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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b5f1fe6858eb23b533680212312620241fdcb75d | a03da6a1edc7b1a1cf4b0829f5ece771f584df95 | /man/theme.rpres.Rd | 127c87360df31fa590bad3c09b3ad2fd2d4ac836 | [] | no_license | homerhanumat/tigerstats | 4fbcc3609f46f6046a033d17165f7838dbd77e1a | 17067f7e5ec6b6cf712b628a4dbf5131c691ae22 | refs/heads/master | 2021-07-06T06:24:07.716196 | 2020-09-22T15:24:01 | 2020-09-22T15:24:01 | 15,921,287 | 14 | 7 | null | null | null | null | UTF-8 | R | false | true | 728 | rd | theme.rpres.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/theme.R
\name{theme.rpres}
\alias{theme.rpres}
\title{Lattice Theme or R Presentations}
\usage{
theme.rpres()
}
\value{
Returns a list to be supplied as the \code{theme} to the \code{lattice} function
\code{\link{trellis.par.set}()}.
}
\descr... |
693e9186ab8c216f8a7f7d50ee28330630716fd5 | 1b67115132aee53bad61fa6fb2198685090e6754 | /server.R | d9a18c8ffd48014727ea3ec979b918f1a2c84fed | [] | no_license | michelbouchou/shinyApp-PML | 4cc3e6026473cdd16cb0572be4a324ce0554d641 | 460d844a30513dbdbfd7e27a1ab4d0b68af34dd4 | refs/heads/master | 2021-01-01T06:10:10.430583 | 2017-07-16T11:18:26 | 2017-07-16T11:18:26 | 97,376,955 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 564 | r | server.R |
library(shiny)
library(scales)
# Define server logic required to draw a histogram
shinyServer(function(input, output) {
output$plot <- renderPlot({
set.seed(18)
nbPoints <- input$numeric
opacity <- input$opacity
dataX <- runif(nbPoints, min = -100, max = 100)
d... |
a89fa72d18313cf0b31e4262e1725c2f28c84436 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/stepPenal/examples/stepaic.Rd.R | 9b3eb1eaa38abb464ae3bf6e727a255c88d5b928 | [] | 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 | 377 | r | stepaic.Rd.R | library(stepPenal)
### Name: stepaic
### Title: Stepwise forward variable selection based on the AIC criterion
### Aliases: stepaic
### ** Examples
## Not run:
##D set.seed(14)
##D beta <- c(3, 2, -1.6, -4)
##D noise <- 5
##D simData <- SimData(N=100, beta=beta, noise=noise, corr=FALSE)
##D
##D stepaicfit <-... |
50a22f32bae437457a76d178043b10f1f93c1809 | 1630e1bf37845810280c6ddb89cb84315d8063e4 | /epis_analysis/epis_analysis.R | bb706b0efa27484c83975743236b783e74a56487 | [] | no_license | ivanovaos/PetriNetExhaustiveSimulator | 1b6cd067f4e4fc327ac4aac77abc08e465bc4f0b | d7c2108432aa8a38d9283cc3e8007584e40b2ca3 | refs/heads/master | 2020-04-07T23:24:36.736304 | 2018-12-01T16:01:16 | 2018-12-01T16:01:16 | 158,811,398 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,300 | r | epis_analysis.R | # this script takes care of output from exhasutive modeling of models
# Saman Amini
# Collect arguments
args <- commandArgs(TRUE)
# Default setting when no argument passed
if (length(args) < 1) {
args <- c("--help")
}
# Help section
if ("--help" %in% args) {
cat("
modeling_downstream.R
script... |
b9dde102b23efb97e5794b5ad6aa7cb40ef37b77 | 7f72ac13d08fa64bfd8ac00f44784fef6060fec3 | /RGtk2/man/gtkViewportGetShadowType.Rd | 0c5b4030f5bd2cddaa2cd085b54c4b56e6b2612d | [] | no_license | lawremi/RGtk2 | d2412ccedf2d2bc12888618b42486f7e9cceee43 | eb315232f75c3bed73bae9584510018293ba6b83 | refs/heads/master | 2023-03-05T01:13:14.484107 | 2023-02-25T15:19:06 | 2023-02-25T15:20:41 | 2,554,865 | 14 | 9 | null | 2023-02-06T21:28:56 | 2011-10-11T11:50:22 | R | UTF-8 | R | false | false | 439 | rd | gtkViewportGetShadowType.Rd | \alias{gtkViewportGetShadowType}
\name{gtkViewportGetShadowType}
\title{gtkViewportGetShadowType}
\description{Gets the shadow type of the \code{\link{GtkViewport}}. See
\code{\link{gtkViewportSetShadowType}}.}
\usage{gtkViewportGetShadowType(object)}
\arguments{\item{\verb{object}}{a \code{\link{GtkViewport}}}}
\value... |
eaf8ce6e646baf7162bbfac069b1aca542fa9bb3 | d6744296dbd0427a05119f56c378cdd39d71aad2 | /man/DMRViterbi.Rd | c5ff998af82631a72475fa4b355f02c3e2783f4a | [] | no_license | cran/DMRMark | a7e50e0351f40bb026a47fc650bd9ee86a15a15f | fbf5ffa2c4c628320964ddd4c1ff628c7dbdf9ec | refs/heads/master | 2020-08-05T07:18:31.763883 | 2017-04-21T16:58:43 | 2017-04-21T16:58:43 | 67,360,999 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,787 | rd | DMRViterbi.Rd | \name{DMRViterbi}
\alias{DMRViterbi}
\title{
Viterbi algorithm to estimate posterior probabilities of DMRs.
}
\description{
This function takes M-values and estimated parameters
from 'DMRMark', then uses Viterbi algorithm for
estimating states' posterior probabilities for each locus.
}
\usage{
DMRVit... |
ca83fad1a0803ecffc9e4470043f9946cb9ace50 | 3d0c35ec6ae3761a182045135de01d1e44a40a38 | /Autoforecasting0227.R | 8946a9800e2d8a3288275f329a6840ad97612eb8 | [] | no_license | wenrurumon/stnn | 75f09265b63e77796a55fa1d59cc178203b89b1a | f86c57f05a51bf1990df4055c56ac2a98910eed1 | refs/heads/master | 2020-12-28T04:25:25.615430 | 2020-07-19T07:19:32 | 2020-07-19T07:19:32 | 238,181,205 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 16,169 | r | Autoforecasting0227.R |
############################
# Module
############################
rm(list=ls())
library(plyr)
library(openxlsx)
library(data.table)
library(dplyr)
library(keras)
library(MASS)
#Get Model File
get_model_file <- function(x,i,p,gety=TRUE){
if(gety){y <- t(x[p+i,,drop=F])}
x <- t(x[1:p+i-1,,drop=F])
if(gety){y[y<... |
cfd71441616f5e2a75d58b3b63c778dd6812d13b | 4d216630e99eda5974b2655baf8928ca7da754bd | /man/apply_filter_specfile.Rd | 1a3ba5b8db3d66f3ea68dc362e18dbde4977f1da | [] | no_license | ashiklom/edr-da | 467861ec61cd8953eb272e2844414a522db7268f | b092600954b73fa064300c6e7b21d0413d115b94 | refs/heads/master | 2021-07-12T18:59:20.190169 | 2021-04-12T14:00:17 | 2021-04-12T14:00:17 | 71,824,349 | 2 | 5 | null | 2018-02-01T13:29:03 | 2016-10-24T19:26:27 | R | UTF-8 | R | false | true | 429 | rd | apply_filter_specfile.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/specfile.R
\name{apply_filter_specfile}
\alias{apply_filter_specfile}
\title{Apply single filter to spectra HDF5 data file}
\usage{
apply_filter_specfile(aviris_h5, quosure)
}
\arguments{
\item{aviris_h5}{HDF5 file object}
\item{quosure}{An ... |
7eaaa767e00d9c1b3f5e7a6bded18edbda24f7ca | b7cd62ff3a55a1d1c35ab39c86045ec4950fc0b3 | /plot6.R | dc27499e2dd751919ce226a7d2739ec9c70c580a | [] | no_license | bbamini/Exploratory_Data | 7f4f1fe7e84aab21ef5577856132c907d7884a1f | c96b473f9deb0bc42c62ac4573546730da9bb72b | refs/heads/master | 2020-04-22T10:56:29.651454 | 2016-09-12T05:51:23 | 2016-09-12T05:51:23 | 67,979,516 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,081 | r | plot6.R | ## Read PM2.5 Emissions Data
NEI <- readRDS("summarySCC_PM25.rds")
#SCC <- readRDS("Source_Classification_Code.rds")
library(reshape2)
#Subset Baltimore City and Los Angeles County PM2.5 data for motor vehicles
balt_LA_road <- subset(NEI, (fips == "24510" | fips == "06037")
& type ==... |
a43c45a11f343cc9781819c448778a4b7869302e | f2316e98c2e423836e7f291aeb666827fc35df4e | /Plot2/plot2.R | cac0abfd8f261c4ba256e21f44e872f0a24eb128 | [] | no_license | yshen92/ExData_Plotting1 | 311a1e23879d9277a2d5a14165389b2a7a5d6f82 | ba6d19115d3d1e8de62793d10c55970ecda86526 | refs/heads/master | 2020-07-07T08:02:20.689521 | 2019-08-21T07:47:20 | 2019-08-21T07:47:20 | 203,298,202 | 0 | 0 | null | 2019-08-20T04:14:17 | 2019-08-20T04:14:16 | null | UTF-8 | R | false | false | 570 | r | plot2.R | #Read_Data
household <- read.table('household_power_consumption.txt', header=TRUE, sep=';', na.strings = "?")
household[['date_time']] <- strptime(with(household, paste(Date, Time, sep=" ")), "%d/%m/%Y %H:%M:%S")
household[['Date']] <- strptime(household[['Date']], format="%d/%m/%Y")
#01-02 July Data
july <- subset(ho... |
6f334c0b0d4a1fd40d492b04cedfcc993c6d3c1f | 0aaecd6991a7f16759a1f8d2b3be6093f8a183af | /inst/snippet/coag-mct.R | 773d109a2fe87a3dd98b4c8aeccacabf80bc17f3 | [] | no_license | cran/fastR | 3f0e3959dad4e5d361c341eb6bea670eab6bfdcc | 572a5dc31e5aa85af4126662f95268329179c87b | refs/heads/master | 2021-01-21T04:55:14.927487 | 2017-07-27T19:52:06 | 2017-07-27T19:52:06 | 17,695,981 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 196 | r | coag-mct.R | coag <- coagulation
coag$x1 <- coag$diet=='B'
coag$x2 <- coag$diet=='C'
coag$x3 <- coag$diet=='D'
coag.model <- lm(coag~x1+x2+x3,coag)
coag.model1 <- lm(coag~1,coag)
anova(coag.model1,coag.model)
|
25cdbdae77a5c815a55733ef07309dc271959fd9 | 17f1b5b761a43ec178602a43f24ac72c2d5d01a9 | /lobstr/inst/testfiles/v_size/libFuzzer_v_size/v_size_valgrind_files/1609881833-test.R | 0e27a9e3ade0584b0b31899d4cfd9b32b11fbcdb | [] | no_license | akhikolla/newtestfiles-2 | 3e1882e7eea3091f45003c3abb3e55bc9c2f8f56 | e539420696b7fdc05ce9bad66b5c7564c5b4dab2 | refs/heads/master | 2023-03-30T14:44:30.614977 | 2021-04-11T23:21:23 | 2021-04-11T23:21:23 | 356,957,097 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 75 | r | 1609881833-test.R | testlist <- list(size = NULL, n = 5.45361239830194e-311, element_size = 0L) |
202baccc00992dcbcefd7a05d99ebdfd2c7f7add | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/RevEcoR/examples/show-methods.Rd.R | 157794411f0698dfcdf687ad665036fce168bd60 | [] | 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 | 206 | r | show-methods.Rd.R | library(RevEcoR)
### Name: show,seedset-method
### Title: The show generic function
### Aliases: show show,seedset-method show-methods
### ** Examples
## Not run:
##D show(seed.set)
## End(Not run)
|
ca08d11e7274a7c7f8cfa21a53abcf1ce1865749 | 4ef1abc89cd63293ad7da8c799492aff5ae5a666 | /inst/tinytest/testSummary.R | 1c881fb31d5f8d28e8bade9387ab469d2d117f00 | [
"MIT"
] | permissive | bengalengel/OmicNavigator | 07ae25f23b8162e3fdee9b7b6cad7f84b4190e32 | 2edaf7204afe9d37467be474ef39ed40ca2d393f | refs/heads/main | 2023-04-17T22:53:51.470685 | 2021-04-26T14:51:43 | 2021-04-26T14:51:43 | 348,800,839 | 0 | 0 | NOASSERTION | 2021-03-17T17:46:59 | 2021-03-17T17:46:58 | null | UTF-8 | R | false | false | 768 | r | testSummary.R | # Test summary.onStudy()
# Setup ------------------------------------------------------------------------
source("tinytestSettings.R")
using(ttdo)
library(OmicNavigator)
emptyStudy <- createStudy(name = "empty", description = "An empty study")
testStudy <- OmicNavigator:::testStudy(name = "test", description = "A t... |
62f7e7587ccd5a72409a6dfb78a1082d9df2da16 | fa433bb45c39743dffea926544dc402d7801b7ee | /code 1 cox analysis.R | 0c922eaf292f1d3f6792a267bbae917e019f9d99 | [] | no_license | heleliangww/Alternative-splicing-for-ACC | 68d867a9cadc208542dca4eaafd413095ae4f016 | 0230ef81a0fd46db2aac039b65936639353d98d6 | refs/heads/main | 2023-01-23T16:00:43.544616 | 2020-12-07T08:25:35 | 2020-12-07T08:25:35 | 319,247,234 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,118 | r | code 1 cox analysis.R | rm(list = ls())
library(survival)
clinical<-read.table("./clinical_finial.txt",header=TRUE,sep="\t")
rownames(clinical)<-clinical[,1]
clinical<-clinical[,-1]
AS<-read.table("./AS.txt",header=TRUE,sep="\t")
rownames(AS)<-AS[,2]
AS<-AS[,-2]
AS<-as.matrix(AS)
intersection<-intersect(rownames(clinical),colnames(AS))
AS_a... |
969edab9a62d03ac162b5b148621b94ec6805610 | a3f7826863b6b81bc99ccf9c414f8bcf09a335e7 | /man/myKable.Rd | 74c12c098b065b9c559ce1ff4f92874df5b1e139 | [] | no_license | cran/rmdHelpers | 24c9516a15a8d6de20bb92df4df1ceba27786ce1 | b091a8e1ec70f651305074b03ccb38dd0008c599 | refs/heads/master | 2021-01-18T18:09:53.043265 | 2016-07-11T23:09:59 | 2016-07-11T23:09:59 | 55,989,977 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,420 | rd | myKable.Rd | \name{myKable}
\alias{myKable}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Wrapper for kable
}
\description{
A small wrapper for the knitr kable function
to allow automated bolding of row and/or column names.
Additional functionality may be added/
}
\usage{
myKable(x, row.names = NA, boldRowN... |
d9c1631452b840414939939b28557fcd91d5c503 | de84560d6597a1980ff2dc2e18bd1e7ad2b67af1 | /plot3.R | 705e6f83b953357675afbd187347bb9ddbfeaa28 | [] | no_license | jwleemd/ExData_Plotting1 | c7227b0708b41f74a6f9c31eb45f6366cfcd8a02 | 41ab46d17ff00dfa0b678110693345197d5eb67b | refs/heads/master | 2021-01-12T21:05:19.847388 | 2015-11-08T13:18:47 | 2015-11-08T13:18:47 | 45,780,666 | 0 | 0 | null | 2015-11-08T13:02:54 | 2015-11-08T13:02:54 | null | UTF-8 | R | false | false | 1,170 | r | plot3.R | # Downloading and unzipping the dataset
url <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(url, destfile="household_power_consumption.zip")
unzip("household_power_consumption.zip")
data <- read.table("household_power_consumption.txt", header=T, sep=";", strings... |
5a94fd394447af691ab3a8919af2926635bc678e | c93cf355ec2868c1f5bd04a4df7e4cd572987527 | /district_pay_income.parse.R | c5cf5bff8c03c7ebafba83877819ea7179626ab2 | [] | no_license | helen-sinica/esbk | 614d0fb042b054880792f6c43f02129771cfdf3d | a4283b5c7339ade076e34637253a5b074746e241 | refs/heads/master | 2020-03-31T01:45:06.234034 | 2015-05-27T07:39:52 | 2015-05-27T07:39:52 | 35,873,878 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,149 | r | district_pay_income.parse.R | library(XML)
library(stringr)
# set working directory according to the OS
is.windows <- function() .Platform$OS.type=="windows"
ifelse(is.windows(), setwd("D:/E-sun"), setwd('/home/helen/esbk'))
#xxx getwd()
# read 22 htmls (loop by names)
keywd <- LETTERS[-c(12, 18, 19, 25)]
count <- 1
for(c in keywd){
... |
1a5c8b87861629469f92d1959eea465e4bfe3d4c | e8cbfa032b4e85396d31690a8434d28c549184bc | /code/coronaphase.R | 0654d9b4173906666bd18391edb2a0369f7eee32 | [] | no_license | laasousa/Speed_and_strength | 3ecd75e11c55731fb306b9b500da9d3b1b35ca06 | cc4df20cc36ad9c003035106da584477c10decca | refs/heads/main | 2023-03-19T21:27:46.522967 | 2021-03-10T04:36:15 | 2021-03-10T04:36:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,745 | r | coronaphase.R | library(ggplot2); theme_set(theme_bw())
library(dplyr)
library(gridExtra)
## Next step: generalize. Calculate distributions by: convolving, cumulating and then differencing.
r <- log(2)/3
## Assume three equal lag kernels; we move from exposed to pre-symptomatic to symptomatic, p is relative contagiousness of pre-sy... |
c1c2d0965675d7f4ec351665bf45cbcf079aa0d2 | 0877d83cdf78f6e3bb122c7d2c031791684506d3 | /man/score_hbi_mp_nav_water.Rd | a47a8796521db73f610f78d2a741add0af2413bf | [] | no_license | BWAM/BAP | fec1dbe4475f3869f8007894e9ad9a5581cb1277 | 9dd041516b2f4c8a2269516c57d7ade41746d7e9 | refs/heads/master | 2023-04-30T00:25:15.586434 | 2023-04-26T16:17:49 | 2023-04-26T16:17:49 | 180,187,817 | 0 | 1 | null | 2023-04-17T16:54:43 | 2019-04-08T16:18:52 | R | UTF-8 | R | false | true | 551 | rd | score_hbi_mp_nav_water.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/score_mp_nav_water_metrics.R
\name{score_hbi_mp_nav_water}
\alias{score_hbi_mp_nav_water}
\title{Score HBI (Multiple-Plate Navigable Waters)}
\usage{
score_hbi_mp_nav_water(metrics.df)
}
\arguments{
\item{metrics.df}{= a data frame of calcula... |
f7976c267213b812946b3ca2dd671b968ab79d9d | 0acaeb10c17ca4327b2aed3c10707793e1e707b2 | /inst/tests/test-session.R | ee5d5831fc10a94b0e44d69e94e3434aff3c7544 | [] | no_license | rtirrell/databasr | 18cd85cf614a5ff981d73921a48fdb1201e10710 | b772e84b5711ddcd65dc8a23d8bd99247977a76e | refs/heads/master | 2020-06-04T04:04:06.177626 | 2011-03-20T22:27:56 | 2011-03-20T22:27:56 | 1,368,624 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 203 | r | test-session.R | context("Testing Session")
expect_is(session, "Session")
connection <- session$request("test")
expect_true("test" %in% session$users)
session$release(connection)
expect_false("test" %in% session$users) |
8f80735c0cbd2a0714410af3237d0ad71ee61555 | 97a3ea44ae0103ea399778df78e42977b15c0230 | /man/get_all_events.Rd | fd459b05e63910f821ae3d999503f376c79f4e3e | [] | no_license | resplab/epicManual | cc069ce65b7b870d923d5ae1c896d95ce5aa7035 | 8e7290c7d7f31245e40aa9c9df0c62a6d6a77db2 | refs/heads/master | 2022-02-22T03:35:14.101436 | 2019-08-28T00:06:32 | 2019-08-28T00:06:32 | 198,313,270 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,339 | rd | get_all_events.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/core.R
\name{get_all_events}
\alias{get_all_events}
\title{Get Events Matrix}
\usage{
get_all_events()
}
\value{
Returns a data frame consisting of all events from the model simulation.
The data frame returned has parameters as follows:
\it... |
cb0ed2266ddc5daeeff57536f6509b664f6334f8 | 91b563b0b521d5fdf446bf0441c9c04098eeb854 | /bin/install | 7c0751a2265bf64f887cc9394da53335e6130c8e | [] | no_license | pedmiston/forks | 4373945112763a741b38e0d504725f8ef4ebc23b | 71a19433911c3a21f692a62706d1bef693681522 | refs/heads/master | 2021-01-01T06:42:43.950652 | 2017-07-22T23:12:47 | 2017-07-22T23:12:47 | 97,492,037 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 64 | install | #!/usr/bin/env Rscript
devtools::document()
devtools::install()
| |
bb002cb73cec7fb96c930664d7bc9caf521fee09 | c27f0c3e89a68b8aa5591ba832c58e76ec507ad9 | /better/chiq7/chiq7.R | 5dbc4b78c6fccafa27fc0ec3ca651305c2641a01 | [] | no_license | darkryder/DMG_project | aeb164800352cb1fa969b1d8788039157aa04aac | 5e23f3ea25bf93dbbb8ed917d7531a3b555ac5ff | refs/heads/master | 2020-04-10T23:41:43.979490 | 2015-09-13T10:31:57 | 2015-09-13T10:31:57 | 41,957,773 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 734 | r | chiq7.R | v<-read.csv('cleaned_train.csv',header=T)
printable_index <- function(i){
answer = i
if (i <= 218) {
answer = i-1
}
if (i >= 240) {
answer = i+1
}
return (i)
}
########make a list gg=[] having var names(eg 1,5,6,) which are CATEGORICAl then check if( i in gg) :do//// else i++
#i... |
9282213e8c37085e58ec823058e46555d18f60d5 | cd072a1ded3c066073f02be680e171d1f295c3e7 | /AD_GWAS/pchic_analysis/gtf_processing.R | 2953ece89db7d7016693abf3571b867681db215b | [] | no_license | Nicolas-Eng/ShenLab | ead12265246c422cde17f1c03d8f1affe071776a | 784460eaec1a4bc61bc2024ca28ae1e4a214321c | refs/heads/main | 2023-04-21T05:26:39.099980 | 2021-05-05T05:47:05 | 2021-05-05T05:47:05 | 364,122,962 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,769 | r | gtf_processing.R | #
# gtf_processing.R
# Author: Michael Song
# Last modified: 2019-01-15
# This script processes a GTF file for use with the main analysis script.
#
# Set up environment and load settings ------------------------------------
# Clear workspace before running script.
rm(list=ls())
# Turn off scientific notation for w... |
3ba5df31f3d4c00c8d8aaaa298564612add0d4cf | 3a2b15c469cf4778a100340bcc2cf2642edd37b0 | /man/current.other.Rd | 86d272f63b16be850e4ae0e801d10353b680ea34 | [] | no_license | Qingys/MILC_backup | 9657aaf2267ffad568c8f8fa2772d3381f31a874 | cabc1bcbabf99cd250abf7b44f662138ed5a4f7d | refs/heads/master | 2023-03-17T01:53:43.623830 | 2014-02-18T00:00:00 | 2014-02-18T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,191 | rd | current.other.Rd | \name{current.other}
\alias{current.other}
\docType{data}
\title{current.other dataset
}
\description{
An R object of class "list" containing Cumulative Incidence Function estimates for other cause (not lung cancer) mortality, for current smokers by age (5-years age group), gender ("male" or "female") and smoking... |
b89bdfb6005718438813d92e4c719f4f7bc8daa4 | b667618e65e08cec98c0c75a00bb7b6d079bf34d | /code.R | 09954e623fd6888c888845d3be28f644fb26e4aa | [] | no_license | mingzhuye/Flarition_Health_Test | 843b9cc5032b449bceb3758366d49d1e59e8bdd4 | fa663582147107982fc12b52b9f9729cb50d66bc | refs/heads/master | 2021-07-15T06:15:08.121920 | 2017-10-19T19:50:48 | 2017-10-19T19:50:48 | 107,591,451 | 0 | 0 | null | null | null | null | WINDOWS-1258 | R | false | false | 3,149 | r | code.R | orders = read.xlsx("flatiron_qs_orders_admins_july_16.xlsx", 1)
administration = read.xlsx("flatiron_qs_orders_admins_july_16.xlsx", 2)
demographics = read.xlsx("flatiron_qs_orders_admins_july_16.xlsx", 3)
patients = read.xlsx("flatiron_qs_orders_admins_july_16.xlsx", 4)
practices = read.xlsx("flatiron_qs_orders_admin... |
70eddc2e22096bb58eb658979f09d3cf37f44eaf | 6cf9a94de51479dc65dad3608a4b315ba289a36f | /test_not_run/hipo15_subgroups_deseq2.R | 20030b18a6491f0139b6be9899b4bba1de81923d | [] | no_license | NagaComBio/cola | 818c3afdab7e140d549ab9ebf6995a882c967cf5 | 304b3cf771e97ced7f4b20388815b882202cdd84 | refs/heads/master | 2021-04-27T08:31:19.184145 | 2018-02-26T10:00:07 | 2018-02-26T10:00:07 | 122,491,685 | 0 | 0 | null | 2018-02-22T14:45:23 | 2018-02-22T14:45:23 | null | UTF-8 | R | false | false | 6,657 | r | hipo15_subgroups_deseq2.R |
library(methods)
library(GetoptLong)
datatype = "cell01"
GetoptLong(
"datatype=s", "cell01"
)
# library(cola)
source("/home/guz/project/development/cola/load.R")
# register_top_value_fun(AAC = function(mat) AAC(t(mat), cor_method = "spearman", mc.cores = 4))
source("/home/guz/project/analysis/hipo15/script_for_re... |
287f43e7674c47230f1782e11e35da94c1784db1 | b2f61fde194bfcb362b2266da124138efd27d867 | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Experiments/Basler/terminator/stmt21_252_267/stmt21_252_267.R | 04b47354d606c7ce533fa9d9bd21db2fb330b345 | [] | no_license | arey0pushpa/dcnf-autarky | e95fddba85c035e8b229f5fe9ac540b692a4d5c0 | a6c9a52236af11d7f7e165a4b25b32c538da1c98 | refs/heads/master | 2021-06-09T00:56:32.937250 | 2021-02-19T15:15:23 | 2021-02-19T15:15:23 | 136,440,042 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 720 | r | stmt21_252_267.R | c DCNF-Autarky [version 0.0.1].
c Copyright (c) 2018-2019 Swansea University.
c
c Input Clause Count: 13204
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 13203
c
c Performing E1-Autarky iteration.
c Remaining clauses count after E-Reduction: 13203
c
c Input Parameter (command line, ... |
e301f5335bc3ae660aa660ba0feb715666afd410 | da8dae69e597072bc616936d1d72a96f65e4efa0 | /code/oldversions/v4_20190329/tools/nictools/R/cheb.R | 9adb2638b6552a27ec03da2b110ad878977b776d | [] | no_license | UCL/provis | 71e82c383cd9414840e57c2a2867826d6b4ee3e6 | 86a287c7bc705d4aeffb9bbcf96747e97e6d688b | refs/heads/master | 2020-08-01T04:08:20.198284 | 2019-11-08T12:09:43 | 2019-11-08T12:09:43 | 210,310,151 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 478 | r | cheb.R | #' Compute matrix of chebyshev polynomials
#' @param x vector of values betwen -1 and 1
#' @param n n-1 = highest order polynomial
#' @return cheb (nx x n) matrix of results
#' @examples
#' x<-matrix(2*c(0:10)/11-1,11,1)
#' c1< cheb(x,5)
cheb<-function(x,n) {
nx<-nrow(as.matrix(x))
cheb <-matrix(rep(1,n*nx)... |
46c661eb3ef6508f9338c472c410cfbc021d93bc | 5ee3003b66131a65253f18b82608e9fc526ae0c5 | /Figure_2/monocle_GBS_unexp.R | 6f8b3bc1d60a5b3f3029c17f57d7d0347a46ef63 | [] | no_license | yanailab/Pathcourse | 1b8e5d546a71a683a703052e38b1969d5b057217 | fd8e53e9e54e0c23b3116a2de4d838bc51ed5f4f | refs/heads/main | 2023-04-14T19:51:19.357475 | 2022-08-19T19:30:39 | 2022-08-19T19:30:39 | 390,096,509 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,473 | r | monocle_GBS_unexp.R | #### Installing and loading packages ####
setwd("C:/Users/Gal/Dropbox (NYU Langone Health)/Projects/Pap36_Pathcourse/analysis/analysis_by_figure/new_2020_5_16/Figure_2")
options(warn=-1)
#source("http://bioconductor.org/biocLite.R")
#biocLite("monocle")
library(monocle)
#### Loading data ####
## you need raw matrix... |
b6c705134dbd4c7a740f7164d44776312037fc48 | 8eed7a301375eb2920f0ba032fb6428bce9e33a7 | /SS/Base_model1/ParameterCheck.R | e9c024cc471c0412ea370b737255f55f134e373f | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | melissamonk-NOAA/GopherBlackYellow2019 | 363b9c5b6b2b32703cd31225678db288d53a10dc | bfa62d2ae6e158ed17b66ee01b03b22ad79999d1 | refs/heads/master | 2022-02-22T18:49:22.490814 | 2019-10-02T19:21:53 | 2019-10-02T19:21:53 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 615 | r | ParameterCheck.R |
rm(list=ls(-1))
library('r4ss')
# update_r4ss_files()
# devtools::install_github('r4ss/r4ss')
WD <- c('C:/XiHe1/GPHR2019/SSModel/SS/')
setwd(WD)
with.covar = T # T: without -nohess; F: with -nohess
a1 <- SS_output(dir=WD,covar=with.covar)
a2 = a1$parameters
a3 = a2[!is.na(a2$Active_Cnt),]
a4 = a3[,1:12]
rowname... |
daaab689340eb235e0a8ac214ddd493ffe44ff7e | b4c83dfd4419ad6ff8a41cfca4992b0e580907f0 | /DADM_Final_Project.R | 4e5f4d4fbfe151b3662ecfade92366254ae03fa4 | [] | no_license | jainkavisha/DADM | e7d33852a0ccaa4c522288e640b3ecfdf2fbb6e9 | c56709f6db7255c97c42dda4a08fd3180fea8c02 | refs/heads/main | 2023-01-18T21:50:53.117360 | 2020-11-29T19:36:58 | 2020-11-29T19:36:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,229 | r | DADM_Final_Project.R | # Getting and setting the appropriate working directory
getwd()
setwd("/Users/mihikagupta/Desktop/SEM_2/DADM/DADM_FinalProject")
# Loading relevant libraries
suppressPackageStartupMessages(library(tidyverse))
suppressPackageStartupMessages(library(skimr))
suppressPackageStartupMessages(library(GGally))
suppressPackage... |
7ae8ff25c9689499e1cbd9fc3c124e9edbbf9441 | 8b209188d063cd3c173e0fb1262b11ef16ec6cfe | /man/add_window_l.Rd | 08bc3f84c514cd539bd1ef7adcf32d36b309012d | [] | no_license | cran/tnet | 26e7a2f9e737b9cde34e29a9918315d183a2ca31 | 15bd16db1192d2ff0712aa916785fd50d6927fd0 | refs/heads/master | 2021-01-15T12:26:21.300405 | 2020-02-24T17:00:02 | 2020-02-24T17:00:02 | 17,700,542 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,273 | rd | add_window_l.Rd | \name{add_window_l}
\alias{add_window_l}
\title{ Add smoothing window to a longitudinal network }
\description{
This function adds negative ties (i.e., a smoothing window) to a longitudinal network.
}
\usage{add_window_l(net,window=21, remove.nodes=TRUE)}
\arguments{
\item{net}{ Longitudinal network }
\i... |
a232b63aed52ecd8d7fa4b248ee8cb60aa9231e6 | f19e1d54a1405ca75e2b4a059278246a47423da6 | /R/1_worldclim_crop.R | 37d4258a0d1c937ba214354d813942da8b602487 | [] | no_license | Projeto-BHRD-INMA/clima | 934257a337145dbb721b47b818339571e9f61a4c | 1688fc6930051bf93d87019827f3af51b2cc2b0f | refs/heads/master | 2022-11-14T06:15:09.832652 | 2020-06-19T22:41:37 | 2020-06-19T22:41:37 | 269,772,150 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,190 | r | 1_worldclim_crop.R | ############################################
# Explorando dados climáticos da BHRD
# Bruno M. Carvalho - brunomc.eco@gmail.com
# Cortando rasters de GCMs para a BHRD
############################################
library(raster)
library(rgdal)
library(stringr)
# dados worldclim
# mask da regiao da BHRD (extensão do po... |
8f546e4a915e9106689e96e4adeb11d4ed72270f | 9a430b05c1e8cd124be0d0323b796d5527bc605c | /wsim.distributions/R/find_cdf.R | a5b7de01136ac2d68af4111a4459be2a5e45e767 | [
"Apache-2.0"
] | permissive | isciences/wsim | 20bd8c83c588624f5ebd8f61ee5d9d8b5c1261e6 | a690138d84872dcd853d2248aebe5c05987487c2 | refs/heads/master | 2023-08-22T15:56:46.936967 | 2023-06-07T16:35:16 | 2023-06-07T16:35:16 | 135,628,518 | 8 | 0 | null | null | null | null | UTF-8 | R | false | false | 931 | r | find_cdf.R | # Copyright (c) 2018 ISciences, LLC.
# All rights reserved.
#
# WSIM is licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License. You may
# obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0.
#
# Unless required by applicab... |
fb8abb0fd050500c318ceef2722879eaeed17208 | def66edebf317dd925261ee343655b06681e7490 | /man/gg_hide_X_axis.Rd | 48e83c77e16d321d513fc84220c18f3dccf3d2bf | [
"MIT"
] | permissive | terminological/ggrrr | 5e0a925fc858c7b7e020372b8dd6be29688bef1c | 82ebcec9c1f71a8b49d733302cd6c6e72d6d5a57 | refs/heads/main | 2023-04-06T23:56:58.090401 | 2023-03-28T17:21:48 | 2023-03-28T17:21:48 | 489,738,724 | 0 | 0 | MIT | 2022-06-16T14:18:41 | 2022-05-07T17:24:53 | R | UTF-8 | R | false | true | 259 | rd | gg_hide_X_axis.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ggplot-utils.R
\name{gg_hide_X_axis}
\alias{gg_hide_X_axis}
\title{Hide the x axis of a plot}
\usage{
gg_hide_X_axis()
}
\value{
a theme
}
\description{
Hide the x axis of a plot
}
|
97491cc074e7fcf8b6c8f3b41aa2535e4b17a2c7 | d25ffe6711f9b621f5cf3d9e0daed2ff5dba5d8a | /R/rp_sample_parallel.R | bf3322be406f6109f9f02d70ce6f01c750acf1d5 | [] | no_license | bplloyd/CoreHF | 0313e782b3f199026e3e8db7273ce9e8bef3f78a | 2aae9c6817db0c3168d104d8654d2b180e3e6ce6 | refs/heads/master | 2021-01-21T11:24:05.395756 | 2017-07-20T14:01:11 | 2017-07-20T14:01:11 | 91,341,924 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,664 | r | rp_sample_parallel.R | rp_sample_parallel = function (portfolio, permutations = NULL, max_permutations = NULL)
{
#library(parallel)
#portfolio
if(is.null(max_permutations))
max_permutations = 200
if(is.null(permutations))
permutations = 100000
ncore = parallel::detectCores()
cl = parallel::makeCluster(ncore)
env = ne... |
935ae46080c8e4450987201adcc223d0b2ac6d1a | 39b6b094b248c1f423539052ea81bb40ec37ff00 | /plotCalibrationFits.R | 3971f9bc3f7cbc8294bba9557ba94628bea1a709 | [
"MIT"
] | permissive | k-wheeler/coralReef | 6eb187fe15d1362f8aaa8c197f01fd6f0890605e | 374348838ba2710607717527b87b900402ad04de | refs/heads/master | 2020-04-26T05:04:54.203518 | 2019-05-06T21:58:46 | 2019-05-06T21:58:46 | 173,322,229 | 0 | 0 | MIT | 2019-03-01T15:11:41 | 2019-03-01T15:11:40 | null | UTF-8 | R | false | false | 680 | r | plotCalibrationFits.R | ##' Plots the calibration fits
##'
##' @param out.mat JAGS output in matrix form
##' @export
plotCalibrationFits <- function(out.mat,dat,years){
regions <- c("Lower Keys","Middle Keys","Upper Keys","Biscayne Bay","Dry Tortugas")
for(r in 1:5){
xCIs <- matrix(nrow=3,ncol=0)
for(j in 1:(ncol(out.mat)/5)){
... |
dcc47c21be8aa1261b0e2605e5f94dfb416f284b | 47aa1badb4a1b01b634ab6fa0e2c18050b4706d2 | /scripts/IRkernel.R | 55bbad8f26506327205e18f5364fdb313b75d6d9 | [] | no_license | bryanpaget/DataScienceWorkstation | e016ac7e13b900c4e2fc39e2f2d5cc07a5de50bb | 64130e0417dfd7cb7935c401ea3ecf1da3fe5d37 | refs/heads/master | 2023-01-02T04:56:18.912286 | 2020-10-16T03:25:34 | 2020-10-16T03:25:34 | 299,076,651 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 109 | r | IRkernel.R | install.packages('IRkernel')
IRkernel::installspec() # to register the kernel in the current R installation
|
76d77f24fa025350327e6ab37269e50e018b630e | 4863435653da8649080259a7bb151c436782be6d | /style.R | f00b80a812f8df94ef98e7329b27732c58f95631 | [] | no_license | Carnuntum/agree | 842e5e8898deb3fae7775e03edcff7cb95aa0f5e | 2ca81550cf8512075515c62d08b96da746d2f1ce | refs/heads/master | 2023-05-30T04:00:05.889149 | 2021-06-23T18:15:08 | 2021-06-23T18:15:08 | 288,434,397 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,159 | r | style.R | navbarCol <- tags$style(HTML(
'.skin-blue .main-header .navbar {transition:1s}
.skin-blue .main-header .navbar:hover {background-color: dimgrey}'
))
bodyCol <- tags$style(HTML(
'.content-wrapper {background-color: dimwhite;}'))
dropMenuStyle <- tags$style(HTML(
'.tippy-tooltip.translucent-theme {backg... |
d7b7b8dfa73990222cb0bbfa24906a54a2e084f2 | fb4f18c9816cff08debc4d7c4d0ca035920952ea | /Ex_4/functions/obj_kernel.R | c740acc54b8557ad63aa352cbe14b988ba784774 | [] | no_license | marcohv/exercises_ts_dtu | cdd880768df7bbb7d12a92feb5738249777fe6e7 | cdf5818a51447b4adce742024b68e387901ea39a | refs/heads/master | 2020-03-27T19:39:13.452140 | 2018-09-18T13:43:11 | 2018-09-18T13:43:11 | 147,003,352 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,738 | r | obj_kernel.R | ## Wrap the leave-one-out in a function which returns the score
obj_kernel <- function(h, frml, data, k = k, ieval = 1:nrow(data), n_min=10, local_second_order = TRUE, return_yhat = FALSE){
## Should second order terms be added to the data and frml
if(local_second_order){
## Input variables
nms ... |
4039e1c2ef6407bee1789d34b68983087d7d27d2 | 877cca47bedf6725dda3fd99a97a9cc60f030beb | /scripts/dataframe_calendar.R | db5cd1ed100515f67e6d4056afac7d9f6cc674bf | [
"MIT"
] | permissive | info-201a-au20/airbnb-covid-analysis | 7a55bb8ec4851e0e08c70bb5b5b51152a012f65e | 6985ec2d54ba740a731a37d912c6112b6a758858 | refs/heads/master | 2023-04-04T19:28:30.521964 | 2021-03-18T00:06:25 | 2021-03-18T00:06:25 | 312,765,685 | 0 | 1 | MIT | 2021-04-18T22:11:01 | 2020-11-14T07:10:19 | R | UTF-8 | R | false | false | 229 | r | dataframe_calendar.R | # will use next analysis
# seattle_calendar <- read.csv("../data/Seattle_2020_October/calendar.csv.gz", stringsAsFactors = FALSE)
# tokyo_calendar <- read.csv("data/Tokyo_2020_October/calendar.csv.gz", stringsAsFactors = FALSE) |
b6fcd06ad289d84e5da6512d82d581f39e7baeed | 8b23d55e966e7bc0b636374296d0077aa28a7d17 | /Plots_for_Paper_vmat/scripts2/scriptforEDrepeat.R | b9829767bc9632d32075045b81195bdaadea5f6b | [] | no_license | pcarbo/gtexresults_matrixash | 74ab9f56a31fe4125ae5c368f3d21f638db0828e | 4e9b14e836054178942c9d58c6405cc2ec0afbc8 | refs/heads/master | 2021-01-22T20:26:33.891110 | 2017-03-23T18:22:28 | 2017-03-23T18:22:28 | 85,109,000 | 0 | 0 | null | 2017-03-15T18:45:27 | 2017-03-15T18:45:27 | null | UTF-8 | R | false | false | 1,282 | r | scriptforEDrepeat.R | library('mashr')
library('ExtremeDeconvolution')
t.stat=read.table("~/jul3/maxz.txt")
s.j=matrix(rep(1,ncol(t.stat)*nrow(t.stat)),ncol=ncol(t.stat),nrow=nrow(t.stat))
v.mat=readRDS("~/test.train/vhat.RDS")
v.j=list()
for(i in 1:nrow(t.stat)){v.j[[i]]=v.mat}
mean.mat=matrix(rep(0,ncol(t.stat)*nrow(t.stat)),ncol=ncol(t.s... |
3b8fa575b00b86c38f7eeaa8cf0213db49de1854 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/DWreg/examples/dw.meanvar.Rd.R | 806bc05f3f5eee4c7213d841eec518f6972dded7 | [] | 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 | 283 | r | dw.meanvar.Rd.R | library(DWreg)
### Name: dw.meanvar
### Title: Mean and Variance of Discrete Weibull
### Aliases: dw.meanvar
### Keywords: dw.meanvar
### ** Examples
dw.meanvar(q=0.9,beta=1.5)
#compare with sample mean/variance from a random sample
x<-rdw(1000,q=0.9,beta=1.5)
mean(x)
var(x)
|
671f61cc379b90cd607286db92040d9315d9a922 | ba945c14ead9387327f06f36fd744b4be6c0fdba | /Sun/Sun_O5.R | 56271c2627445c9ff13da309d6ad0eb370e081bd | [] | no_license | wissebarkhof/hpc-matrix-multiplication | 11b63543a4be259b65cdbe34a8044f7ded52cccb | 760945a3a5c0731873cea5a13fe505e5f3a89a77 | refs/heads/master | 2020-04-15T16:29:01.721027 | 2019-01-11T14:43:05 | 2019-01-11T14:43:05 | 164,838,732 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,396 | r | Sun_O5.R | setwd("~/Google Drive/10.semester/02614 HPC/Assignment 1/GIT/Data")
Sun_O5_kmn <- read.table("DataSunO5/SunO5kmn.dat", quote="\"", comment.char="")
Sun_O5_kmn$TYPE <- "kmn"
Sun_O5_knm <- read.table("DataSunO5/SunO5knm.dat", quote="\"", comment.char="")
Sun_O5_knm$TYPE <- "knm"
Sun_O5_mkn <- read.table("DataSunO5/SunO... |
8d683bf45c96b507523ebaf11ee70cb986898b8b | 2ee70a959208a50de0f96bef772b6f5f025b67c4 | /CIS8695_NeuralNet_Basic.R | 062a1a67c0dbf92ea4d86dc814c5d012100d97f4 | [] | no_license | DarshikaKesarwani/Project | 16775923171f2705fec7aa0f0486409829d113a9 | f669a7c2fbd7058cc12705ada6833938bcd2732a | refs/heads/master | 2020-04-27T15:42:09.796593 | 2019-03-31T06:06:33 | 2019-03-31T06:06:33 | 174,456,361 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,040 | r | CIS8695_NeuralNet_Basic.R | rm(list = ls())
setwd("C:/Users/lxue5/Dropbox/2019Sp/CIS8695/5 NN AI")
install.packages ("neuralnet")
library(neuralnet)
library(nnet)
library(caret)
accidents.df <- read.csv("CSV_Accidents_new.csv")
# selected variables
vars <- c("ALCHL_I", "PROFIL_I_R", "VEH_INVL")
# partition the data
set.seed(2)
training<-sample(... |
c3b075b5cc8b3d59a311b10d3f384f4099338121 | a980b2fa82b3c6ba0100457402c84d500923215a | /tests/testthat/test-wait.R | c841910babdcc19901261427e327b0bea75d4efa | [
"MIT"
] | permissive | RLesur/crrri | b5bc761f9e0571012f5ef36e89a69503ec3e7cc7 | 69c54e657f117b9e30b6a5475604e1e0c6584150 | refs/heads/master | 2022-09-09T06:55:11.776063 | 2021-03-11T14:48:11 | 2021-03-11T14:48:11 | 157,903,442 | 167 | 13 | NOASSERTION | 2022-08-22T15:48:30 | 2018-11-16T18:00:50 | R | UTF-8 | R | false | false | 1,206 | r | test-wait.R | context("test-wait")
test_that("wait(): both pipes work with a promise as an argument", {
value <- runif(1)
pr <- promises::promise_resolve(value)
with_magrittr_pipe <-
pr %>% wait(0.1)
expect_identical(hold(with_magrittr_pipe), value)
with_promises_pipe <-
pr %...>% wait(0.1)
expect_identical(... |
96518eac783b29e46e093cbcec68342207d41d33 | 4fc2fbdb5adb83ecda830f3054dc019a9e3aba12 | /R/plot.shapes.R | c77fc14f1659e8c6f8013ed008fd1887742713d1 | [] | no_license | briatte/rigraph | a8d520edd5aa727dac3ab4ea92b5efa4dfc7af07 | 7403e8a65bb99f1047b85f62e162a1c34e9d6137 | refs/heads/dev | 2021-01-22T11:27:40.977904 | 2017-05-03T16:08:28 | 2017-05-03T16:08:28 | 92,696,135 | 1 | 1 | null | 2017-05-29T00:49:22 | 2017-05-29T00:49:22 | null | UTF-8 | R | false | false | 34,442 | r | plot.shapes.R |
# IGraph R package
# Copyright (C) 2003-2012 Gabor Csardi <csardi.gabor@gmail.com>
# 334 Harvard street, Cambridge, MA 02139 USA
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation... |
240effdcafee599b6ffbf0ae299cf93c9fb9ec64 | 7eb63399fa00e3c547e5933ffa4f47de515fe2c6 | /man/print.fromXYZ.Rd | 759b6e3f46bfc037e96d68f68b1f83a14da673e3 | [] | no_license | bentaylor1/lgcp | a5cda731f413fb30e1c40de1b3360be3a6a53f19 | 2343d88e5d25ecacd6dbe5d6fcc8ace9cae7b136 | refs/heads/master | 2021-01-10T14:11:38.067639 | 2015-11-19T13:22:19 | 2015-11-19T13:22:19 | 45,768,716 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 405 | rd | print.fromXYZ.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/spatialAtRiskClassDef.R
\name{print.fromXYZ}
\alias{print.fromXYZ}
\title{print.fromXYZ function}
\usage{
\method{print}{fromXYZ}(x, ...)
}
\arguments{
\item{x}{an object of class spatialAtRisk}
\item{...}{additional arguments}
}
\va... |
548635dcc049774d36437394a0e2fff3776463ce | 8b61baaf434ac01887c7de451078d4d618db77e2 | /man/rm.na.Rd | 1fadbe0c85dc13693f6f0931055d604212908f15 | [] | no_license | drmjc/mjcbase | d5c6100b6f2586f179ad3fc0acb07e2f26f5f517 | 96f707d07c0a473f97fd70ff1ff8053f34fa6488 | refs/heads/master | 2020-05-29T19:36:53.961692 | 2017-01-17T10:54:00 | 2017-01-17T10:54:00 | 12,447,080 | 3 | 1 | null | null | null | null | UTF-8 | R | false | true | 387 | rd | rm.na.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rm.na.R
\name{rm.na}
\alias{rm.na}
\title{remove NA's from an object}
\usage{
rm.na(x)
}
\arguments{
\item{x}{a 1D object}
}
\value{
an object with no \code{NA}'s
}
\description{
remove NA's from an object
}
\note{
Defunct: \code{\link{na.omi... |
d9d453bac0997144df6e06b1ec3f28b1f295276b | c784be70105a2f34f820295e1189b351e33a56dd | /R/queue.R | f25a9d84697f0ba992ba22b9e6515c92066b0e19 | [] | no_license | sumprain/dbMapR | 80f39be8d1bcee5812ebe8b256b6f2ef7238fee8 | 9642a3c4c5e21f1344fdee6d7f0b71f44df741e2 | refs/heads/master | 2021-01-09T20:17:19.104350 | 2016-01-18T15:28:24 | 2016-01-18T15:28:24 | 42,582,541 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,739 | r | queue.R | #' @export
queue <- function(max_length = 5L, parent = emptyenv()) {
e <- new.env(hash = TRUE, parent = parent)
attr(e, "max_length") <- max_length
return(structure(e, class = "queue"))
}
#' @export
push <- function(queue, value) {
UseMethod("push")
}
#' @export
empty <- function(queue) {
UseMethod("empty")... |
331c1d0aefc4e68f3457041351fe7e137c0d384d | fffa2b4bc248b745cb0f3986f57b78ab3036c58c | /rankhospital.r | f4a8425f50ee7aca9d65f3ed8576aa7785f1cffe | [] | no_license | pmanickavelu/datasciencecoursera | 3696b0859509d2a5db3f76c444b873eb3d3a740a | 9f667e4fe5c03a189dee1e9d4f15fdeaa0b48d21 | refs/heads/master | 2021-01-11T02:48:28.366326 | 2016-10-21T11:10:43 | 2016-10-21T11:10:43 | 70,921,377 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,582 | r | rankhospital.r | rankhospital <- function(state, outcome, num = "best") {
## Read outcome data
## Check that state and outcome are valid
## Return hospital name in that state with the given rank
## 30-day death rate
outcome_data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
outcome_keys <... |
8e02e4a3bbaed3515f45e1a555268306ffa06328 | 7e3f188372012ed9635facb1a2a3b0bab71cef48 | /R/compare_expr.r | 15ac0220607d2e2f76fbbd28ae7d0667544f4270 | [] | no_license | skranz/RTutor | ae637262b72f48646b013b5c6f89bb414c43b04d | f2939b7082cc5639f4695e671d179da0283df89d | refs/heads/master | 2023-07-10T03:44:55.203997 | 2023-06-23T05:33:07 | 2023-06-23T05:33:07 | 11,670,641 | 203 | 61 | null | 2020-06-17T16:11:34 | 2013-07-25T20:47:22 | R | UTF-8 | R | false | false | 18,099 | r | compare_expr.r | examples.describe.call = function() {
x = 1:5
describe.call(runif(10,1,2))
describe.call(2*3+4)
describe.call(x[1:4])
df = data.frame(x=1:100)
describe.call(df %.% filter(x>80))
}
examples.describe.call = function() {
f = function(x) {
y = substitute(x)
describe.call(call.obj=y)
}
f(2*x)
... |
702d664511509c26d7e42e0ccf1f37fdb553bee3 | b2f61fde194bfcb362b2266da124138efd27d867 | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/E1/Database/Amendola-Ricca-Truszczynski/selection-hard/ctrl.e#1.a#3.E#130.A#48.c#.w#5.s#41.asp/ctrl.e#1.a#3.E#130.A#48.c#.w#5.s#41.asp.R | 59322560ce55ffa0ea261d86a122701949fabbe6 | [] | no_license | arey0pushpa/dcnf-autarky | e95fddba85c035e8b229f5fe9ac540b692a4d5c0 | a6c9a52236af11d7f7e165a4b25b32c538da1c98 | refs/heads/master | 2021-06-09T00:56:32.937250 | 2021-02-19T15:15:23 | 2021-02-19T15:15:23 | 136,440,042 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 91 | r | ctrl.e#1.a#3.E#130.A#48.c#.w#5.s#41.asp.R | 41fe05f586958cb2c255a85f86f35705 ctrl.e#1.a#3.E#130.A#48.c#.w#5.s#41.asp.qdimacs 5377 15598 |
3bcb7d7ea8235fce8dc366e2099268879b962c7b | c5d3abd3a3913b4684328cfd0ac88c2f399efad2 | /content/scholarGenerated/Zeppel2015.r | ab258affa3d280217a2b822b3af8d99f0de79779 | [] | no_license | douglask3/webpageGenerator | 09a3ee3c46019c4c427d70b78c54ab66e1bf1eb3 | c30b66a866513ad71f101ebf822cf3a34cc81279 | refs/heads/master | 2021-01-10T12:20:06.738656 | 2017-02-07T21:36:45 | 2017-02-07T21:36:45 | 43,382,723 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,074 | r | Zeppel2015.r | # Example
header = 'Title: Drought and resprouting plants
Date: 2015-01-01 00:00
Category: Publications
status: published
tags: Publications, Traits for Resistance and Recovery to Disturbance, LPX Dynamic Global Vegetation Model
Many species have the ability to resprout vegetatively after a substantial loss
of biomass... |
c57264f8b720aba6d35d5c1aea7c2a26c94adcd1 | 013c1c5c3220764b25a7fc9d434c502a5c190b93 | /IE7275 working/17jan.R | ca8c3f366b8eab707f3a2c6df469d3fb7cc5bb07 | [] | no_license | mashwinmuthiah/Making_sense_of_data | a0e06eadccd4a63feeb376b793358366e14e3ee3 | 31e9613673ccd8b014f776b0ced5219930217ae5 | refs/heads/master | 2020-04-20T10:08:11.027566 | 2019-02-26T15:59:12 | 2019-02-26T15:59:12 | 168,782,563 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,043 | r | 17jan.R | m<-martix(c(1,2,3,4,5,6),ncol=2)
IQR(usedcars$price)
quantile(usedcars$price)
quantile(usedcars$price,probs = c(0.01,0.99))
quantile(usedcars$price,seq(from = 0,to=1,by=0.2))
boxplot(usedcars$price,main="box plot of used car price",ylab="price($)")
hist(usedcars$price,main="histogram of used car price",xlab="price($)")... |
e9226dac1698f1a4cddf323fc71a568dd8c0353b | 0e7a066f410066e8533031a8fd23b0b6ad7d2258 | /R/Ex_Files_Data_Wrangling_R/Exercise Files/Ch05/05_03/separate_complete.r | 3e6cc1bfb5ad64fd171190a2faef2a4e2fa03cc6 | [
"MIT"
] | permissive | vvpn9/Handy-Tools | 6560c02ef99cc6ef57168e36f744694bc79a69ad | 5b8e59e80832985c352b7f6e578462e61fcbc300 | refs/heads/main | 2023-06-13T23:39:13.146882 | 2021-07-13T06:00:07 | 2021-07-13T06:00:07 | 341,105,420 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 956 | r | separate_complete.r | # Data Wrangling in R
# 5.3 Breaking Apart Columns With Separate
#
# Load the tidyverse and read in the Medicare payments dataset
library(tidyverse)
names <- c("DRG", "ProviderID", "Name", "Address", "City", "State", "ZIP", "Region", "Discharges", "AverageCharges", "AverageTotalPayments",
"AverageMedicareP... |
936e302542a6e7914597e0117c860c17e5264bfe | c06da00ce0c89f3a6323e895df9f0626111d215d | /man/to_size.Rd | 062a652d6b6da2ba607d040a39e3d256537de3f2 | [
"CC-BY-4.0"
] | permissive | iPsych/webmorphR | 41fc542b846a5592bae5374c6037715f9d4cb3ed | 218f5be8b7b2a868aba023113d580421981a752c | refs/heads/master | 2023-05-05T16:59:32.310237 | 2021-05-23T21:52:15 | 2021-05-23T21:52:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,230 | rd | to_size.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/to_size.R
\name{to_size}
\alias{to_size}
\title{Resize and crop/pad images to a specified size}
\usage{
to_size(
stimuli,
width,
height = NULL,
fill = wm_opts("fill"),
patch = FALSE,
crop = FALSE,
keep_rels = FALSE
)
}
\argument... |
c7368c547021f46b82e8c4f6c9ddfce56c89c384 | ef4eb23543224c14f4cae67190d1f82bd881a4a4 | /dfg_for_kilimanjaro/stable_isotope_analysis/iso_ta200.R | 3c6933f81e780b63b67884563343102206b27eae | [] | no_license | environmentalinformatics-marburg/magic | 33ed410de55a1ba6ff943090207b99b1a852a3ef | b45cf66f0f9aa94c7f11e84d2c559040be0a1cfb | refs/heads/master | 2022-05-27T06:40:23.443801 | 2022-05-05T12:55:28 | 2022-05-05T12:55:28 | 9,035,494 | 6 | 7 | null | null | null | null | UTF-8 | R | false | false | 5,704 | r | iso_ta200.R | library(ggplot2)
library(lubridate)
library(reshape)
library(gridExtra)
library(RColorBrewer)
require(RcolorBrewer)
col <- brewer.pal(8, "brBG")
# set working directory
wd <- setwd("C:/Users/IOtte/Desktop/training/")
### load data
iso <- read.csv2("iso_calc_copy.csv", header = T)
ta200 <- read.csv("C:/Users/I... |
a89ff31e10142e6c311c7ebab889c65570f65b9a | 6fb453f3b45cad66751ee817f9b3463c89196972 | /R/concordance_heatmap.R | 580360e99e8804adfa464b3bf98659b7ed857d07 | [] | no_license | SamirRachidZaim/referenceNof1 | 838c74bdad9f99cc4144ed43368dc2b187403e26 | 65f63660a96022c202addef59888e2026faae24f | refs/heads/master | 2022-12-31T22:02:44.858043 | 2020-10-20T15:16:46 | 2020-10-20T15:16:46 | 296,476,075 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,521 | r | concordance_heatmap.R | #' Constructing robust reference standards for Nof1 studies for precision medicine
#'
#' \code{referenceNof1} is the R implementation of the reference biomarker algorithm by (Zaim 2020)
#'
#' @usage concordance_heatmap(jaccard_matrix)
#'
#' @param jaccard_matrix the concordance matrix used to create the heatmap
#'
#' @... |
0d2f6d323eab9146551a4718741f219023db4987 | 6594403b535237e0bc2137b3e929427df3a4b51f | /2011/RJ-2011-009.R | 6b59b7523eee4537ff0030f54c11efe5e023ef45 | [] | no_license | MrDomani/WB2020 | b42b7992493721fcfccef83ab29703b429e1a9b3 | 2612a9a3b5bfb0a09033aa56e3a008012b8df310 | refs/heads/master | 2022-07-13T03:32:29.863322 | 2020-05-18T17:25:43 | 2020-05-18T17:25:43 | 264,994,546 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,376 | r | RJ-2011-009.R | data(srft)
members <- c("CMCG", "ETA", "GASP", "GFS","JMA", "NGPS", "TCWB", "UKMO")
srftData <-ensembleData(forecasts = srft[,members],dates = srft$date,observations = srft$obs,latitude = srft$lat,longitude = srft$lon,forecastHour = 48)
srftFit <-ensembleBMA(srftData, dates = "2004013100",model = "normal", trainingDays... |
f88ed3fce5d6f7bba677237ea9564c38af0a3976 | 34517b52cf00b7203a96516b578fd6464501a74c | /man/impute_missing.Rd | 7409bb53a2266244a7c7554fb548c130ba6d67b2 | [
"MIT"
] | permissive | yllz/hamr | a50aaf0a6f1e766295ead901980119044e876b11 | b3815e194ef67ffaa76a1349cc18c9e662fc9c96 | refs/heads/master | 2020-03-16T00:13:27.623169 | 2018-03-18T15:48:30 | 2018-03-18T15:48:30 | 124,505,982 | 0 | 0 | MIT | 2018-03-09T07:42:46 | 2018-03-09T07:42:46 | null | UTF-8 | R | false | true | 1,235 | rd | impute_missing.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hamr.R
\name{impute_missing}
\alias{impute_missing}
\title{Impute missing values in a specified column of a data frame or a numerical matrix with three simple methods}
\usage{
impute_missing(dfm, col, method, missing_val_char)
}
\arguments{
\... |
6b1c520265887c61d8169e258914d9590f6de652 | 90196f13726d5d9ad5b5c26d141836ef53d4745d | /R/r2.R | 9ae6789ca911b55f5ce5cd04d8fd2be4d2614762 | [] | no_license | CharlesJB/manhattan | 571d05613b297ea01f32d31fb421eb50fc98f405 | ff4ccdb42fb3826c1b167db5167a256283407209 | refs/heads/master | 2021-01-01T16:56:17.779966 | 2015-06-02T19:04:22 | 2015-06-02T19:04:22 | 31,437,329 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,769 | r | r2.R | #' Add r2 values to GRanges object
#'
#' This function will:
#' 1) Find the best SNPs in \code{gr_snps} using the \code{pvalue} parameter.
#' 2) Will extract relevant lines from \code{geno_ld}.
#' 3) Create \code{r2} vector.
#'
#' @param geno_ld The file *.geno.ld produced by `vcftools` or a
#' \code{data.frame... |
e660b6e1355c10a71b56fcf6f108d997295efc44 | 786d5aea1eddb46aff1cbe34e4e3151f2d184acc | /tests/testthat/test-supreme-integration.R | da7ef444b0ea5d914380f0649f09d1d11e126ebf | [
"MIT"
] | permissive | strboul/supreme | 34ea5346f72f79b87c866e78d90f145ff536f6fd | 715c0e1685f47094871eca625d109acd0fd0e6ae | refs/heads/master | 2021-06-07T17:31:10.605554 | 2021-06-05T12:39:51 | 2021-06-05T12:40:31 | 169,471,133 | 61 | 2 | NOASSERTION | 2020-07-08T18:35:32 | 2019-02-06T20:22:40 | R | UTF-8 | R | false | false | 7,031 | r | test-supreme-integration.R |
context("test-supreme: Integration tests")
# integration-data paths
module_output <- file.path("integration-data", "module-output.Rtest")
multiple_server_definition <- file.path("integration-data", "multiple-server-definition.Rtest")
server_exprs_elems <- file.path("integration-data", "server-exprs-elems.Rtest")
with... |
fb5ce8ce71ac938fb0f7c4c0c12a69594a38ae94 | e4a86352f154b710fb2607e9cd8ef01232fec389 | /R/fruit_avg_demo_code.R | 220f7445f1cbd5617ecf66da04ca65b961f921e4 | [
"LicenseRef-scancode-public-domain"
] | permissive | snowdj/debugging | f33431903014c84cf6092b698f03f1c8e0d31c5e | 2740b1f83382ade3f0a6687a9cc106b6065fcc60 | refs/heads/master | 2021-01-16T02:13:26.949642 | 2020-02-15T01:00:24 | 2020-02-15T01:00:24 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,557 | r | fruit_avg_demo_code.R | # setup ----
options(width = 50)
options(error = rlang::entrace)
source("R/knitr-error-wrap.R")
dat <- read.csv("R/fruit.csv", strip.white = TRUE)
source("R/fruit_avg.R")
# first look at dat and fruit_avg(); see error ----
# series of 3 code slides
# in Keynote, position based on "black" (error) example
dat
fruit_a... |
832c1ecbe0ec37dc2b0f5f5de29099036bf79168 | 4d12b578bce8c6508101174c5bb5e5586b5673d4 | /R/scatterplot.R | 948c0161a1ad6c13b31ce6b0d2950178955818be | [] | no_license | swang3/timestudy | 7f00f508674cba20a81e0e43895fa6f3ead24589 | 93f70835fd3599400ca6043226683dd26564418f | refs/heads/master | 2021-08-28T00:54:39.310244 | 2017-12-10T23:52:21 | 2017-12-10T23:52:21 | 107,064,174 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 282 | r | scatterplot.R | scatterplot<-function(data,x_data,y_data,x_lab,y_lab,title){
requireNamespace("ggplot2")
scatter<-ggplot(data,aes(x=x_data,y=y_data))+
geom_point(shape=19)+
xlab(x_lab)+ylab(y_lab)+
ggtitle(title)+
theme(plot.title = element_text(hjust=0.5))
return(scatter)
}
|
253f4732330ab0643b9c2a71e359d7fe922ff207 | e9665a99eda6af9bfb27777dc7c53a339f8b2d70 | /man/normal.Rd | f205d6f0a8fb77bc1f5f4c3a3a258f012f55d077 | [
"MIT"
] | permissive | paulsharpeY/psy.phd | 5bf45b8c8e5deff128c3d6c75312d70ce500bd90 | 9d5965369639650917eb14c45674b856ba116675 | refs/heads/master | 2023-07-02T18:51:01.215697 | 2021-07-26T16:53:08 | 2021-07-26T16:53:08 | 228,865,345 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 274 | rd | normal.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/psy.phd.R
\name{normal}
\alias{normal}
\title{Various tests for normality}
\usage{
normal(x)
}
\arguments{
\item{x}{Data frame}
}
\value{
Data frame
}
\description{
Various tests for normality.
}
|
6f40e0c330e6e733654560ea8475411382465910 | 3d97b24b8b05cefda925dcbd99f07e5e7abda0fb | /dataPrep.R | bc32e5039be778602c65e54a1e6a92241873b97b | [
"MIT"
] | permissive | wurstmineberg/wurstminestats | 8a653c1d3d694bbea4d233e0592af5d295d0bcd2 | 1bf0017812cd69b07c9e47a02097a7b0641a5f1e | refs/heads/master | 2021-01-23T13:18:31.738429 | 2015-09-04T14:52:59 | 2015-09-04T14:52:59 | 16,962,610 | 1 | 0 | null | 2014-05-22T15:16:15 | 2014-02-18T20:27:35 | R | UTF-8 | R | false | false | 3,900 | r | dataPrep.R | #### Datapreparations ####
## Startup
message("Making preparations…")
source("config/options.R")
source("functions.R")
# Checking if wurstmineR needs an update
message("Checking for wurstmineR")
# devtools::install_github("jemus42/wurstmineR", ref = "dev")
library("wurstmineR")
#Sys.setenv(TZ = "UTC") # Don't ask
#... |
e58f97ade7e950b4dfa904385e642dca3f289c0a | 54ab125482e07f85918a361407ac127c2128ef3b | /web scrapping.R | 623644e874c9ce284d0c180c1aee803331c14033 | [] | no_license | vithika03/WebScrapping_in_R | 8b40e2bdcbf1c44c6bb575a8ac0ae5a72aebbfe2 | 3e07ede6baab3c27f63c1af69bd564a5e29d0daf | refs/heads/master | 2020-03-24T02:43:44.055738 | 2018-07-26T04:21:15 | 2018-07-26T04:21:15 | 142,388,153 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 941 | r | web scrapping.R | #install.packages('rvest')
library('rvest')
datalist = list() #define the variable
for(i in 160:175){ #run loop for the number of pages in the website
url <- paste0('https://www.zomato.com/ncr/delivery-in-gurgaon?ref_page=zone&page=',i, '') #changes page for each iteration
webpage <- read_html(url) #read the html p... |
428a66db6782c2a907569a10e50627fa50e11145 | 7531afc00e390923ea286520b931face524a5b45 | /A_Simulations/SimulateSubwise.R | f260679dd1015c21c542903d788c21704d222b20 | [] | no_license | NomisCiri/Social_Adolescence_Public | 0cee432a2abef2662ff423606a50e0226e55f7b8 | cf5151ebf6b1890f032715c3a69c78ca15dc5c75 | refs/heads/master | 2020-05-16T18:53:51.751435 | 2020-02-20T10:29:35 | 2020-02-20T10:29:35 | 183,242,759 | 1 | 1 | null | 2020-02-20T10:29:37 | 2019-04-24T14:11:28 | R | UTF-8 | R | false | false | 22,721 | r | SimulateSubwise.R | ## this script is made so it can run many simulations from the command line.
bashInput <- commandArgs(trailingOnly = TRUE)
#for debugging
#bashInput<-c(1,2)
#setwd(here())
load('simulate.RData')
library(truncnorm)
#What happens if i just duplicate it.... which is a more realistic scenario in our experiment anyway....
s... |
a4d14c588d1d30c219baca0ce25bd267b3dc06f5 | 9bf4135a0dc4eda6c14159616e53f8bd87d404c2 | /man/add_eventscale.Rd | e5aae4b51cfecd967d0745a56c19064a5b306079 | [] | no_license | adeze/events | 2c0c7ebab319dea9c3d13f7ffdc42453f6c39f46 | c245f52726adac5eb529bcf52b92b29b3e2d29ff | refs/heads/master | 2021-01-22T13:07:58.819709 | 2014-03-16T20:46:30 | 2014-03-16T20:46:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 455 | rd | add_eventscale.Rd | \name{add_eventscale}
\alias{add_eventscale}
\title{Apply eventscale to event data}
\usage{
add_eventscale(edo, sc)
}
\arguments{
\item{edo}{Event data}
\item{sc}{scale}
}
\value{
Event data with a scaling
}
\description{
Applies an eventscale to event data
}
\details{
Applies an eventscale to event data. This ad... |
12bbbd7b05e1fb43f4e4299722afd7ed326fd1e6 | 389568d389710a27a5210c837095262fbe85ca9e | /inst/extdata/archive/src/vpathToEpath.R | 336cdade8777d66e179820b38ce54d02177c8ecb | [] | no_license | CBIIT/geneSetPathwayAnalysis | 5fe72e6e58d8cc91f1089c4d8e7152a64cbc3698 | ecdbd6ae8acb4968834c523fa4fbc1a9bc10cd09 | refs/heads/master | 2023-02-08T02:00:11.638585 | 2023-01-31T15:13:27 | 2023-01-31T15:13:27 | 178,019,545 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,839 | r | vpathToEpath.R | # lapply(all_shortest_paths(g, aIdx, bIdx)$res, function(x) {
# cat("IT: ", get.edge.attribute(g, "interactionType", E(g, path=x)), "\n")
# E(g, path=x)
# })
## Get Network
library(paxtoolsr)
library(rcellminer)
library(igraph)
sif <- downloadPc2("PathwayCommons.8.All.EXTENDED_BINARY_SIF.hgnc.txt.gz")
#sif <-... |
a6f5eb19be92363dce5253deba0a74fe277f69ac | 30ec93c0d3a45feeaa6ea38e73c3c660d374b2be | /app.R | b3f5425de0881cad532b468b872c45fc9939f29b | [] | no_license | rgs212/HackathonTeam2 | 6b9450666d63ddb182a38164d7a7be74e96d2a1c | de03d7be9925dd19e859bda62d9994430dc8154e | refs/heads/master | 2022-10-02T17:11:18.948956 | 2020-06-08T09:51:40 | 2020-06-08T09:51:40 | 267,627,092 | 0 | 2 | null | 2020-06-08T09:51:42 | 2020-05-28T15:30:48 | R | UTF-8 | R | false | false | 8,593 | r | app.R | ### notes
library(shiny)
library(DT)
library(shinyalert)
library(shinyBS)
library(dplyr)
# Define UI ----
Human <- read.csv("~/Hackathon/Example.csv")[,-1]
ui <- fluidPage(
titlePanel(p(column(2,img(src = "Exeter.png", height = 100)),
column(8,h1(strong("Complex Disease Epigenetics Group Database"... |
9535195088274b57b79924a223a1cfb710b96eb3 | fb5a4392c02428ef7171e757e9dced834f6b72e1 | /07.PCI.computation.R | faf497752c85bfacc0c771e615b170a6d5f93d10 | [] | no_license | pdicarl3/BiolPsychiatry_2019 | 99d05e44fdf56a3cc109543d4672343725b80ff5 | 82de7fe00e7237b44b6e4b7ebb0957efe9914c69 | refs/heads/master | 2020-04-24T19:52:04.835367 | 2019-07-03T13:59:21 | 2019-07-03T13:59:21 | 172,226,048 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,531 | r | 07.PCI.computation.R | #########################################################################################
### POLYGENIC CO-EXPRESSION INDEX (PCI) computation #####################################
#########################################################################################
### load function to compute A-prime
source("PCI_... |
8a14c905f2eb02bbea3498047b5ab5513d27c285 | 2f2cc4176842b864f287c1b3198bf90990734bcf | /create_dfm.R | 8ca2bde180f15bbe1261adef24900f14f27bdd11 | [] | no_license | m4n0v31/DS_Cap | 1c7315c4133c60980d3bfced8c015cedcff4e535 | 0ab89e87b8254d124bc933a6d5014afdbd7e56b9 | refs/heads/master | 2021-01-10T07:45:19.650755 | 2016-01-12T17:39:18 | 2016-01-12T17:39:18 | 48,003,254 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,905 | r | create_dfm.R | # Compute dtm
library(ggplot2)
library(knitr)
library(tm)
library(quanteda)
corpora <- corpus(textfile("data/*train.txt"))
if(!file.exists("data/dfm.RData")){
dfm <- dfm(corpora)
save(dfm, file="data/dfm.RData")
rm(dfm)
}
for(i in 2:4){
if(!file.exists(paste("data/dfm_", i, ".RData", sep=""))){
... |
d3b0d56d57d27ca6a0ea77ddac0bf985acfbb6a5 | d96320b1375d32f0c7a84ddf621d8e1c2501e478 | /valence_trust.R | 8a78fb3e8d3be69e587742c33770eac5a33a4f11 | [
"MIT"
] | permissive | louismaiden/blogg | e1e0b21019167e220597f892ff929eadece8cada | 446fbad93d86e302e0687967e9f24b840c97a367 | refs/heads/master | 2021-01-24T03:56:52.427976 | 2020-09-25T13:24:03 | 2020-09-25T13:24:03 | 121,855,076 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,781 | r | valence_trust.R | library(dplyr)
library(ggplot2)
library(hrbrthemes)
library(plotly)
library(highcharter)
library(moderndive)
library(readxl)
library(tidyverse)
library(stargazer)
load("C:/Users/nyulo/Documents/R/blogg/tracks_subset")
party <- read_xlsx("C:/Users/nyulo/Documents/R/blogg/political_party_by_year.xlsx")
gdp <- read_xlsx(... |
e1616c7ecc06c2c5034ddeca181abf36f762684f | 5f0cc64d3fc8b19504074004c481a6c3f3ea22a8 | /webtool/scripts/db_operations.R | d496b0b1f7e51b569a942256628306a24543c7dc | [
"MIT"
] | permissive | Parivesh123/rain-fp7 | ba3d7fb650d385d145db450349f1c7e481556518 | 81f0adc91019c6b45a2242dcadeb37368d7900a5 | refs/heads/master | 2020-05-24T21:27:20.787593 | 2017-06-09T17:40:47 | 2017-06-09T17:40:47 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 17,859 | r | db_operations.R | # -------------------------------------------------------------------------
# Risk Assessment Tool
#
# Tool developed within the "Risk Analysis of Infrastructure Networks in
# response to extreme weather" (RAIN) FP7 European project (rain-project.eu)
# by Grupo AIA (www.aia.es).
#
# Authors:
# -- xclotet (clotetx... |
2a643b3fa4818ad854b3960aa55146fc97e0771b | 965348fc1c33ebbce0e9f802bd4213a24eaf44c5 | /man/spectrophoto_boxplot.Rd | 9bb35eec056af109035d9a2727faea4843bc86b5 | [
"MIT"
] | permissive | IreneSchimmel/funkyfigs | 38dfabbd0bc77377f1a422d7dd64187dbb8a2ab5 | 19a789de9f70b3f5a3723bf52bd7b35b52d9bdbb | refs/heads/main | 2023-05-10T09:25:09.624368 | 2021-06-18T13:06:48 | 2021-06-18T13:06:48 | 377,165,566 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 707 | rd | spectrophoto_boxplot.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/spectrophoto_boxplot.R
\name{spectrophoto_boxplot}
\alias{spectrophoto_boxplot}
\title{Spectrophotography boxplot}
\usage{
spectrophoto_boxplot(data, group, y)
}
\arguments{
\item{data}{the desired dataset}
\item{group}{the desired group}
\... |
3534d4361dc4f05a587fd9b560260b358307ff12 | e5ec2b5cd54b930e6a8303536d10deb291964e87 | /Protocol_Simulation/Protocol_Simulation/Unit_Tests/testthat/test_markov_states_sum_to_one.R | cb0c30cc40b5650ae7bb5a42f3d4b457275d9d60 | [] | no_license | bridder/BHM_PS_2020 | df6cd496d9838b770c2be8cab5f7ca8ca01a47eb | 5f6f2ef1388765347eb23f20a8a37a5021212f14 | refs/heads/master | 2020-12-27T21:07:24.600615 | 2020-02-03T20:16:45 | 2020-02-03T20:16:45 | 238,053,473 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,796 | r | test_markov_states_sum_to_one.R | context("Testing markov_states_sum_to_one.R")
test_that("Expect errors if stateDataFrame is not a dataframe.",
{
expect_error(markov_states_sum_to_one("a",1e-6))
expect_error(markov_states_sum_to_one(23L,1e-6))
expect_error(markov_states_sum_to_one(1.5423,1e-6))
... |
e22ffc544eb2cc1c5efcfc48c590ec2329a32467 | f0f133124e46a821abc1b2a8cfd02ea8987340b7 | /all_season_leaflet.R | 3bb52011118436dd71cab12e76ad4c60c1a5e865 | [] | no_license | erinwalls/erhs_535_final | ca9bfd55eac201eb0484facec5a7be5f43b866c4 | c9df7a845e608687b092ec945cf4dbe74912108b | refs/heads/master | 2020-09-09T18:09:26.578879 | 2019-12-14T06:16:25 | 2019-12-14T06:16:25 | 221,520,482 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,956 | r | all_season_leaflet.R | #all seasons
library(tidyverse)
library(rworldmap)
library(sf)
library(leaflet)
library("dplyr")
library(viridisLite)
library(janitor)
country_data_all <- read_csv("country_all_iso_all.csv", )
countriesLow <- countriesLow %>%
st_as_sf
#Temporarily removing air date (not sure how to animate/facet/etc. in Leaflet)
... |
8a2305245be03f437285f0c96be7e7db7e964cef | b6e31cfa3c6bb42f2f7f32ab2c49b372149b4924 | /R/genotype_conf.R | 219f6bd816c7f99eb51242ba4a5b8163954d78c0 | [] | no_license | marcjwilliams1/Alleloscope | b2b2020b800d1ad2e63154b130ae2626d0a13e61 | dbf1b7773c197affedac540b49ea9c4a3a6c0e20 | refs/heads/main | 2023-08-07T14:30:27.923798 | 2021-09-27T03:06:33 | 2021-09-27T03:06:33 | 394,618,929 | 1 | 0 | null | 2021-08-10T10:57:18 | 2021-08-10T10:57:17 | null | UTF-8 | R | false | false | 2,935 | r | genotype_conf.R | #' Compute confidence scores based on posterior probability for each cell in a region.
#'
#' @param X: A ncell by 2 dataframe. Column 1: normalized coverage (rho_hat); Column 2: theta_hat
#' @param gt: A vector of lenth ncell. The numbers represent cell-level allele-specific copy number states.
#'
#' @return A lineage ... |
7936def5e8ca8d2eced0a3f202b9fe5a9147dde3 | 4eb0befe400a36a027196d6ff10840e276e2fb0a | /man/crossover.Rd | 21c7d6a12a09b6c934d2d7dd5ea246334d262a22 | [] | no_license | zhrlin/GA | 736a11499b02a7dd1fdaa29c887dcc3c6cc999b7 | 556810b18ff501a63f4116f0411a745eb57fe7c3 | refs/heads/master | 2020-11-26T23:48:25.893431 | 2019-12-20T09:36:23 | 2019-12-20T09:36:23 | 229,234,330 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 796 | rd | crossover.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/crossover.R
\name{crossover}
\alias{crossover}
\title{Crossover}
\usage{
crossover(chromo_1, chromo_2)
}
\arguments{
\item{chromo_1, chromo_2}{Numeric vectors with binary 0/1 elements. Should be of same length.}
}
\description{
\code{crossove... |
ad89866224bf813dd17ec6a1374765e06fb0d6b8 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googlecomputebeta.auto/man/InstanceReference.Rd | e15ba5a53577a8bb3c0668ab3498e3273e84ef8c | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 542 | rd | InstanceReference.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compute_objects.R
\name{InstanceReference}
\alias{InstanceReference}
\title{InstanceReference Object}
\usage{
InstanceReference(instance = NULL)
}
\arguments{
\item{instance}{The URL for a specific instance}
}
\value{
InstanceReference object... |
fab2e3726ecf7d990d072cec56003dc5a07de27a | ad020fd7242dff50644fdf40f4a42dc5796fb9e9 | /R/gss.R | f7b5b8a2d7fd6ea2e77424a6a6e7ff92ec47d738 | [] | no_license | ktargows/htmllayout | 875c55b457d2d9d6c0f2e913df09dbe958148e0d | 9a57c03c0e1a9e974c17bc2519c4c06bbd153c1b | refs/heads/master | 2021-01-20T00:20:28.193579 | 2015-09-25T02:25:38 | 2015-09-25T02:25:38 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,126 | r | gss.R | #' @export
gssDependency = function() {
htmltools::htmlDependency(
'gss', '2.0.0', system.file('assets', 'gss', package = getPackageName()),
script = 'gss.min.js',
head = '<script type="text/javascript">window.engine = new GSS(document);</script>'
)
}
#' @export
gssMatrix = function(mat, prefix = '') {... |
b36861fa0a18f86af48d572f93dec93e1be486e5 | 25098c7f80c40414f18bf25a7d9a12bf64d1fa94 | /plot1.R | 113a3bd9ddef6562985bf2c87fb9bc69c73dc89d | [] | no_license | dansum15/ExData_Plotting1 | adde5b3219a3227121828fec11b2ca1ad31c83a8 | 4dab7f90cd0370c6ee09d5374d159c43caaa0f8f | refs/heads/master | 2021-01-18T00:13:06.286589 | 2016-01-11T04:34:28 | 2016-01-11T04:34:28 | 49,393,000 | 0 | 0 | null | 2016-01-11T00:49:30 | 2016-01-11T00:49:30 | null | UTF-8 | R | false | false | 1,220 | r | plot1.R | if(!file.exists("exdata-data-household_power_consumption.zip")) {
zipfile <- tempfile()
download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip",zipfile)
file <- unzip(zipfile)
unlink(zipfile)
}
data <- read.table(file, header=T, sep=";")
data$Date <- as.Date(data$Da... |
18051b3c9c10e996a75acf6189e9a49df8ea3eb3 | ebb9a0c747fad779aba3a92266551f0a7c445d8a | /man/tidy_genorm.Rd | 809573110347268a76a490098e6dd829e64d9953 | [] | no_license | dhammarstrom/generefer | ce0215e1ec01b19a9b6d32f7bae28921b04d849d | 5e4532a49a07b32f1a8fec72eb2ac8ed507cafa1 | refs/heads/master | 2021-05-10T18:08:02.275722 | 2020-09-04T13:18:13 | 2020-09-04T13:18:13 | 118,621,326 | 3 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,741 | rd | tidy_genorm.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tidy_genorm.R
\name{tidy_genorm}
\alias{tidy_genorm}
\title{Calculate reference gene stability}
\usage{
tidy_genorm(dat, sample = "sample", gene = "gene",
expression = "expression", log = FALSE)
}
\arguments{
\item{dat}{Name of the data fra... |
3aebf8e2115c8fd5a9066e9dda6ce94673cd207a | ecd0188879f984eba2455fba5c5ad24688737502 | /man/quantile_normalize_cols.Rd | 50e46372a67c7d155f21941a9682fa5b01bc9307 | [
"Apache-2.0"
] | permissive | davidaknowles/suez | 71e0be678dcab61e671b3283d3b19a5245754702 | 8b96529a867a23635027c1d185e68a7add3c9913 | refs/heads/master | 2021-05-07T16:40:01.683115 | 2021-03-18T19:20:18 | 2021-03-18T19:20:18 | 108,589,583 | 4 | 2 | null | null | null | null | UTF-8 | R | false | true | 282 | rd | quantile_normalize_cols.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map_interaction_qtl.R
\name{quantile_normalize_cols}
\alias{quantile_normalize_cols}
\title{Quantile normalize columns}
\usage{
quantile_normalize_cols(input)
}
\description{
Quantile normalize columns
}
|
f2a1f62f69d6402624b3567a025177b45497d1f7 | 9463229d7d9cc5902971aed9c9c4efe2f4083c50 | /tests/testthat.R | 6ca7a5557f8eda924f383cf2e3c87a12fbd7a559 | [] | no_license | sapfluxnet/sapfluxnetQC1 | df66fb4c8282c14aa8921e668f671928c73e300a | c66115798d0c0814f399b1df6505f146594b6bdf | refs/heads/master | 2021-05-01T12:53:11.380754 | 2019-03-01T09:15:47 | 2019-03-01T09:15:47 | 52,454,181 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 70 | r | testthat.R | library(testthat)
library(sapfluxnetQC1)
test_check("sapfluxnetQC1")
|
9088f787ffcfbe67ec285b723e29c695bc760a18 | 249c82f3755ca232fc7e86ffc7416f9f3b1abf77 | /inception.R | 9396ee09d3c045a84acbe14676cc38dd09a2c8f8 | [] | no_license | ashlizjosh/Miniproject | a501d86f38832d757d13ec0f977ebf5373564ed0 | 94ee6bb30abac15d9384d5cb9bb5a84121690b13 | refs/heads/master | 2023-03-06T03:13:26.328774 | 2021-02-12T10:25:37 | 2021-02-12T10:25:37 | 299,181,426 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 528 | r | inception.R | v <- c(97,98,97.5)
g_range <- range(0, v)
plot(v, type="o", col="blue", ylim=g_range, axes=FALSE, ann=FALSE)
#plot(v, type="o", col="green", ylim=g_range, axes=FALSE, ann=FALSE)
#plot(v, type="o", col="blue", ylim=g_range, axes=FALSE, ann=FALSE)
axis(1, at=1:3, lab=c("Bacterial leaf blight","Brown spot","leaf smut"))
a... |
d93cb45dc8757bdbb336b5803fe3fbddda73edce | 0a1c607003a2a773bcbb68d3889909f35af0d758 | /SB_060718/SB_msh2_wt/regioneR/defineMaskedRegions.R | efc93c1e052eb3baa1453de72a75902291806c83 | [] | no_license | ajtock/GBS_CO | 5fed369a6e739fe163ebe490fdb504f9a5b43f0d | c2ff2ab01736060a390e0eceb74504a9cadfbd82 | refs/heads/master | 2021-12-03T17:35:46.211069 | 2021-10-25T14:56:36 | 2021-10-25T14:56:36 | 146,581,321 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,518 | r | defineMaskedRegions.R | #!/applications/R/R-3.3.2/bin/Rscript
# Create and save regions to mask in overlap analyses
library(regioneR)
outDir <- "/projects/ajt200/GBS_CO/SB_060718/SB_msh2_wt/regioneR/"
# Col/Ler mask
maskGR <- toGRanges(data.frame(chr = c("Chr3",
rep("Chr4", times = 3)),
... |
4c71b2ec02f185aec25dd56580a701b9a058f78b | bd4d459aca02be3900cbccd5f1f8a4abe1d30314 | /tests/testthat/test-haplotypes.R | 7c49ed5e7414eddce2c0fe18356da78dc7f9507a | [] | no_license | augusto-garcia/onemap | 98ff53e2825c8cf626cff6c433acd78311ac5fa3 | d71d3c4800ddb00848a15a8635e08f8f1428bd1d | refs/heads/master | 2023-07-07T02:23:26.351957 | 2022-11-25T19:27:50 | 2022-11-25T19:27:50 | 31,918,564 | 35 | 27 | null | 2023-06-28T16:57:49 | 2015-03-09T19:37:05 | R | UTF-8 | R | false | false | 974 | r | test-haplotypes.R | context("test plot haplotypes")
test_that("ordering and HMM parallel", {
test_haplo <- function(example_data, which.group, sum.counts){
eval(bquote(data(.(example_data))))
onemap_mis <- eval(bquote(filter_missing(get(.(example_data)), 0.15)))
twopt <- rf_2pts(onemap_mis)
all_mark <- make_seq(t... |
5cdcb496ce95471530787738faa1cede17a34b26 | f549ca13cfe755675c45105c5bfeba89af836c14 | /SACS_measuresNavon.R | 570f99710ab43a5f9dfdece2c9aaef5cbec15558 | [] | no_license | TeresaWenhart/Navon | d682d44d4717ea9a64e6017928bf7b628fe12396 | 99a7f2783d97edaa03a1dac7f4598142e535897a | refs/heads/master | 2021-09-22T19:21:36.979538 | 2018-09-14T11:30:19 | 2018-09-14T11:30:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,642 | r | SACS_measuresNavon.R | #script to calculate the SACS measures from AGLTresults table
# SACS = Z(%)-Z(RT) Speed accuracy composite scores
# high score--> efficient performance, low score --> poor performance
# calculate this for each congruency separation condition and all trials
library("dplyr", lib.loc="/usr/local/lib/R/site-library")
... |
88e7d0290e5d3cae3091d4d58ff50378efcaa00b | b5dd41686cf7a4c1cc141b3b77064b981ee8e3f1 | /code/group 31_project.R | 87fb87e7172d7247ef13b0a5abb9ed8269615f60 | [] | no_license | miftahulridwan/Airbnb-price-and-superhost | dcf5e1d09fa3ab1a527774315f46b3a9be7bf282 | bfa5942e796113c9c430be454d862601bdc16329 | refs/heads/master | 2022-11-10T08:40:28.240408 | 2020-06-10T19:13:36 | 2020-06-10T19:13:36 | 270,871,264 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 29,376 | r | group 31_project.R | ### Title : Research Skills: Programming with R
### Group Number : 31
### Group Member :
### 1. Adrian Konja (SNR: 2037123 | ANR: u242159)
### 2. Fernando Catalan Resquin (SNR: 2048042 | ANR: u270800)
### 3. George Satyridis (SNR: 20469... |
1ce717edb4405c9f712d3703d440b3c8a58fdc78 | 79b319935938bcd2cea0b936f0225dbcbd133070 | /cachematrix.R | bc78a32791e34948a4fe57827b306c5ad3bd5642 | [] | no_license | majeedfarooq/ProgrammingAssignment2 | 91cf52141285a331e6ce73ec07342abee9e61b65 | 1c42bc0e119c877452f07f8252d908685f0b0af0 | refs/heads/master | 2021-01-16T19:35:46.151164 | 2016-07-02T06:03:00 | 2016-07-02T06:03:00 | 62,430,558 | 0 | 0 | null | 2016-07-02T02:41:44 | 2016-07-02T02:41:44 | null | UTF-8 | R | false | false | 1,274 | r | cachematrix.R | ## Stores any invertible matrix and its inverse into cache
## If the matrix is reused to find inverse cache is checked first
## if inverse matrix is found in the cache, inverse is not
##re-calculated and the cached inverse matrix is used instead.
## This function takes a matrix as input. Stores the matrix in a
##... |
c98a405371e485341284ce75e91d5e6c6b76c5db | 16cad2b04656d88d3a76c6dd70660862a87aef1e | /Part 4 - Clustering/Section 25 - Hierarchical Clustering/HierarchicalClustering.R | 89f2e6057434ebb4a60171a9f1e5dd2b3e885ccc | [] | no_license | ytnvj2/Machine_Learning_AZ | 7d4bfdd01eb7aa5269b5521e575204a960afc0db | 2bc3c0803b48642b4e0290f9df2cf46308a5b2a5 | refs/heads/master | 2020-03-11T11:01:39.372379 | 2018-04-24T10:37:44 | 2018-04-24T10:37:44 | 129,955,508 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 450 | r | HierarchicalClustering.R | dataset=read.csv('Mall_Customers.csv')
X=dataset[4:5]
# dendrogram
dendrogram=hclust(dist(X,method = 'euclidean'),method = 'ward.D')
plot(dendrogram, main = paste('Dendrogram'),xlab = 'Customers',ylab = 'Euclidean Distance')
# fitting X to HC
hc=hclust(dist(X,method = 'euclidean'),method = 'ward.D')
y_hc=cutree(hc,... |
f108edd76057cf88fc375fce29c97bebfa004e5f | d65e2884871291bc757d619383998761884938e7 | /script.R | d540e037b7b2814bbe3db41d3b452571049e31bc | [] | no_license | schepens83/rasp-pi-fitbit | a923656493ef1579300b62625f9471c1b7884521 | a1078167c221753e6c05761130eea4a59368667a | refs/heads/master | 2021-05-13T21:26:11.030638 | 2019-06-28T18:17:58 | 2019-06-28T18:17:58 | 116,463,321 | 0 | 0 | null | 2020-07-28T04:11:45 | 2018-01-06T07:26:47 | R | UTF-8 | R | false | false | 7,696 | r | script.R | source("init.R")
# GLOBAL FILTERS ----------------------------------------------------------
mnth = 4
daily <- daily %>%
filter(date > Sys.Date() - months(mnth))
# sleep_by_hr <- sleep_by_hr %>%
# filter(sleepdate > Sys.Date() - months(mnth))
sleep_detailed <- sleep_detailed %>%
filter(sleepdate > Sys.Date()... |
bcc1a2b03336902a4d96348e72e0809d1ce95cb4 | 6fb04083c9d4ee38349fc04f499a4bf83f6b32c9 | /tests/limitations/test_subset.R | 9b5b5d777c1e62782fefc0dc05133490ff4c4855 | [] | no_license | phani-srikar/AdapteR | 39c6995853198f01d17a85ac60f319de47637f89 | 81c481df487f3cbb3d5d8b3787441ba1f8a96580 | refs/heads/master | 2020-08-09T10:33:28.096123 | 2017-09-07T09:39:25 | 2017-09-07T09:39:25 | 214,069,176 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,469 | r | test_subset.R | ## testing M_Subtraction with different length vectors
## Cases with dates failing
test_that("check FLVector subtraction",
{
flt <- FLTable("FL_DEMO.finequityreturns","txndate")
flv1 <- flt[1:8,"equityreturn"]
flv <- flt[1:10,"equityreturn"]
flv1R <- as.vector(flv1)
flvR <- as.vector(flv)
FLexpect_equal(flv... |
7c8d42134a7fa6891e8659492441f9cd112460b5 | 9ba49020ab6aadecbf45469709b7db6d4a9fb5fd | /R/IDETECT.R | b0ac77f40bd3fa9b2297d9a0c8ee6096fd41f386 | [] | no_license | cran/breakfast | 938d3c35ffd5f8f8f0d3e30b4f831fd935d7b515 | b6db9f5933d7de57db0712f590366cd7ce45674e | refs/heads/master | 2022-10-24T01:37:23.643946 | 2022-10-18T12:45:08 | 2022-10-18T12:45:08 | 92,512,136 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 11,675 | r | IDETECT.R | #' @title Solution path generation via the Isolate-Detect method
#' @description This function arranges all possible change-points in the mean of the input vector in the order of importance, via the Isolate-Detect (ID) method.
#' It is developed to be used with the sdll and information criterion (ic) model selection ... |
8da668b6347eb9e9d96d36771a8bfd57779fed46 | f1de1e557c0013509bfa93ebec936e81549232fe | /Chapter 4/Chapter4_Problem13.R | f8dd8657e1e8364164ef9191505f9af15d9605fb | [] | no_license | BassJohn09/Introduction-to-Statistical-Learning---Solution | f79036df36e4e741b2d2df79cec35f0a4b84cf55 | 499587a5bb836f3d6486b294d7144f983636979b | refs/heads/master | 2020-04-24T10:40:52.559098 | 2019-02-26T23:06:32 | 2019-02-26T23:06:32 | 171,902,010 | 0 | 0 | null | 2019-02-26T23:06:33 | 2019-02-21T16:00:22 | Jupyter Notebook | UTF-8 | R | false | false | 2,238 | r | Chapter4_Problem13.R | # Chapter 4 - Problem 13
# Using the Boston data set, fit classification models in order to predict
# whether a given suburb has a crime rate above or below the median.
# Explore logistic regression, LDA, and KNN models using various subsets
# of the predictors. Describe your findings.
require(ISLR)
crim01 <- ifels... |
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