2017-12-10T19:54:04 | 2017-12-10T19:54:04 | 37,754,923 | 0 | 0 | null | 2015-06-20T02:24:50 | 2015-06-20T02:24:50 | null | UTF-8 | R | false | false | 1,715 | r | cachematrix.R | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
# makeCacheMatrix creates and stores a list with functions for
# 1. set the the matrix
# 2. get the the matrix
# 3. set the inverse of the matrix
# 4. get the inverse of the matrix
make... |
fb4711c31310cfe9ec6809394afff31c79716d86 | 8967080ed53683afe6783e51bce533c0e7d56e09 | /problem3.R | 34cb061fe811f39cf50c96526067d15149852389 | [] | no_license | niklaslang/UoE_MATH11174_Ass2 | 1598cce5e6dcda57efbfa5c105314e91cc503854 | ff832e588d28ef7a02f4a68b67fabdafcd645776 | refs/heads/master | 2021-02-22T07:49:10.010477 | 2020-04-10T15:56:37 | 2020-04-10T15:56:37 | 245,372,421 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,351 | r | problem3.R | ### (a) ###
# Reading file `GDM.raw.txt` into a data table named `gdm.dt`,
# and storing rsID and coded allele in a separate data table (call it snp.allele.dt)
library(data.table)
gdm.dt <- fread("GDM.raw.txt")
if(!"stringr" %in% rownames(installed.packages())) {
install.packages("stringr") # functions for making... |
25fb8d169c3c3aba6f484721123f75d8aeeb3a3e | dcee1dc28392dee9c57ccf0b3c1c5a20a300fbcb | /man/get_benchmark_fund_relationship.Rd | 1794eed91ec291a07b10b0d5598d6f53a25c78c8 | [] | no_license | stoltzmaniac/AZASRS | 05b1156581ecba3c585f35c8094cb6f244b30bf2 | 3213480feabefd45d1c4e17953ef030def9f72b5 | refs/heads/master | 2020-12-12T13:53:55.141655 | 2020-01-15T15:54:28 | 2020-01-15T15:54:28 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 626 | rd | get_benchmark_fund_relationship.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_benchmark_fund_relationship.R
\name{get_benchmark_fund_relationship}
\alias{get_benchmark_fund_relationship}
\title{Get relationships between funds and benchmarks get_benchmark_fund_relationship}
\usage{
get_benchmark_fund_relationship(
... |
e8ec5729e5b3bcc4f43d9caee389793bac5da158 | 27d0c7693aa36a78f82929c32f0967707b9c0429 | /man/getAE.Rd | 48c80330c570f95a424f181e87be82973660f01d | [] | no_license | suhaibMo/ArrayExpress | 2fbc6f4dce9e53211263caf5c20fc4be1c9e83c9 | 90c0f055598de3320d7e9759408dd983d968ff8f | refs/heads/master | 2020-03-08T20:01:08.935108 | 2018-04-06T08:52:14 | 2018-04-06T08:52:14 | 128,371,135 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 1,626 | rd | getAE.Rd | \name{getAE}
\alias{getAE}
\docType{data}
\title{ Download MAGE-TAB files from ArrayExpress in a specified directory }
\description{
\code{getAE} downloads and extracts the MAGE-TAB files from an
ArrayExpress dataset.
}
\usage{
getAE(accession, path = getwd(), type = "full", extract = TRUE, local = FALSE, sourcedir... |
6e7f22594595cd875876ecd19603a4fd813dad1f | 78cbe41b44c4b6004664261ca40ad000b9369b5e | /run_analysis.R | eca513ac34187ebb34ac4847b28f4b6a99890be0 | [] | no_license | Krish31875/Getting-and-Cleaning-data | 71ea13aeb41d125aeb2038ce5a59e35cfea24c03 | 934c901300e6306d23943ebad569fe658088ebde | refs/heads/master | 2021-01-10T16:52:20.502321 | 2016-02-06T14:29:49 | 2016-02-06T14:29:49 | 51,203,895 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,366 | r | run_analysis.R | gd <- read.csv("getdata_data_ss06hid[1].csv")
getwd()
gd <- read.csv("getdata_data_ss06hid.csv")
dim(gd)
stsplit(names(gd))[123]
strsplit(names(gd))[123]
strsplit(gd, names)
varnames <- strsplit(gd, "wgtp")
varnames <- strsplit(names(gd), "wgtp")
varnames[[123]]
fileurl <- "https://d396qusza40orc.cloudfront.net/getdata... |
470510473cadccb5e93d5594efb214832b96f36e | 08cd51b59bed5318ca5701c31356bd625d862b66 | /corr.R | 3f227bcc38b4969459cc18faa80d34b4a93a084c | [] | no_license | Franzhang/R-Programming | 07f31464a9876c93db656824dfcde75bcc35acae | 2023cd9d1cda730d928253c5cefaca1956c49da7 | refs/heads/master | 2016-09-05T14:34:46.271413 | 2014-08-06T01:07:54 | 2014-08-06T01:07:54 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 554 | r | corr.R | corr <- function(directory, threshold = 0) {
files_list <- list.files(directory, full.names = TRUE)
id <- 1:332
dat <- data.frame()
cor_vec <- c()
nobs <-c()
x <- integer()
y <- numeric()
for(i in id){
dat <- read.csv(files_list[i])
x <- sum(complete.cases(dat))
nobs <- c(nobs, x)
y <- c... |
9a055925f1a6b518773c180da2dc9f30eb5d63f8 | 04b4df4159043ec6db1cdf47b7314d7cf56cd657 | /man/stanova_lm.Rd | a31933f2d19afc3894edadc07cd9971545286625 | [] | no_license | bayesstuff/stanova | f37630f26fecaf4f3e21bfe07def0232ac91ff82 | 988ad8e07cda1674b881570a85502be7795fbd4e | refs/heads/master | 2021-07-04T04:34:07.870525 | 2021-06-06T18:54:59 | 2021-06-06T18:54:59 | 241,858,315 | 8 | 0 | null | 2020-09-18T14:33:54 | 2020-02-20T10:41:11 | HTML | UTF-8 | R | false | true | 2,286 | rd | stanova_lm.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stanova_lm.R
\name{stanova_lm}
\alias{stanova_lm}
\alias{stanova_aov}
\alias{stanova_glm}
\title{Estimate ANOVA-type models with rstanarm}
\usage{
stanova_lm(formula, data, check_contrasts = "contr.bayes", ...)
stanova_aov(formula, data, che... |
53f5b8529eb08ab7b2f3da50b8bf347515eac05d | 66278b8e44b1ed85d37868ae1ea27d5514a77138 | /rlang_201Grade/.Rproj.user/38390253/sources/per/t/2871C139-contents | efb28010a6a9cda2c0cd10ce01e602440bfacff5 | [] | no_license | amkan5/R | d26c7bd11e66d9e830438f8d8cd01bcba75cd012 | 1477f9bdf16e27495c09bbe04011a0c8e0757d90 | refs/heads/master | 2020-03-23T04:37:33.476904 | 2018-08-03T08:39:56 | 2018-08-03T08:39:56 | 141,095,474 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 940 | 2871C139-contents | ## dplyr
# filter() 행추출
# select() 열추출
# arrange() 정렬
# mutate() 변수추가
# summarise() 통계치산출
# group_by() 집단별로 나누기
# left_join() 데이터합치기(열)
# bind_rows() 데이터합치기(행)
# view() 뷰어창에서 데이터 확인 !! 주의... v가 대문자
install.packages("dplyr")
library(dplyr)
path <- getwd() #working directory 의 약자 지금 작업하는 위치
path
setwd("csv_exam") #worki... | |
2677d3f342a8b893007d0ca7d23fdd1c9b7c8ab2 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/nlmeU/examples/missPat.Rd.R | f14fe7329549afba23349b6f1535a4b93914aea9 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 235 | r | missPat.Rd.R | library(nlmeU)
### Name: missPat
### Title: Extract pattern of missing data
### Aliases: missPat
### ** Examples
dtf <- subset(armd.wide,
select = c(visual12, visual24, visual52))
missPat(dtf, symbols = c("?","+"))
|
887475c3095976c7d9996ca17d1523966849fa29 | 0885e50ada7d5d8df3e3418a63ec126f5e599477 | /Predict_Extract/10k_buffer.R | 13fadc0c0f6d73fd6e4d21d940de88abbeb48de0 | [
"Unlicense"
] | permissive | hamishgibbs/Gibbs_Thesis_R | badda547bef0923d2c4dac151ef4eb774c64b57f | 71e7661d565c0c0b3d6b82d8078d9ea90da61b9e | refs/heads/master | 2023-07-03T02:35:05.536420 | 2019-08-12T09:49:27 | 2019-08-12T09:49:27 | 201,491,440 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,311 | r | 10k_buffer.R | library(rgdal)
library(rgeos)
library(sp)
library(spatial)
library(raster)
#Make a point file with all the points within 10 k of the study site
pts = readOGR(dsn='F:/Predictive_Modelling/Vector_Data', layer='Cell_Centroids')
boundary = readOGR(dsn='F:/Field_data/04_Colombia_results', layer='plot_boundary')
... |
2a0ee03612e428c76ae88be6288890211c494e89 | 5168565cb17124d490b1019e5e2f8e06433936a0 | /cachematrix.R | a14eda015f5be28d749ece3c5b4d825cfee3d196 | [] | no_license | yamanarora/ProgrammingAssignment2 | ac37b46f703131ab05d08b994094a46a5e2ec774 | 472e3dc3e579d10a82521192ace4a5cd486d4a89 | refs/heads/master | 2021-01-12T09:09:48.422428 | 2016-12-18T10:54:16 | 2016-12-18T10:54:16 | 76,776,379 | 0 | 0 | null | 2016-12-18T10:26:50 | 2016-12-18T10:26:49 | null | UTF-8 | R | false | false | 1,106 | r | cachematrix.R | ## Here are two functions that are aimed at getting the inverse of a matrix (assumed to be invertible). The aim is to check the cache
## for an existing solution, and if solution is not present, then calculate the inverse and store it in the cache.
## The function makeCacheMatrix accepts a matrix whose inverse is t... |
4294b8832751dc1f724edd9a086a85748d0170f2 | 55a5e246d1318275a5a0f1fc9b2e1b080ab26fe7 | /man/transform_adjust_brightness.Rd | c287e66ca4a28fa3dfa108c5168c420a3521d924 | [
"MIT"
] | permissive | mohamed-180/torchvision | 610577f5b1dec7a628df8c047c41ec18376e35f5 | 0761c61441f838f1b0c6f3624c40542934fb24f8 | refs/heads/main | 2023-07-14T14:20:21.225664 | 2021-08-23T17:18:10 | 2021-08-23T17:18:10 | 399,161,368 | 0 | 0 | NOASSERTION | 2021-08-23T15:48:55 | 2021-08-23T15:48:54 | null | UTF-8 | R | false | true | 2,067 | rd | transform_adjust_brightness.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/transforms-generics.R
\name{transform_adjust_brightness}
\alias{transform_adjust_brightness}
\title{Adjust the brightness of an image}
\usage{
transform_adjust_brightness(img, brightness_factor)
}
\arguments{
\item{img}{A \code{magick-image},... |
94d15cea612b3c0e2bece9f0d810e63504eb5514 | 80dfcda1ebcb091dd2bef1d566683c206967aa7c | /cachematrix.R | 1c604c6465139e4d61bb7ccab2c92a196196f8ab | [] | no_license | Umar412/ProgrammingAssignment2 | b68339979f62b2ba94fc703cd808c361e2367d31 | 769ca47a7039761569be4f4da0fbe3d66cc47c99 | refs/heads/master | 2022-11-05T21:41:11.269821 | 2020-06-16T20:15:23 | 2020-06-16T20:15:23 | 272,793,164 | 0 | 0 | null | 2020-06-16T19:20:02 | 2020-06-16T19:20:01 | null | UTF-8 | R | false | false | 1,157 | r | cachematrix.R | ## makeCacheMatrix: This function creates a special “matrix” object that can cache its inverse.
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
f <- function(y){
x <<- y
inv <<- NULL
}
g <- function() {x}
setInverse <- function(inverse) {inv <<- inverse}
getInverse <- function() {inv}
lis... |
bdb20fc129dec5ef018b5a109543e03faccf662c | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/uwIntroStats/examples/tableStat.Rd.R | fc2f484e5bfd1617b89dd0f5434d9bb97715e765 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,795 | r | tableStat.Rd.R | library(uwIntroStats)
### Name: tableStat
### Title: Table of Stratified Descriptive Statistics
### Aliases: tableStat tableStat.default tableStat.do print.tableStat
### Keywords: ~kwd1 ~kwd2
### ** Examples
# Load required libraries
library(survival)
# Reading in a dataset
mri <- read.table("http://www.emersonsta... |
f43580b65d5b378bf5cb94ad2cd2d3277bc66c87 | ab5871840e0b0e01d03feec960bd6478a5e49dca | /man/tests.Rd | 3cdc634c4091b60bdae383006b10f905eeb8fc5a | [] | no_license | jeff-hughes/paramtest | 2551cf59e140406db965f3dee3b89cb547be1144 | bee7be25e9bd6ef6c69c9d59291f0c451db3cfca | refs/heads/master | 2020-05-21T06:15:45.463415 | 2017-10-24T14:16:49 | 2017-10-24T14:16:49 | 84,586,183 | 2 | 2 | null | null | null | null | UTF-8 | R | false | true | 731 | rd | tests.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/helpers.R
\name{tests}
\alias{tests}
\alias{tests.paramtest}
\title{Return the parameter values that were tested by paramtest.}
\usage{
tests(test, ...)
\method{tests}{paramtest}(test, ...)
}
\arguments{
\item{test}{An object of type 'paramt... |
ca170da4e1541ca0f15f2a1c411f28dbb2d8dbf8 | 18a07f5c173da511804cb30f4604d063063a34f9 | /man/gamma_coin.Rd | 3d46e978fdec7dbc17c41dd1e8c9792b2642e464 | [
"CC-BY-4.0"
] | permissive | rchan26/layeredBB | b0b61837e94f1c64b5aa9542e9608a332d2ee4c2 | d40cd35bbb055409c21d2cc6612d00bc0fd80b94 | refs/heads/master | 2022-03-07T13:16:42.029976 | 2022-02-25T13:24:19 | 2022-02-25T13:24:19 | 188,111,543 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,085 | rd | gamma_coin.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RcppExports.R
\name{gamma_coin}
\alias{gamma_coin}
\title{Gamma coin flipper (Algorithm 26 in ST329)}
\usage{
gamma_coin(u, k, x, y, s, t, l, v)
}
\arguments{
\item{u}{simulated value from random U[0,1]}
\item{k}{integer value starting index... |
335981be08673fef2876a6ca03b4e5c14f3a0cfc | 29585dff702209dd446c0ab52ceea046c58e384e | /Luminescence/R/calc_HomogeneityTest.R | 3080d581f30a78cb669982d9850c8a25a6bb1d79 | [] | no_license | ingted/R-Examples | 825440ce468ce608c4d73e2af4c0a0213b81c0fe | d0917dbaf698cb8bc0789db0c3ab07453016eab9 | refs/heads/master | 2020-04-14T12:29:22.336088 | 2016-07-21T14:01:14 | 2016-07-21T14:01:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,994 | r | calc_HomogeneityTest.R | #' Apply a simple homogeneity test after Galbraith (2003)
#'
#' A simple homogeneity test for De estimates
#'
#' For details see Galbraith (2003).
#'
#' @param data \code{\linkS4class{RLum.Results}} or \link{data.frame}
#' (\bold{required}): for \code{data.frame}: two columns with De
#' \code{(data[,1])} and De error \... |
278ccfb35bfeda2c652a18586fb2f00ae6e9c0b9 | 16a4a8be49003375bdb2868f472697fe5313b62e | /Exploratory/Week3/plots3and6.R | f478639fe22ef5569c82d12a3d570d9530044091 | [
"MIT"
] | permissive | llattes/datasciencecoursera | 42cd3c0881b79fb71ffcad08abd75ff926782961 | bb807e97a077d1167780fac51413b526ab2aa62d | refs/heads/master | 2021-01-17T15:25:23.879098 | 2015-09-02T17:40:17 | 2015-09-02T17:40:17 | 27,514,469 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,023 | r | plots3and6.R | # Plot 6
# ------
## PA 2: Exploratory Data Analysis
## Plot 6
##
## Libraries needed:
library(ggplot2)
## Set working directory
setwd("D:\\Data Science Specialization\\Exploratory Data Analysis\\Course Project")
## Step 1: read in the data
## This first line will likely take a few seconds. Be patient!
if(!exists("... |
d9feab5308bc6c9798956f47dffba6157ff28cf1 | ce58f13cf8a15cc817317ef3ee4d55728972b663 | /plot2.R | 7e504ecb14ed28940271e56e542617d5e2f98bf4 | [] | no_license | Lkhagvaa-erdenesuren/ExData_Plotting1 | 9fb9767d0581f14dfd61ae8589f25d8a86a70731 | f7dc74e431543c2cc55cfc89805a3aa746627bef | refs/heads/master | 2020-12-03T01:41:31.593323 | 2016-01-11T17:39:16 | 2016-01-11T17:39:16 | 49,362,564 | 0 | 0 | null | 2016-01-10T10:35:51 | 2016-01-10T10:35:50 | null | UTF-8 | R | false | false | 560 | r | plot2.R | library(datasets)
alldata <- "./data/household_power_consumption.txt"
data <- read.table(alldata, header=TRUE, sep=";", stringsAsFactors=FALSE, dec=".")
powerconsump2daysdata <- data[data$Date %in% c("1/2/2007","2/2/2007") ,]
date_time <- strptime(paste(powerconsump2daysdata$Date, powerconsump2daysdata$Time, sep=" "),... |
e1dcf270a1aa095ed0d89e1cd48a8d1651083161 | b00d5c221259a7f5d899d84e04ef57712b312a4e | /rprog.R | 150b6bbf6d0ca6888a0af2ca11e7e92b18270b2e | [] | no_license | masymbol/customer_experience | 365e4de7139fc3a8af61ab248c6d22ee9cb792fc | 4c82ef8c3611dc5d543aacc0e0ea7ad0b892ac8a | refs/heads/master | 2021-03-27T16:15:30.131943 | 2014-12-27T10:23:00 | 2014-12-27T10:23:00 | 24,134,394 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,993 | r | rprog.R | library(bitops)
library(digest)
library(RCurl)
library(NLP)
library(RColorBrewer)
library(ROAuth)
library(bitops)
library(RJSONIO)
library(stringr)
library(tm)
library(httr)
library(wordcloud)
library(devtools)
library(twitteR)
library(plyr)
library(stringr)
library(twitteR)
api_key <- "fmC6OcWB4jqwBT7bRmVssagmP"
api_s... |
c714b0a06b07f97ab0aab69e8c820886c41a63e6 | 860efbde82499c1cc307e36b57f6af41fe37225e | /man/analyze.p2.Rd | a89f9e54e97fd4d6eb107ba855a567dead8513a1 | [] | no_license | cran/gainML | 92a2ffb79ca5026e9e509edcdc1cc43b151ddb92 | f85e402726004d6f9a31f812cc0a66bf83eabffc | refs/heads/master | 2020-12-21T23:34:19.542072 | 2019-06-28T12:40:07 | 2019-06-28T12:40:07 | 236,601,381 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,696 | rd | analyze.p2.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/period2.R
\name{analyze.p2}
\alias{analyze.p2}
\title{Apply Period 2 Analysis}
\usage{
analyze.p2(per1, per2, opt.cov)
}
\arguments{
\item{per1}{A dataframe containing the period 1 data.}
\item{per2}{A dataframe containing the per... |
8a95d9a7cc8599202069287b1376f471cb8128d9 | 5524d53f97e4af319ceebc8bd5dabd2e81fd789c | /R/glossary_class.R | ad64da62b772eb5a0c067200af90ffce891898c5 | [] | no_license | zachary-foster/glossary | 220f9d51b38a85e7828cb4e0ab8ab7f739413dac | fd43b669d1bcd326722b0d8faaead83357b82db2 | refs/heads/master | 2020-03-22T17:14:33.280555 | 2018-07-14T09:04:01 | 2018-07-14T09:04:01 | 140,383,414 | 6 | 1 | null | 2018-07-14T09:00:00 | 2018-07-10T05:51:03 | R | UTF-8 | R | false | false | 6,960 | r | glossary_class.R | #' Glossary class
#'
#' This is used to add terms to a glossary
#'
#' @param definitions_path Where the the definitions of terms are stored. This
#' is used to show the definitions when hovering over a glossary term in the
#' text.
#' @param glossary_path The file the glossary will be added to. This is used to
#' ... |
1feb8b1aa1ea26c9fba16572332136a5c23b179b | 9465052503f31b26d516a85808a95a5d1ae5e11c | /tests/testthat/test-anomaly.R | 94f020e64b4e00487e824229a8078e00c7291d4e | [
"Apache-2.0"
] | permissive | ecmwf/caliver | 26e03662a1c2c979c00d178e8ac6e59c58b6f701 | 1b82bc4e5476cba3a16782370505bc0b50241569 | refs/heads/master | 2022-02-25T01:44:23.904450 | 2022-02-21T17:51:40 | 2022-02-21T17:51:40 | 73,203,648 | 16 | 7 | null | 2021-03-18T13:35:00 | 2016-11-08T16:11:16 | R | UTF-8 | R | false | false | 150 | r | test-anomaly.R | context("anomaly")
test_that("Testing the file anomaly.R", {
x <- anomaly(r, b, asEFFIS = TRUE)
expect_true(raster::cellStats(x, max) == 6)
})
|
58f9ddd1031a3b569b8bc56eab70b3c93c2d5c98 | cbede1f778ec1b69c51d5f90e66edf1bfeee18a0 | /README.rd | 768e9611b9850bb19f8df57e6535dc891726d633 | [] | no_license | gbsnaker/django_demo | 88e862176be5ebbb3874a9d9a6b4e386f65c2b58 | 0e39a886b5747e7687a9f856971201cfb38a743a | refs/heads/master | 2020-12-30T15:54:32.424971 | 2017-05-13T18:54:09 | 2017-05-13T18:54:09 | 91,182,977 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 136 | rd | README.rd | # django demo
<h6>add study 3</h6>
<h6>add bootstrap</h6>
<h6>sublime bootstrap autosnippet s3-***</h6>
<h6>add jinja2 variables </h6>
|
82ad9085b0cec8432b6a0a1c9114605ec32fd4eb | d3902442ba45fddad61a36dd844fcd0862a08f90 | /man/check_connection.Rd | 4e224b9edb1b9911c7737226908e8eb3d34ad66b | [
"MIT"
] | permissive | JasperHG90/sleepsimRapiClient | d003caca1d2e7a46cfcc73f38ab108f18b14917c | 6ba993ee7565490e7b5ff3123622f034bb60d194 | refs/heads/master | 2021-03-07T20:56:14.915862 | 2020-05-14T08:30:35 | 2020-05-14T08:30:35 | 246,296,409 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 318 | rd | check_connection.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api.R
\name{check_connection}
\alias{check_connection}
\title{Check if connection to server is possible}
\usage{
check_connection()
}
\value{
TRUE if connection active, else FALSE
}
\description{
Check if connection to server is possible
}
|
c9e87a52f930a374903a25bed1648eb1037ccbe3 | 5dc84c75f79ef6114daa20080d0677200c037f98 | /man/gdcFilterDuplicate.Rd | 78ff653ce7fbf8d84da9e4f71c9dd50c78696fc7 | [
"Apache-2.0"
] | permissive | rli012/GDCRNATools | 6a25f3e72ea716b4f60e36e725caea557f6a6e29 | e2c4f4e8c40041b1f3d374f9a5a561949e803830 | refs/heads/master | 2023-08-25T04:18:18.876861 | 2022-08-20T01:44:51 | 2022-08-20T01:44:51 | 112,437,042 | 14 | 9 | Apache-2.0 | 2023-08-04T09:01:57 | 2017-11-29T06:37:47 | R | UTF-8 | R | false | true | 690 | rd | gdcFilterDuplicate.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/gdcFilterSamples.R
\name{gdcFilterDuplicate}
\alias{gdcFilterDuplicate}
\title{Filter out duplicated samples}
\usage{
gdcFilterDuplicate(metadata)
}
\arguments{
\item{metadata}{metadata parsed from \code{\link{gdcParseMetadata}}}
}
\value{
A ... |
61fa8b07fb37f3c7baca902f9dbf4a347aa8e71c | be8c9660ff29a44d1835b74b3ec861cd76adb834 | /methods/analysis-glint_get-glint-dependencies.R | 8a4e10b5647147102bb67c92c2ed781cc18fc26d | [] | no_license | metamaden/recountmethylation_flexible-blood-analysis_manuscript | ec9ba3666db953430ec1be509a826d45fba97f57 | ec835f346da6bcb628ac262d22c5827936610981 | refs/heads/main | 2023-04-16T20:18:31.234484 | 2023-02-02T20:33:38 | 2023-02-02T20:33:38 | 401,501,606 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 167 | r | analysis-glint_get-glint-dependencies.R | library(basilisk)
# define env attributes
env.name <- "dnam_si"
pkgv <- c("hnswlib==0.5.1", "pandas==1.2.2", "numpy==1.20.1",
"mmh3==3.0.0", "h5py==3.2.1") |
dd576a611a4d21d2d770b615f83eb8f9f2ab75cd | 34b94b2de56a8f7023487b0e33b5eb9d1863ce09 | /man/get_pm_fund_info.Rd | e2195a08ae18afc55033d5b3114da6fad87222ec | [] | no_license | AZASRS/AZASRS | b42a9ddba0c249281e723ce160a633aedfc583b0 | b862856345f658664ed7b0cc1e55899fa25e552d | refs/heads/master | 2021-06-15T18:27:33.491298 | 2020-09-24T17:07:40 | 2020-09-24T17:07:40 | 137,259,227 | 0 | 3 | null | 2021-01-08T16:31:08 | 2018-06-13T19:06:52 | R | UTF-8 | R | false | true | 1,777 | rd | get_pm_fund_info.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_pm_fund_info.R
\name{get_pm_fund_info}
\alias{get_pm_fund_info}
\title{Get all pm_fund_info}
\usage{
get_pm_fund_info(
con = AZASRS_DATABASE_CONNECTION(),
add_benchmark = FALSE,
return_tibble = TRUE
)
}
\arguments{
\item{con}{is a d... |
27ca26d2459f261480cf7e92256bd5ffcf58713b | 2af4939100afa621c6c9fedf4749bb10798bf209 | /Transitions.Rd | b276b84610f03f92edec4914d451437334a5258e | [] | no_license | mcattau/code_efficiency | ef0688197c5e388e6e1814f2ac2160b2997f385a | b81027b7fd3e62dd763136fb0d0cd8e81e74711e | refs/heads/master | 2020-12-30T23:36:58.170672 | 2017-04-05T17:58:54 | 2017-04-05T17:58:54 | 86,605,674 | 0 | 1 | null | 2017-04-06T18:01:42 | 2017-03-29T16:35:27 | R | UTF-8 | R | false | false | 84,086 | rd | Transitions.Rd | ## Megan Cattau
## Earth Lab, Project Forest
## Contact info: megan.cattau@gmail.com or megan.cattau@colorado.edu, 706.338.9436
## Project: Disturbance Interactions in the Southern Rockies
## Project overview: Forest transitions (i.e., Changes in ecosystem type / forest composition and structure) as a function of distu... |
005fa17f202717f0fc92ba502a1848e7618ad116 | 408220de1e7ad6a66fee48b86522bbb0eef9759f | /barcodes_file/barcodes_check.R | 8a09ad3b52b544c707dc9be88cc0e2ed404e5979 | [] | no_license | Wolflab/erisor | 942414f5b182a56f8ebd5106960513a44fdca522 | 7bda5af88e8a0ad0aa0e7a91abff0f81a8025ebc | refs/heads/master | 2020-06-24T23:14:22.572548 | 2017-08-03T12:43:13 | 2017-08-03T12:43:13 | 96,948,658 | 0 | 0 | null | 2017-07-12T00:32:48 | 2017-07-12T00:32:48 | null | UTF-8 | R | false | false | 370 | r | barcodes_check.R | #setwd('/Users/jimblotter/Desktop/Grad_School/Data_Analysis/erisor/barcodes_file/')
install.packages(compare)
library(compare)
before <- read.csv("before.csv", header = FALSE)
after <- read.csv("after.csv", header = FALSE)
before
after
for(i in before[1,]){
if(i == after[]){
if i %in% after{
print("oops")
... |
5a6ddcad7fdd879f72d289a9ce73b416048939e2 | 8a270978e710878945f37852d0be9f73cfa75078 | /other/fussballdaten.R | ea2e6a330fb29fadbdca193bd153f7df4e31f137 | [] | no_license | bydata/football_data | bdcacdfff7d8d099aaf93637a0f131c48462ae01 | 44e59cd8349f2a02df983b0d16eafc37fbed0e4e | refs/heads/master | 2023-07-08T02:20:20.089361 | 2023-06-30T15:22:04 | 2023-06-30T15:22:04 | 145,601,237 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 17,111 | r | fussballdaten.R | library(tidyverse)
library(rvest)
library(parallel)
library(ggthemes)
# retrieve page content - takes either a URL string or a vector of strings which constitute a url (will be collapsed to one string using "/")
get_content <- function(url) {
if (is.vector(url)) {
url <- str_c(url, collapse = "/")
}
#conten... |
9af8809727b23a2c4e47d77de2ce98648fffb440 | 96dac3b379db632cc577600f1041ecafbddca400 | /scripts that do not actuially work/data processing script for tracking.R | 53744e89843d3cc6f2998c08d9b62ac42eaf5d0b | [] | no_license | kaye11/Some-R-scripts | 78e53b0c37254945120fca91255801b392835cb1 | 632b16a3269c7ce5c7c14efceb26fb02bf66eac1 | refs/heads/master | 2021-01-23T06:44:20.200098 | 2016-09-01T18:56:25 | 2016-09-01T18:56:25 | 21,462,015 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 881 | r | data processing script for tracking.R | #Changing directory
getwd()
setwd("D:\\Karen's\\PhD\\R program")
getwd()
##Rename Data
t1<- trackdata2
## GrossDistance (GD)
GD <- aggregate( V ~ A , data = t1 , sum , na.rm = TRUE )
## Computing the NetDistance (ND)
## Split the data
dfs <- split(t1,t1$A)
## calculation
NDtemp1 <- sapply( dfs , function(x) dist( x... |
bbe3e3d4fc3aeb8dcbbad48dff599b97e220bc18 | 53430551f5f65103243e349f27a8283c5f54ec98 | /pollutantmean.R | 67526f0fecac0e5518f149860e7867e8df0ca6df | [] | no_license | rserran/ProgAssignment-1 | 3761bfd1ee4a64ec408d5ce94a4b5633123f118c | 26399cacf0053aa18cf0c42cfef3d5fd35b479a8 | refs/heads/master | 2020-04-17T12:25:51.723626 | 2019-01-19T19:09:59 | 2019-01-19T19:09:59 | 166,578,754 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 822 | r | pollutantmean.R | ## polluttant function calculates the mean of the poluutant selected from
## specdata directory monitors selected (id)
## the function assumes directory argument is located in the R working directory
pollutantmean <- function(directory, pollutant, id = 1:332) {
path <- paste(getwd(), directory, sep = "/")
f... |
9d3fc6d12dbc03d80df9b5c6771eed41cea3262f | c9f1434aaae3b1606acb71ad5594ba2ef2d7a233 | /R/rlba.R | c47d08498589d0a63d9ab26d17473cedd3c483ba | [] | no_license | cran/glba | 84a61aee7b31416a47352ad04e95961b1a299368 | 2e43a7bd8ce543cf92056ad7a85d47d74f14b354 | refs/heads/master | 2022-05-21T14:29:01.142929 | 2022-05-02T12:01:52 | 2022-05-02T12:01:52 | 30,880,069 | 2 | 2 | null | null | null | null | UTF-8 | R | false | false | 700 | r | rlba.R | rlba <-
function(n,b,A,vs,s,t0,st0=0,truncdrifts=TRUE){
n.with.extras=ceiling(n*(1+3*prod(pnorm(-vs))))
drifts=matrix(rnorm(mean=vs,sd=s,n=n.with.extras*length(vs)),ncol=length(vs),byrow=TRUE)
if (truncdrifts) {
repeat {
drifts=rbind(drifts,matrix(rnorm(mean=vs,sd=s,n=n.with.extras*length(vs)),ncol=length(vs),b... |
8046d060517bd0fe018ad2d9565d62e7271d18d6 | 875c89121e065a01ffe24d865f549d98463532f8 | /man/liveArrayTimes.Rd | 3f78ca53dc2d448b812db6a839ab0aff83f79d4f | [] | no_license | hugomflavio/actel | ba414a4b16a9c5b4ab61e85d040ec790983fda63 | 2398a01d71c37e615e04607cc538a7c154b79855 | refs/heads/master | 2023-05-12T00:09:57.106062 | 2023-05-07T01:30:19 | 2023-05-07T01:30:19 | 190,181,871 | 25 | 6 | null | 2021-03-31T01:47:24 | 2019-06-04T10:42:27 | R | UTF-8 | R | false | true | 437 | rd | liveArrayTimes.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/load.R
\name{liveArrayTimes}
\alias{liveArrayTimes}
\title{Assign live times to arrays}
\usage{
liveArrayTimes(arrays, deployments, spatial)
}
\arguments{
\item{arrays}{The array list}
\item{deployments}{the deployments list}
\item{spatial}... |
d0d9a61779389ee86a6de1f50b37357fa7c3a175 | 5adc0dfe6cae8f90cc20cd149bf03852b0396e34 | /tests/testthat/test_clean_projlead.R | 0c36f4c4a85afc7f6052ab1fde34c0126808161a | [
"MIT"
] | permissive | AGROFIMS/ragrofims | 43664011980affa495c949586bde192d08d4b48e | bc560a62c19c30bbc75615a19a4b9f8a235f7ddf | refs/heads/master | 2023-02-21T08:49:34.989861 | 2021-01-20T16:22:48 | 2021-01-20T16:22:48 | 277,626,238 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,254 | r | test_clean_projlead.R | library(ragapi)
library(ragrofims)
context("Test for clean and get metadata from project lead")
test_that("Test get_projlead_metadata for testq0 - API ver. 233 - no combos", {
out <- get_projlead_metadata(studyId = 3,format = "data.frame",
serverURL = "https://research.cip.cgiar.o... |
e218ddf0ebe53cfb9c9bfcfa33d212c36709d147 | 9dc507cc478cccf7bc4c94dd46699e308a93b08f | /PRC/prc_raw.v3.R | d76414ae8a321ac1274e2a678ddc6839ef31146b | [] | no_license | Lupenrein/R-scripts_MA | 9b12bba332cf91cfd33fd73e96f6ebfc5c85d9ac | a13e25a67d9883715f8ca38c3a12db181680b370 | refs/heads/main | 2023-04-07T07:03:26.099960 | 2021-03-29T06:41:37 | 2021-03-29T06:41:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,663 | r | prc_raw.v3.R | ## Script for a principal response curve without statistics
## Requirements for datafile:
## - populations (type) coded as follows: 0 = T0rb (reference), 1 = T2rb, 2 = T0ina, 3 = T2ina, 4 = T2cur
## Script by Natalie Dallmann, Institute for environmental research, RWTH
## Version 3 (24.02.2021)
## Load required ... |
3933d953f824fb0f1b6dae60db53fbab0e494fc0 | 41a8f96b9449fad33b54797dec9ccb1704a2c298 | /R/utils.R | aa35353798603e90185dcd0d5866dfee0bfd3459 | [] | no_license | borangao/BSLMMSusie | c02fbf9caf04755d361f4088134ec6133b51629c | 2cbd0d50832c2356a2426aa3c99082a8d238e284 | refs/heads/master | 2023-03-07T12:15:24.728644 | 2021-02-18T04:00:05 | 2021-02-18T04:00:05 | 331,758,215 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,551 | r | utils.R | susie_slim = function (res)
list(alpha = res$alpha,niter = res$niter,V = res$V,sigma2 = res$sigma2)
n_in_CS_x = function (x, coverage = 0.9)
sum(cumsum(sort(x,decreasing = TRUE)) < coverage) + 1
in_CS_x = function (x, coverage = 0.9) {
n = n_in_CS_x(x,coverage)
o = order(x,decreasing = TRUE)
result = rep(0,le... |
457ba376ab9dfb5399197731beb383444be74511 | 925a1586e11c8f2dff5d43a0b2591bc0d3866aca | /week02-02.R | 829ac0cccd15bbde0889c5c0952d4aae60ab2a97 | [] | no_license | znehraks/2021-1-Statistical-Analysis-With-R | 362baf576c3c4ba46ecc425858f6c4750805eeae | 052049f9e3004e549c5cf087fa724425c56f05d8 | refs/heads/master | 2023-06-02T09:23:20.376185 | 2021-06-14T17:46:51 | 2021-06-14T17:46:51 | 376,593,478 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,021 | r | week02-02.R | dim(midwest)
str(midwest)
#1
midwest$ratio = midwest$popasian/midwest$poptotal
x = mean(midwest$ratio)
midwest$grade = ifelse(midwest$ratio >= x, "large", "small")
table(midwest$grade)
qplot(midwest$grade)
#2
library(dplyr)
midwest_new = midwest %>%
arrange(desc(midwest$ratio)) %>%
select(county, ratio) %>% hea... |
04d797bfe558c528dd35f4a0fcdae4fef53df3ce | 4da5c1df47a2561677163a83f74a4dd7b6bb48fd | /plot2.R | 848c422eb1befb3d176a05732b50baee6d508687 | [] | no_license | jlg373/ExData_Plotting1 | 847b1d5b8b133ae31331674c49f7e4878ab1a862 | 38cd037122f68575492532d88f0d2bdd54e10aa1 | refs/heads/master | 2021-09-05T07:06:00.600491 | 2018-01-25T02:11:52 | 2018-01-25T02:26:23 | 118,835,178 | 0 | 0 | null | 2018-01-24T23:27:22 | 2018-01-24T23:27:21 | null | UTF-8 | R | false | false | 1,143 | r | plot2.R | # Plotting Assignment 1 for Exploratory Data Analysis -
# This script generates the second graphic in the assignment - global active power as a function of time.
# If appropriate data file does not exist in working directory, download and unzip.
if(!file.exists("household_power_consumption.txt")){
download.fi... |
ecdfc7479641870a2010bff2c71876926e2dba8c | 4e01acf5a07af95846300ed1016edf601fdbb6cc | /Rprogramming/assignment1/mysubmit.R | 5caa5e27eced377db5094334641fe12857c021c0 | [] | no_license | carolcoder/datasciencecoursera | 5b5c8e9ca270ba961061c4ae4b5dcacfdcf1bab5 | d80a4ac780506179ab1e25cf559256f2f9de4a31 | refs/heads/master | 2021-01-23T02:49:10.301308 | 2015-08-07T20:06:33 | 2015-08-07T20:06:33 | 30,250,558 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 35 | r | mysubmit.R | source("submitscript1.R")
submit() |
c5e77bc37d17c33ca009a2354a615246fb24a76e | 7b7519e5b264e67d0c837a6a4024c965bca827ac | /programs/summary_variables/bootstrap/make_leaf_p_retranslocation_coefficient_bootstrap.R | c5fbb79af4bc1aa4f11f04622566163eb208c37c | [] | no_license | SoilTSSM/EucFACE_P_synthesis | 32b0cb47b31d4eddbed6739f20142bfac80ecd14 | 006c65fdef6203b77f03afe1fb05b261f16ec6b5 | refs/heads/master | 2020-04-05T20:44:57.715117 | 2018-11-09T04:53:59 | 2018-11-09T04:53:59 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,747 | r | make_leaf_p_retranslocation_coefficient_bootstrap.R | #- Make the retranslocation coefficient
make_leaf_p_retranslocation_coefficient_bootstrap <- function(){
df <- read.csv("download/FACE_P0020_RA_leafP-Eter_20130201-20151115_L1.csv")
### setting up the date
df$Date <- paste0("1-", as.character(df$Campaign))
df$Date <- as.Date(df$Date, "%d-%b-%y")
... |
06089eb06adc0611a740473d927e17f957b27f2e | ba0c0961efc8eccdb432ea21552f65d461f44518 | /tests/testthat/test_biosample_api.R | 1a88228dcf6e5d34a12c0682fbdc1dfcafde95b7 | [] | no_license | waldronlab/omicidxClientR | a3addddb5c455228a6d33d4af7ea9360ff1e8c6f | 2296e785c7acc670d9c7f9821934cbbc80bc2741 | refs/heads/main | 2023-03-25T22:50:15.624236 | 2021-03-18T17:41:30 | 2021-03-18T17:41:30 | 349,137,249 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,487 | r | test_biosample_api.R | # Automatically generated by openapi-generator (https://openapi-generator.tech)
# Please update as you see appropriate
context("Test BiosampleApi")
api.instance <- BiosampleApi$new()
test_that("BiosampleByAccessionBiosampleSamplesAccessionGet", {
# tests for BiosampleByAccessionBiosampleSamplesAccessionGet
# bas... |
f7fa0ad2bed996352c56d6e73f94d4929787ca29 | ba2b161d5fa2ade933922a8d6719e73ea41e2560 | /run_analysis.R | b58db44df011d552ad04b577db3f335d308e097b | [] | no_license | faaransaleem/course3project | ab98553bcad8c13ce464941b6731bf5a2b4210c2 | ef8c4f379276d29fe7a83205dffc21ab5801306a | refs/heads/master | 2020-03-21T00:21:09.186712 | 2018-06-20T11:43:24 | 2018-06-20T11:43:24 | 137,888,633 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,567 | r | run_analysis.R | library("data.table")
##Play with standard files
act <- read.table("UCI HAR Dataset/activity_labels.txt")[,2]
features <- read.table("UCI HAR Dataset/features.txt")[,2]
ourfeatures <- grepl("mean|std" , features)
##Play with Test files
xtest <- read.table("./UCI HAR Dataset/test/X_test.txt")
ytest <- read.ta... |
cf03d1a9da4fb9d0eeee970f4508461db24afb1d | deeb61b4710c15dd88c79843c0b80bdff0231d57 | /R/krikinton-package.R | ec56a8007f41f98686692630e587c8e13e3cd3c0 | [
"LGPL-2.0-or-later",
"BSD-3-Clause",
"Apache-2.0",
"LicenseRef-scancode-proprietary-license",
"MIT"
] | permissive | paithiov909/krikinton | e7dcd9035facdedd17061bf64662441315710e8f | d5b8f716b627379beab5769b4b51a3a70ddae3e5 | refs/heads/main | 2023-06-03T20:27:37.525416 | 2021-06-21T14:14:13 | 2021-06-21T14:14:13 | 304,878,749 | 1 | 0 | MIT | 2021-02-15T16:56:49 | 2020-10-17T13:00:50 | R | UTF-8 | R | false | false | 351 | r | krikinton-package.R | #' krikinton: rJava Wrapper of Sudachi and Kintoki
#' @docType package
#' @name krikinton
#' @import rJava
#' @import dplyr
#' @import purrr
#' @importFrom jsonlite toJSON
#' @importFrom pkgload is_dev_package
#' @importFrom stringi stri_enc_toutf8
#' @importFrom tibble tibble as_tibble
#' @importFrom tidyr separate
#'... |
50f958d3fbff169154dfb6cb849418b0ae272a13 | 17a7f2333706ad280247d187f4aedbeb32714714 | /ui.R | 46700db4f8109312f8812b4ee4de33303af05967 | [] | no_license | t707722/city-weather | 90c3599d55f8ad0104dc2686ffacc132187a0eea | ef1eafcd9e246f8518b8ee0054c63be661f9d68b | refs/heads/master | 2020-09-08T02:13:14.001145 | 2018-09-04T13:26:26 | 2018-09-04T13:26:26 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 502 | r | ui.R | shinyUI(
fluidPage(
theme = shinytheme("yeti"),
titlePanel("Погода в российских городах-миллионниках"),
tags$br(),
fluidRow(column(4, offset = 1, selectInput("city", NULL, choices = cities$city, selectize = TRUE, width = "100%"))),
fluidRow(
column(7, offset = 1, highchartOutp... |
8da5721556ebe840c1d6cd74b423aa8c870a894f | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/steadyICA/R/kcdf_fun.R | 7a83db39e17d61045f10c06d205a0cc77e3b5cdc | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,872 | r | kcdf_fun.R | #-----------------------
# Benjamin Risk
# 25 February 2013
# Edits to David Matteson's PITdCovICA code.
#-----------------------
#---------------------------------------------------
# Benjamin Risk
# 12 March 2013
# modified stats::density.default to return the distribution and the density;
# note that only the Gau... |
f3f71e8f7c128e48dc6a125e984b47cb1cc49d43 | c2e28f45847f8f5170d7ed90d406d9d5c3594625 | /man/norm.samps.Rd | 00e5d5d4a8323a5568d4bb73b27d196d9220cd23 | [] | no_license | mdedge/stfspack | 102d4ef512f21073dc2593db2265630040214357 | 3e7027d677c9017a0e3abaed7d99ef2ac7cf5d5d | refs/heads/master | 2020-03-29T07:03:16.471914 | 2018-09-21T22:33:01 | 2018-09-21T22:33:01 | 149,651,412 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 879 | rd | norm.samps.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/R_functions.R
\name{norm.samps}
\alias{norm.samps}
\title{Generate a matrix of samples from a normal distribution.}
\usage{
norm.samps(mu = 0, sigma = 1, n = 25, nsamps = 10000)
}
\arguments{
\item{mu}{The expectation of the normal distributi... |
3a0a53c18cad4032d182a57b817865e78eb642a0 | feeae2f7e21a7ed662a5ad9b796631e06fb7f7d1 | /pensionFuns.R | e1247f45789799407edc9bdc583bddd834848e2a | [] | no_license | ReasonFoundation/R-sandbox | b26e5d1514fc4e25d5f7e27b71c11f2115867731 | 270ffc532244521d8210bbdd984ce82191834d41 | refs/heads/master | 2020-03-27T22:55:10.963479 | 2019-10-17T21:19:56 | 2019-10-17T21:19:56 | 147,272,110 | 1 | 0 | null | 2019-06-28T23:04:03 | 2018-09-04T01:37:58 | HTML | UTF-8 | R | false | false | 18,286 | r | pensionFuns.R | # This script contains functions used to load pension plan data either from Reason's database or
# from an excel file.
# Author: Andrew Abbott
# Date: 12/11/2018
# Color Scheme
# All images should use web safe colors — this gives us a range of orange and blue
# colors that fit with Reason’s branding, as well as reds a... |
5bbdd87db74337d13c3785c629f442ea7b8ada74 | 1fba8b717eb4b471d268723e448a2fae9e2c514d | /4_dihaploid_pools/analysis/MM_parent_snps.R | 91e1c2c131f5f973f83d24a70e103d3ccfa75ae3 | [] | no_license | kramundson/MM_manuscript | 5cd2b93043aba74f45269204682ed19b07bbfdf6 | fe5b212eaecb0144c61de4f6075fc2eebff3819f | refs/heads/master | 2023-06-17T05:04:06.022695 | 2021-07-09T22:51:57 | 2021-07-09T22:51:57 | 301,579,338 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 18,651 | r | MM_parent_snps.R | #' ---
#' title: "MM Parent SNPs"
#' author: Kirk Amundson
#' date: 2020_1007
#' output: html_notebook
#' ---
#'
#' Aim: Define parent-specific SNP loci and inducer/non-inducer specific alleles
#' at these loci for low-pass SNP analysis of MM dihaploid cohorts.
#'
#' Low quality sites were filtered out in the precedi... |
59c6354851b8ec7b021b422f2985fa56a4fd4e73 | 63370a83deb0209002ede6dd85e8738cfdc1fd6a | /man/source_file.Rd | 681aa8e3f887b6acaa302a0092de8b034880d9be | [] | no_license | maurolepore/fgeo.build | 4e68adcb5cad1710553bf3ef09666d4e7ac9f0cd | d1016c25c609ce136ce7961368b2f375cdacde8a | refs/heads/main | 2021-11-10T01:54:15.697149 | 2018-11-25T18:19:24 | 2018-11-25T18:19:24 | 159,061,036 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 587 | rd | source_file.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/update_fgeo_source.R
\name{source_file}
\alias{source_file}
\title{Update vector to schedule package installation in correct order.}
\usage{
source_file(file, dir = "../fgeo.install")
}
\arguments{
\item{file}{Path to a file in data-raw/.}
\... |
3c9a31fa253ce0109c33ec487a45d17f20114962 | c26126260131d5de42a198a991630037905d1362 | /man/get_proportions.Rd | 00ad98437e755e4adb616bd9bc803dbf6112a87f | [
"MIT"
] | permissive | AlkemaLab/fpemlocal | 88b3d777d3eaa1dd92a91621c89666c7462ca65d | 3aa538c3329967af391223a169cba7e4adb78ca0 | refs/heads/master | 2023-04-12T03:28:17.323380 | 2023-04-04T11:44:10 | 2023-04-04T11:44:10 | 268,617,794 | 0 | 1 | MIT | 2023-04-04T11:44:11 | 2020-06-01T19:50:53 | R | UTF-8 | R | false | true | 560 | rd | get_proportions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fpemreporting.R
\name{get_proportions}
\alias{get_proportions}
\title{Get proportions}
\usage{
get_proportions(posterior_samples, first_year, transformer)
}
\arguments{
\item{posterior_samples}{\emph{\sQuote{Array}} The samples array from \co... |
ec7d21786aa38405bed68ec01c9410c15d88a71c | 0e1204a899a929f6f2087a2727de8f368cbdc6df | /R/RSrc/unipath/unipath.R | 752dce44b030449b38df626399e400981bb90ac2 | [] | no_license | jvnguyen94/fi_sc_analysis | 602af4446c40536b8a5336dc975cf0f51a2971e1 | a1551918a1feb71fbb43fa8c590095a91f0fb747 | refs/heads/master | 2023-07-06T13:21:07.070171 | 2021-04-14T19:45:34 | 2021-04-14T19:45:34 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,390 | r | unipath.R | # ------------------------------------------
# Read args
# ------------------------------------------
args = commandArgs(trailingOnly=T)
if(length(args) < 2) {
message("Invalid number of passed arguments.")
}
umi.path <- args[1]
species <- args[2]
thresholds <- args[3]
n <- args[4]
k <- args[5]
plotting <- args[6]... |
0b3be71031f12b42dd1aaef8b65ccb7f1ae47a14 | 6dd8aafec0785a0fb0b1e16b6f70bbb83e3545a5 | /Machine Learning/Matrix Factorization.R | e9459a018c40ed01c9252224b7ee0d2e8b2f7858 | [] | no_license | jwwikstrom/DS-HarvardX | 22904bc8390a869504153b086b1e60d20f85a480 | e8dde57671864e8edd58ac2f113cd29ad6276ea4 | refs/heads/master | 2021-07-20T09:37:48.769002 | 2020-05-19T13:13:42 | 2020-05-19T13:13:42 | 165,712,485 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,911 | r | Matrix Factorization.R | set.seed(1987)
n <- 100
k <- 8
Sigma <- 64 * matrix(c(1, .75, .5, .75, 1, .5, .5, .5, 1), 3, 3)
m <- MASS::mvrnorm(n, rep(0, 3), Sigma)
m <- m[order(rowMeans(m), decreasing = TRUE),]
y <- m %x% matrix(rep(1, k), nrow = 1) + matrix(rnorm(matrix(n*k*3)), n, k*3)
colnames(y) <- c(paste(rep("Math",k), 1:k, sep="_"),
... |
79d37c011a8aecd3f058c2c2221256e1892816db | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/astroFns/examples/ut2lst.Rd.R | 727d6ec74f01c862ff387797303597045ebc700b | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 792 | r | ut2lst.Rd.R | library(astroFns)
### Name: ut2lst
### Title: Universal time to local sidereal time or hour angle
### Aliases: ut2lst ut2ha
### Keywords: chron
### ** Examples
# LST at UT1 midnight on the first of every month for Green Bank, WV, USA
midLST <- ut2lst(yr = 2012, mo = 1:12, dy = 1, hr = 0, mi = 0, se = 0,
... |
b9f933830357bc9eef8724f62dc131ef2582917c | ab5f335d1dfc44c2f16f4adc7e80a9220e9b4097 | /rscripts/data_sharing_network_dat.R | 6dec12a6dcd7a4afe98bd3c6cc842ab2a1703e41 | [] | no_license | CoWy-ASA/RiverWatch | 857bbe2229730fcdb29a6aa8193e67784f7a06f3 | 1147adb9965215843e60c44f7703e79a84740495 | refs/heads/master | 2021-01-22T23:16:26.662295 | 2015-08-04T20:09:48 | 2015-08-04T20:09:48 | 33,345,992 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,591 | r | data_sharing_network_dat.R | ### look at data from data sharing network
### mjp
library(ggplot2)
dat <- read.csv("data/dsn_pull/rf-1990-2015.csv", header = TRUE, as.is = TRUE)
sites <- read.csv("data//dsn_pull/rf_sites.csv", header = TRUE, as.is = TRUE )
dat$date <- as.Date(dat$Activity.Start.Date, format = "%m/%d/%Y")
dat$Result.Value <- as.... |
ab22b4d5a07203b68867afb4ea96638573a67191 | 104b494275bfbcdc9aa690846cb5136709765a29 | /treeStats.R | 857cfe214ed7f76480125cc48e781ebeeff43728 | [] | no_license | sellisd/IES | d3634f487e27aec90ebe7107503ce17355a1b118 | 04b6f1dc7a0be8c0e48899f4acf3ce7a352bd91e | refs/heads/master | 2021-01-17T04:01:50.070493 | 2018-06-01T21:17:23 | 2018-06-01T21:17:23 | 24,942,238 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,212 | r | treeStats.R | # calculate statistics on trees, the total branch length, number of genes and whether they have a character matrix
library(ape)
treePath <- "~/data/IES_data/msas/phyldog/results/"
load("~/data/IES_data/rdb/charMats")
clusters <- dir(path = treePath, pattern = "*.ReconciledTree$")
clusters <- gsub(pattern = ".Reconciled... |
bb6167b9aae565d887a1c13db3f2ed565a27a8f4 | 802fc356f77e6e0f7ade3c14b00218821b253101 | /plot4.R | 4b7d38a559289f2472d67d3542ad8aabb7cb8e01 | [] | no_license | mbcmn/ExData_Plotting1 | 4bfd79a27a2f94757dbee46bf2331d7deafde766 | 872e8ef7134cb194b4a2d644924406c486de34d2 | refs/heads/master | 2020-08-06T12:26:21.165639 | 2019-12-30T17:34:45 | 2019-12-30T17:34:45 | 212,974,888 | 0 | 0 | null | 2019-10-05T09:33:23 | 2019-10-05T09:33:22 | null | UTF-8 | R | false | false | 1,542 | r | plot4.R | # Read txt file into R
powercons <- read.csv("household_power_consumption.txt", header = TRUE, sep =";", na.strings = "?")
# Convert date and time columns into date and time format
powercons$datetime <- strptime(paste(powercons$Date, powercons$Time), format = "%d/%m/%Y %H:%M:%S")
# Subset for two first days of Februa... |
9afed3145b6e47eed12ce4671153d6fd46820430 | dd953a24d6aba1c5d5a6e81c04fc3c91cc9b5ae4 | /R/Create.actor.youtube.R | 4a3421509f4779f8a4c4031c016e4a9acb1a07d2 | [] | no_license | cran/vosonSML | e63e665d01fc0bba576beebc3f13d73676b38eba | c8d486b70237e725ca232f06e97c07ea4eefe2c8 | refs/heads/master | 2022-09-07T13:04:54.440490 | 2022-08-16T12:00:01 | 2022-08-16T12:00:01 | 145,896,556 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,614 | r | Create.actor.youtube.R | #' @title Create YouTube actor network
#'
#' @description Creates a YouTube actor network from comment threads on YouTube videos. Users who have made comments to
#' a video (top-level comments) and users who have replied to those comments are actor nodes. The comments are
#' represented as directed edges betwee... |
18fc8ab927461ade5461f3f9a979a209978e439f | 44cf65e7ab4c487535d8ba91086b66b0b9523af6 | /data/Newspapers/2002.02.21.editorial.79636.0823.r | 23a7f81c0a1c0783a308e3e304a5d8fdb8f0516c | [] | no_license | narcis96/decrypting-alpha | f14a746ca47088ec3182d610bfb68d0d4d3b504e | 5c665107017922d0f74106c13d097bfca0516e66 | refs/heads/master | 2021-08-22T07:27:31.764027 | 2017-11-29T12:00:20 | 2017-11-29T12:00:20 | 111,142,761 | 0 | 1 | null | null | null | null | MacCentralEurope | R | false | false | 3,579 | r | 2002.02.21.editorial.79636.0823.r | institutiile n - au nici blana , nici coada , n - au nici bataturi in talpa si nu fac nici diaree .
sint doar niste cladiri mai fatoase si niste conventii intre noi , biete fiinte trecatoare .
si atunci , vrind - nevrind , iti vine sa te intrebi , oare de ce a sarit Parchetul General ( de pe linga Curtea Suprema de J... |
af0c084a45b70c41ad474592653b8f1578c27563 | bdb80bd3620d159911090501977e63e2c16fc7a2 | /plot2.R | 74e7005af63b2cba83d019f442a6052c76f00c79 | [] | no_license | EMCE777/ExData_Plotting1 | e1ff9c82dce7e49036a65d0371fc5a94a1c7a93b | 9b53aceb7313ea35ecc11bd85b7429b99efd9458 | refs/heads/master | 2020-04-01T07:54:46.900548 | 2018-10-14T23:24:55 | 2018-10-14T23:24:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,053 | r | plot2.R | # Examine how household energy usage varies over a 2-day period in February, 2007.
# To obtein data from source
houseData <- read.table(file="./Project1/household_power_consumption.txt",
header = T, sep=";", na.strings = "?")
# Transform data type from Date variable
houseData$Date <- a... |
f45e16d533bef17a171d54de885536656473fa66 | 98f11f4107c2fd916e6285bb685dc508e6a47133 | /ui.R | 5dad9a8785a4fa5eae08eec167e05ea21982dc9c | [
"MIT"
] | permissive | peppy/2019-ncov-japan | b121682f8e9021506a1edd4cece0b2fbcd0ca403 | aa56daf6eb4016ba76818592fa982988ebf0a3eb | refs/heads/master | 2022-07-27T14:37:14.328844 | 2020-05-14T00:54:46 | 2020-05-14T00:54:46 | 263,784,571 | 2 | 0 | MIT | 2020-05-14T01:36:07 | 2020-05-14T01:29:13 | null | UTF-8 | R | false | false | 6,872 | r | ui.R | source(
file = "global.R",
local = T,
encoding = "UTF-8"
)
shinyUI(
dashboardPagePlus(
skin = "red",
title = i18n$t("新 型 コ ロ ナ ウ イ ル ス 感 染 速 報"),
header = dashboardHeaderPlus(
title = paste0("🦠 ", i18n$t("新 型 コ ロ ナ ウ イ ル ス 感 染 速 報")),
titleWidth = 600,
enable_rightsidebar = F
... |
eee15ef8c435a81c72edf776c440dcf5bd4eb1de | d859174ad3cb31ab87088437cd1f0411a9d7449b | /autonomics.find/man/infer_contrast_names.Rd | 927ad661ff2f2a0f58dd56ba72af4239e70f2fbe | [] | no_license | bhagwataditya/autonomics0 | 97c73d0a809aea5b4c9ef2bf3f886614eceb7a3c | c7ca7b69161e5181409c6b1ebcbeede4afde9974 | refs/heads/master | 2023-02-24T21:33:02.717621 | 2021-01-29T16:30:54 | 2021-01-29T16:30:54 | 133,491,102 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 463 | rd | infer_contrast_names.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/infer_contrasts.R
\name{infer_contrast_names}
\alias{infer_contrast_names}
\title{Infer contrast names}
\usage{
infer_contrast_names(object)
}
\arguments{
\item{object}{eset}
}
\value{
character vector
}
\description{
Infer contrast names
}
\... |
cf7b86b998d4d1eba74bdba51164796e17e266f1 | 2b2eb91afad071c939bbb1c251e5ee87dca7e709 | /inst/unitTests/nodeAndEdgeData_test.R | 0aea9cbd35bc461e77d1e5703946414c429ded33 | [] | no_license | vgpprasad91/graph | 7a255c5652bf43722e16020aa4e82f01c43533fa | f8cad8e67dffc73106c918ace0904f109255ea1f | refs/heads/master | 2021-01-24T09:01:12.583974 | 2017-06-05T12:19:34 | 2017-06-05T12:19:34 | 93,400,581 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,721 | r | nodeAndEdgeData_test.R | #
# Test setup
#
simpleInciMat <- function() {
## Here's a simple graph for testing
## a b
## |\ /|
## | \___c___/ |
## | | |
## \ | /
## \____d____/
##
##
mat <- matrix(c(0, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0),
... |
1835f6c9f0c8ed607a1dd0b492cccd81919f1885 | f5bbcd5d0436d05c52ec56378f3f77152f739535 | /R/EMSfin.r | cdfb95d7f1f743a63087eee8d3fc953ec870d067 | [] | no_license | cran/varcompci | 931e354dd5f86588398fda731311979744f6b050 | e5d9a6d909762e9b9ecef462b2ec9c660a8ff58d | refs/heads/master | 2020-04-14T23:46:07.129750 | 2011-02-14T00:00:00 | 2011-02-14T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,634 | r | EMSfin.r |
setClass("EMSc",representation(
EMSpretty="matrix",
result_EMS= "matrix",
namesdesc="matrix",
result_EMSlF="matrix",
final_EMS="matrix"
))
setMethod(
f="[",
signature=c("EMSc","character","missing","... |
b5cbd8f3951009aded55048635d37b85354819a1 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/MEMSS/examples/Oats.Rd.R | fc015a8988179f72ef561563a03db07e542ac1be | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 158 | r | Oats.Rd.R | library(MEMSS)
### Name: Oats
### Title: Split-plot Experiment on Varieties of Oats
### Aliases: Oats
### Keywords: datasets
### ** Examples
str(Oats)
|
caaaee4e7f71ea58c02a0dd46c794622d6bcf695 | 092dac9550c38286881f11957d6afdee4232253b | /man/simumix.Rd | d4e266048a3829a1dd3c411a1ae53d0222386955 | [] | no_license | hindantation/forensim | b60016864c7cfa058a0958fd02fe0c5588b8393d | 0eca44897e6ea6b5bec99217c18362da8b266262 | refs/heads/master | 2022-10-11T20:04:39.176056 | 2022-10-04T07:39:12 | 2022-10-04T07:39:12 | 220,780,908 | 0 | 1 | null | 2022-10-04T07:39:13 | 2019-11-10T11:35:19 | R | UTF-8 | R | false | false | 1,757 | rd | simumix.Rd | \encoding{UTF-8}
\name{simumix}
\alias{simumix-class}
\alias{names,simumix-method}
\alias{print,simumix-method}
\alias{show,simumix-method}
\title{forensim class for DNA mixtures}
\description{The S4 \code{simumix} class is used to store DNA mixtures of individual genotypes
along with informations about the individua... |
46f3f21869e786ee78adb594315136e844d1adbd | bf52e409724bea2c2098ed611f879ab5e767f562 | /plot2.R | 2e73249fe142e4f441ca0cd8c8f8a8ad0edf95c0 | [] | no_license | hayesn22/ExData_Plotting1 | 7fc7a4f5e5428f64907921fb0325b8538ff08152 | 2b7e9d87c6f9b24dbf8084ee2b9b8d93a596a956 | refs/heads/master | 2020-06-25T14:45:02.836233 | 2019-07-29T00:15:19 | 2019-07-29T00:15:19 | 199,341,019 | 0 | 0 | null | 2019-07-28T21:57:13 | 2019-07-28T21:57:13 | null | UTF-8 | R | false | false | 1,005 | r | plot2.R | householdpower <- read.table("household_power_consumption.txt",skip=1,sep=";", na.strings = "?", colClasses = c('character', 'character', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric', 'numeric'))
names(householdpower) <- c("Date","Time","Global_active_power","Global_reactive_power","Voltage","Global... |
90d07b9fc6bd09a5d55cf7227d9f237c389eb242 | 67777576fda46de12cc276f08470d0001666b521 | /R/sample_intercept.R | 08f8314047d9eb68eed136882c4a07075168a7b7 | [] | no_license | yjustc2019/WeibullHM | e883690d702e6cb3e13f79ee565b1489883bb2c0 | 357b12921507b11deebe65264a04923deedf5e3c | refs/heads/master | 2021-12-22T13:33:08.547347 | 2017-10-15T01:05:06 | 2017-10-15T01:05:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,149 | r | sample_intercept.R | #
# sample_intercept.R
#
# Created by Zhifei Yan
# Last update 2017-4-22
#
#' Sample intercept effects
#'
#' Produce a Gibbs sample of intercept effects of all states
#'
#' @param y a matrix of current update of Weibull log scale parameters
#' @param alpha a matrix of current update of subject random effects
#' @par... |
1d29204bbdb0c90fab17ca129b9f6705287e5fd4 | 7e0e64d363b4dde2bce1840bf5dd0f2199f0b88e | /send_mail.R | 568faad8f7f68cd347ecfadcc061b01db40e970f | [] | no_license | krzyslom/auto_mail | 2e6a5c6433ee8d25359df087803048316de5e6d9 | d5803f0b1fdfd88a6cc6ac578e4049e7844c8778 | refs/heads/master | 2021-01-22T07:57:25.271867 | 2017-05-30T14:17:44 | 2017-05-30T14:17:44 | 92,586,919 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,530 | r | send_mail.R | # devtools::install_github("rpremraj/mailR") # wymaga instalacji Java
library(dplyr)
library(knitr)
library(mailR)
library(rmarkdown)
# library(readr)
# library(tidyr)
# Parametry poczty
from <- "user@domena.dom"
subject <- "Temat"
smtp <- list(host.name = "Adres servera SMTP",
port = 465,
u... |
a2d0b25dfe4029a266b556af9baa55643e505b53 | c4b88246c20acd36790f988b3fc1aa59170a9cd1 | /48674698/spawn.R | 0b22a6a6894a141735b440ddfe37216315c51257 | [] | no_license | dewittpe/so | 48d6ef6b75a851c831fe78a1829f5acd264caed9 | f11721642a1ad765e3bc382659dd2b7d0de21160 | refs/heads/master | 2021-06-07T11:47:39.334548 | 2020-03-12T15:22:29 | 2020-03-12T15:22:29 | 132,039,477 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 376 | r | spawn.R | rp <- processx::run("R", "--vanilla")
rp <- processx::process$new("R", "--vanilla")
rp$is_alive()
servr::httd(daemon = TRUE, browser = FALSE, port = 4321)
R.utils::withTimeout(
{
s <- rvest::html_session("http://127.0.0.1:4321")
},
t... |
c75993d4d21ac7b93de22e2c29d4a0f228eea491 | ec9ad043b7eb8c868e972fc21011b89e32a0433e | /man/make_filename.Rd | 3a90ff945be773c28f9a98f57c7ec06ddef7dfad | [] | no_license | olb1605/FARS_Package_Coursera | ef65a1063435af897926a4780b2518ef1409481b | f16459798041f02cef306f24d67bf77763a29310 | refs/heads/master | 2020-03-14T03:59:55.807754 | 2018-04-28T21:13:33 | 2018-04-28T21:13:33 | 131,431,675 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 805 | rd | make_filename.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fars_functions.R
\name{make_filename}
\alias{make_filename}
\title{Function "make_filename" - creates a file name in a specified format}
\usage{
make_filename(year)
}
\arguments{
\item{year}{A string or an integer}
}
\value{
This function ret... |
d0bc5d423534a62eb7afe4be98807f005c50be14 | c234c1b9ee9fd67821c552a86dbe1ae65c3ab77d | /app.R | af0f433d45db0ac1c867d73d61b54a80c7d9d37d | [
"MIT"
] | permissive | mick14731/Econ-dashboard | 4cbf535a152dbeeccbf2f12688afe51f24204933 | fbd258cb46b133d195bb0b21aab92dd6d76d0fcc | refs/heads/master | 2020-04-20T12:52:54.560548 | 2019-05-21T23:55:04 | 2019-05-21T23:55:04 | 168,854,235 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,179 | r | app.R | library(shiny)
source("functions.R")
source("cpi maker.R")
source("Lab_force.R")
ui <- shinyUI(fluidPage(
tabsetPanel(
tabPanel("CPI without",
sidebarLayout(
sidebarPanel(
width = 3,
selectizeInput("choice_Ex","Sectors to exclude:",
choices = colnames... |
4f39306430b8ea1cf0b105d96a634e6f44e31cfe | 9b6f4de24c64ddc70e4ec59bd2f030dd58436a94 | /TS/ts3.R | 470c32ecf1f64486db8065a7f0675d4235a4be84 | [] | no_license | GopalKrishna-P/analytics | e1c5207fc1f8132db371886a83f80b7272786ee0 | 232a32b7317ede1897794745acd6f2b7b0ac393d | refs/heads/master | 2023-04-26T18:24:14.978599 | 2021-05-29T09:50:16 | 2021-05-29T09:50:16 | 129,134,381 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,769 | r | ts3.R | # Time Series
#dataset
AirPassengers
class(AirPassengers)
JohnsonJohnson
nhtemp
Nile
sunspots
ds = list(AirPassengers,JohnsonJohnson,nhtemp,Nile,sunspots)
sapply(ds, class)
# Sales TS Data
sales = c(18, 33, 41, 7, 34, 35, 24, 25, 24, 21, 25, 20,
22, 31, 40, 29, 25, 21, 22, 54, 31, 25, 26, 35)
tsales = ts(... |
a9135555cf42d844d1466741aeae0903fc2b7505 | a06c3e5453bc4ef2f882b6e71c803a0e9498afe7 | /class5/041818.R | 863ea03ffbd6bb91dadd4fc0ffd2ba8e0c610445 | [] | no_license | clocheltree/bggn213 | df81d6f60913622d1342d49a7ddc158fe3b0e515 | 7a387939f9b1d2d2c93cab6ab6c2192fb97669b1 | refs/heads/master | 2020-03-15T14:24:11.646519 | 2018-06-06T21:30:25 | 2018-06-06T21:30:25 | 132,189,301 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 839 | r | 041818.R | # Bioinformatics Class 5
# Plots
x <- rnorm(1000,0)
summary(x)
# let's see this data a graph
boxplot(x)
hist(x)
# Section 1 from lab sheet
baby <- read.table("bggn213_05_rstats/weight_chart.txt", header = T)
plot(baby, type = "b", pch = 19, cex = 0.5, lwd = 0.5, ylim=c(2,10), xlab="Age (months)", ylab="Weight (kg)... |
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