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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
661e4e065888c3d8b7af73ce82aa6069e55b1e3e | bf3c8997999d5eae8ecbe67499f4d2b83241bb22 | /man/Bdiag.Rd | d0df57eef5d4d6653154d1ad1de02bfe054b8573 | [] | no_license | cran/Rsfar | ebb39aa64b41fb24cfcbcf214661cc5b6abf9a2c | e212914b3b481227a66e68d19a25ed99a5ad1d68 | refs/heads/master | 2023-04-21T08:08:20.163246 | 2021-05-10T07:02:27 | 2021-05-10T07:02:27 | 366,094,340 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 460 | rd | Bdiag.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.r
\name{Bdiag}
\alias{Bdiag}
\title{Create block diagonal matrix}
\usage{
Bdiag(A, k)
}
\arguments{
\item{A}{a numeric matrix forming each block.}
\item{k}{an integer value indicating the number of blocks.}
}
\value{
Retu... |
96f77424f920e719ef2ffbe83e3767e62079460a | 5c133fd27806cfe67789dd4b2db1508764908ee8 | /PLOT4.R | 59f65b98637a4d2cbb9c6b3a83626f85359df156 | [] | no_license | nsamniegorojas/ExData_Plotting1 | 6a42a644911b93d8c9a31ef1d23d6e09e98d4d11 | d79160dfe6e759284d5c4916513c2fa5eae0c89d | refs/heads/master | 2023-01-20T15:56:30.154420 | 2020-11-28T16:52:56 | 2020-11-28T16:52:56 | 300,127,236 | 0 | 0 | null | 2020-10-01T03:21:08 | 2020-10-01T03:21:07 | null | UTF-8 | R | false | false | 1,329 | r | PLOT4.R | rm(list = ls())
#reading file csv
setwd ("C:/R_PROJECTS/EXPLORATORY_DATA")
#install.packages ("readr")
#library("readr")
data <-read.csv2 ("C:/R_PROJECTS/EXPLORATORY_DATA/PROJECT1_EDA/household_power_consumption.txt", header = TRUE)
data <- na.omit(data)
#subsetting data
subdata<-subset(data, data$Date=="1/2/2007"|d... |
b0b6e3b57bdc981d36a2b8c672eb731efb5f6ac8 | 93053d8d9226645f2be4fbbc3de1fe7a444c7746 | /man/check_inds.Rd | a195c2626e90f2f6b839a52082999b76be741bdb | [
"MIT"
] | permissive | USAID-OHA-SI/Wavelength | 500a55dd3c1fba630a481b0610b8a264d1fcddca | 270e88233a0316f521d64adefe70112954c9ab33 | refs/heads/main | 2023-04-04T22:50:52.704479 | 2023-03-16T15:57:57 | 2023-03-16T15:57:57 | 179,119,038 | 3 | 0 | NOASSERTION | 2023-02-10T14:27:14 | 2019-04-02T16:38:22 | R | UTF-8 | R | false | true | 381 | rd | check_inds.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/validate_output.R
\name{check_inds}
\alias{check_inds}
\title{Validate indicators for export}
\usage{
check_inds(df)
}
\arguments{
\item{df}{HFR data framed created by \code{hfr_process_template()}}
}
\description{
Check whether there are any... |
e1c2a3bc6659e9b7baa9182f98729dfdd47ed460 | b0f44e41d4a8d9031373e23dc0a35e9a20279426 | /exp_newdata.R | 60084fce9dd3d641e6e0a3882c968399d1a07637 | [] | no_license | LeoCai/MultiDeviceAlign-R | c6aa5043816668d330976e396d30fd39caa6c46b | 89390a16e38a65bc8608f9415a115195a8ff2d9f | refs/heads/master | 2021-01-17T14:41:22.434860 | 2017-02-20T08:10:27 | 2017-02-20T08:10:27 | 54,257,332 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 410 | r | exp_newdata.R | source("./utils.R")
source("./getMatrixByMag.R")
source("./readData_new_1.R")
source("./addPCAData.R")
lacctop = cbind(top$LinearAcc0,top$LinearAcc1,top$LinearAcc2)
gacctop = getGlobalAccByMag(top)
plot(gacctop[200:1000,2],type="l",main="global top forward")
cor(gacctop[200:1000,2],lacctop[200:1000,3])
plot(lacctop[20... |
0339aed7f4d2ee66fe9045694d2b9ad50efe35a5 | 2a0bd90218f12a1914514048d9c7a025031159b0 | /Main/Level1/scripts/GenerateDrug_ExposureReport_QueryWise.R | b4b08dbdbefae267a697dfd8a0ecfdddd646871e | [
"BSD-2-Clause"
] | permissive | PEDSnet/Data-Quality-Analysis | 366b293ba4bd35f68128a16a4982151316d97145 | 84517d161a281415beddaddc10d9dbcba8423e47 | refs/heads/master | 2021-07-10T20:52:54.906245 | 2021-04-16T15:47:09 | 2021-04-16T15:47:09 | 85,956,773 | 25 | 6 | BSD-2-Clause | 2019-09-09T21:37:42 | 2017-03-23T14:05:57 | R | UTF-8 | R | false | false | 28,918 | r | GenerateDrug_ExposureReport_QueryWise.R | flog.info(Sys.time())
generateDrugExposureReport <- function() {
table_name<-"drug_exposure"
data_tbl <- cdm_tbl(req_env$db_src, table_name)
concept_tbl <- vocab_tbl(req_env$db_src, "concept")
#writing to the final DQA Report
fileConn<-file(paste(normalize_directory_path( g_config$reporting$site_director... |
379105eb00ba97757b7db552f2c27a7081070aa3 | f49961347a44b3137a465182b70f0158885fbca7 | /man/qapi_connect.Rd | 2f78cffdd20a68168492443f0ca31bcc6499f155 | [
"BSD-3-Clause"
] | permissive | jlpalomino/qtoolkit | 4ef5dce9f16336253431cb74b4ecc75179e7e124 | 139777e39a97dae23155e73d2b5331080d829c62 | refs/heads/master | 2020-04-17T15:13:36.535071 | 2019-02-20T17:01:49 | 2019-02-20T17:01:49 | 166,690,221 | 0 | 0 | MIT | 2019-01-20T17:40:01 | 2019-01-20T17:40:01 | null | UTF-8 | R | false | true | 474 | rd | qapi_connect.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api.R
\name{qapi_connect}
\alias{qapi_connect}
\title{qapi_connect}
\usage{
qapi_connect(org_id, api_key, auth_file = ".qapi_auth.R", verbose = FALSE)
}
\arguments{
\item{org_id}{Qualtrics org_id with which to get surveys}
\item{api_key}{Qua... |
6835878c22a0e1dad722bde43fd5a147562f2d6e | a20cb6896e4d32c52a480d068aa879bd292d91f5 | /Ch1.R | be915578ed15bbc8320402a5e8eba2f74391e0b3 | [] | no_license | animohan/artr | aeecf4831b6727bb6101ed2b1fcee36ee776e21c | 30f470e2691d659d4e721bf8a5dd733970765c91 | refs/heads/master | 2021-01-22T08:19:05.809179 | 2017-05-01T13:41:02 | 2017-05-01T13:41:02 | 81,892,133 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,060 | r | Ch1.R |
# mean of 100 random numbers
mean(abs(rnorm(100)))
# 10 random normal variables
rnorm(10)
x = c(1,2,4)
q = c(x, x, 8)
x[1]
x[1:3]
mean(x)
sd(x)
#Internal R datasets
data()
#Nile Dataset
mean(Nile)
sd(Nile)
hist(Nile)
hist(Nile, breaks = 20)
#Functions
oddcount = function(x){
k = 0
for(n in x){
if(n%%2 ==... |
00f9c9458edeea829262b45cfb3e206e46e39650 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.management/man/finspace_update_kx_user.Rd | 2e18936eb0cad6c16f15e35fc473cbab05288f65 | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 817 | rd | finspace_update_kx_user.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/finspace_operations.R
\name{finspace_update_kx_user}
\alias{finspace_update_kx_user}
\title{Updates the user details}
\usage{
finspace_update_kx_user(environmentId, userName, iamRole, clientToken = NULL)
}
\arguments{
\item{environmentId}{[re... |
73ed1187afcbf8b532637bc2f84bf01a996570f6 | 7da20f1ae5d81913f2afd47ecb526b661e78a1e7 | /src/R/gbr.R | 5a6af3fc9c7da5bdfb887a43b78f2851e5c09164 | [
"MIT"
] | permissive | kim3-sudo/pll_analysis | 368184b695dff3734ff1ca3fcd405c594677994f | ff2ff6e6628e02929908125d96a32a8a0b8ceff1 | refs/heads/main | 2023-05-02T23:23:39.241404 | 2021-05-18T16:47:27 | 2021-05-18T16:47:27 | 362,242,716 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,621 | r | gbr.R | # PLL Groundball Analysis
# Sejin Kim
# STAT 306 Sports Analytics
# This script is for the gradient boosted regressor
library(mosaic)
library(dplyr)
library(gbm)
library(parallel)
library(leaps)
library(caret)
library(MASS)
# Read in data
pll <- readRDS(url('https://github.com/kim3-sudo/pll_analysis/blob/main/data/p... |
5be44ca231c8f54745493720dfe268cf2614c728 | 9b701a373869246abf01c52bcaaddfea4e277ba6 | /R/untargeted/replace_rownames.R | f4c37dbcb0359a9b5c40c837ae68733d14b13d80 | [] | no_license | rmylonas/AgerMelo | 4ee9a780c8bd4178d83d5ac9e6d678345099b584 | 7a5bf1036f72be59f87d5314b15afdd6318ef25d | refs/heads/master | 2021-01-23T03:48:48.811500 | 2014-01-09T16:11:13 | 2014-01-09T16:11:13 | 14,770,790 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,519 | r | replace_rownames.R | ###################################################################
# prepare the data-matrix DM and replace the rownames
###################################################################
# remove all objects before processing
rm(list=ls())
# list of experiment names
varieties <- c('fuji','golden', 'pinklady')
mod... |
f168f8dc595b5cf35dd47c794069dbb976b2fa36 | 2bf2033789cde8804ab0c3077b609d329b1e5dcf | /man/GO_terms.Rd | b6ba9b012e0a9319e60a66059ee166e78e435c4d | [
"MIT"
] | permissive | berkgurdamar/predatoR | 42449695d42282fc85ce914b086a5779bc05527f | afe4e565cf69c382975477e852d0d4b197ffb9e7 | refs/heads/main | 2023-01-24T22:34:18.271668 | 2022-12-29T14:17:15 | 2022-12-29T14:17:15 | 415,351,683 | 5 | 0 | null | null | null | null | UTF-8 | R | false | true | 442 | rd | GO_terms.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GO_terms.R
\name{GO_terms}
\alias{GO_terms}
\title{GO Term Number from Gene Name}
\usage{
GO_terms(filtered_info_df)
}
\arguments{
\item{filtered_info_df}{input data.frame which contain only one PDB entries}
}
\value{
Number of GO Terms which... |
cabd517a5db20fc8af2bc11584148c0215993d70 | db0c516d7d341158b01b18d4d186997870cf5f20 | /R/ml_evaluator.R | 6330b2054f87c0b0393ae4af1bde4dde4711aec3 | [
"Apache-2.0"
] | permissive | EugenioGrant/sparklyr | 6b5f1e9dbeda14d203210ba4379f36b8adda6c4f | 984ba4ed18a2ba97b13bf5915a5c2d3781589044 | refs/heads/master | 2020-04-25T14:35:58.081779 | 2019-02-26T08:16:56 | 2019-02-26T08:16:56 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 993 | r | ml_evaluator.R | new_ml_evaluator <- function(jobj, ..., class = character()) {
structure(
list(
uid = invoke(jobj, "uid"),
type = jobj_info(jobj)$class,
param_map = ml_get_param_map(jobj),
...,
.jobj = jobj
),
class = c(class, "ml_evaluator")
)
}
#' @export
spark_jobj.ml_evaluator <- func... |
74ba38971fb285a3821e6f9c24a628250536b885 | c5de5d072f5099e7f13b94bf2c81975582788459 | /R Extension/RMG/Energy/Trading/PortfolioAnalysis/readPriceVolChangesCVSSAS.r | 5adcb5d439aeb3513fb2c6d9edeac4e675c8514e | [] | no_license | uhasan1/QLExtension-backup | e125ad6e3f20451dfa593284507c493a6fd66bb8 | 2bea9262841b07c2fb3c3495395e66e66a092035 | refs/heads/master | 2020-05-31T06:08:40.523979 | 2015-03-16T03:09:28 | 2015-03-16T03:09:28 | 190,136,053 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,759 | r | readPriceVolChangesCVSSAS.r |
readPriceVolChangesCVSSAS <- function(Portfolio, Date)
{
# browser()
options$SASdir <- "S:/Risk/Projects/SAS/DATASTORE/SASIVaRProcm/"
fileList <- list.files(options$SASdir)
fileCorePortfolio <- paste(strsplit(toupper(Portfolio)," ")[[1]], sep = "", collapse = "-")
indPortfolio <- grep(fileCorePortfolio, fileL... |
b13ec958f0ac377aea7be0228375bd5745b9b73e | d9ff3460cd82506ab94c72645e9ef5c9ddfa05b1 | /dplyr mtcars.R | d18cae2fa33b7a88e7a8716db465b616b78abab7 | [] | no_license | inso2501/analytics1 | 650942ef37725e4c6adb74840e0d9884bc9ce8b7 | 1a2c8f8d7179ac90ed7c3433460133b238c33be9 | refs/heads/master | 2020-04-02T16:33:28.467316 | 2018-10-27T12:47:00 | 2018-10-27T12:47:00 | 154,617,752 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,710 | r | dplyr mtcars.R | #analysis of dataset mtcars using mtcars
library(dplyr)
?mtcars
mtcars%>%summarise(mean(cyl))
mtcars%>%group_by(gear)%>%summarise(mean(am),mean(drat))
mtcars
#structure of a data frame
str(mtcars)
dim(mtcars)#dimensions
names(mtcars)#column names
rownames(mtcars)#rownames
summary(mtcars)
#summary activities on mtcar... |
24e969c26055a577ae8403ad97ded369e216954e | fb65f86a18adc1dc19b5cfe484c73a6c2a3cb05a | /scripts/brahman_angus_bionano_corrected_cut.R | 9f61c589940a7865e405e75ad989f9c60e7b0a0c | [] | no_license | njdbickhart/BrahmanAngusAssemblyScripts | a27dcd3a570bf99413a83b8888440cadca186083 | c42cb5cc347a6436f35fb8d36557ab4aeb158c9a | refs/heads/master | 2020-05-18T08:47:58.873884 | 2019-08-07T21:35:57 | 2019-08-07T21:35:57 | 184,305,807 | 0 | 0 | null | 2019-08-07T21:25:20 | 2019-04-30T17:41:16 | R | UTF-8 | R | false | false | 94 | r | brahman_angus_bionano_corrected_cut.R | /Users/lloyd/Documents/lloyd_2017/Research/Brahman_Angus/brahman_angus_bionano_corrected_cut.R |
3210345526ad93c6f38bb0872443641b08985112 | 21702fd53af97efd67f3ea5ff4073bf3a376cb02 | /R/dendro_rpart.R | f1bb198194aa8a73b316031ea1a2cc909fab3bb6 | [] | no_license | andrie/ggdendro | 80af9c3973c8c5a2cab4ea970372d50d78885cd8 | b75c06e11698a5deda638adc556f0e263b38d5a7 | refs/heads/main | 2023-07-22T08:02:29.906864 | 2022-02-15T15:56:37 | 2022-02-15T15:56:37 | 2,166,358 | 57 | 11 | null | 2023-07-06T06:40:16 | 2011-08-06T20:35:39 | R | UTF-8 | R | false | false | 5,723 | r | dendro_rpart.R | #
# ggdendro/R/dendro_rpart.R by Andrie de Vries Copyright (C) 2011-2015
#
# 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; either version 2 or 3 of the License
# (at your option).
#
# Thi... |
bcc12fce2f2ed5baab902d174f2ebda8084f6bd4 | 014d46dfeac6175fbfc679e8edbac142f217d48e | /R/inflate.R | a8b212d417162b5771e28f56aaea3164829547e5 | [] | no_license | chengvt/cheng | 52707263a256f8923321b16811b3dd8ec15aaf6b | aba26d0772a1fd543899078071579a827aab318b | refs/heads/master | 2020-05-30T07:19:05.633286 | 2017-11-02T03:21:42 | 2017-11-02T03:21:42 | 56,038,451 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 496 | r | inflate.R | #' @export
inflate <- function(x, n){
if (is.matrix(x)) {
y <- apply(x, 2, function(x) rep(x, each = n))
} else if (is.data.frame(x)) {
y <- as.data.frame(apply(x, 2, function(x) rep(x, each = n)), stringsAsFactors = FALSE)
# copy class if different
if (!isTRUE(base::all... |
f691768ed6e0a04aefb5b69d718547b5f69d8fa6 | 0c345da92198de35ae5e5ff0658185bb5fb3f93e | /code/data_cleaning.R | 285956ec4f03ea5ac876e4b414a6cb9778adae25 | [] | no_license | gdicecco/community-turnover | 67775a89af1691845d44e811269dc984cb333186 | b8dc562f9d5a250899a174907be7ca35516dfc8c | refs/heads/master | 2021-11-11T08:25:16.617962 | 2021-10-29T16:54:51 | 2021-10-29T16:54:51 | 240,097,811 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 7,173 | r | data_cleaning.R | ### Subset BBS data for community trajectory analysis
library(tidyverse)
library(purrr)
library(spdep)
library(tmap)
library(sf)
library(vegclust)
library(ecospat)
### Read in data #####
## NA map
na <- world %>%
filter(continent == "North America")
## BBS 2017 Version
# Append correct BioArk path
info <- sessi... |
87100a553e234dd92043f589545c8da7d83225a3 | 7917fc0a7108a994bf39359385fb5728d189c182 | /cran/paws.management/man/ssm_list_tags_for_resource.Rd | f66a18cb3f82aa639bff2a2106e6f5ea7bb512ce | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | TWarczak/paws | b59300a5c41e374542a80aba223f84e1e2538bec | e70532e3e245286452e97e3286b5decce5c4eb90 | refs/heads/main | 2023-07-06T21:51:31.572720 | 2021-08-06T02:08:53 | 2021-08-06T02:08:53 | 396,131,582 | 1 | 0 | NOASSERTION | 2021-08-14T21:11:04 | 2021-08-14T21:11:04 | null | UTF-8 | R | false | true | 937 | rd | ssm_list_tags_for_resource.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ssm_operations.R
\name{ssm_list_tags_for_resource}
\alias{ssm_list_tags_for_resource}
\title{Returns a list of the tags assigned to the specified resource}
\usage{
ssm_list_tags_for_resource(ResourceType, ResourceId)
}
\arguments{
\item{Resou... |
f6bc27242568cd5ebe9170a44b33de38e7634e72 | fda10c36d5d27cf550b61d757c92a5c013974f3b | /man/expand.Rd | 2b7e5e234c59f81717bc6e1841ad36e334a72b84 | [] | no_license | gobbios/cfp | 9e5da1cbfe0c7185f5c772e11c107cb3407d2051 | 4402e7b9e776915156b22da921bd993d445c8049 | refs/heads/master | 2022-05-07T11:23:22.510689 | 2022-04-01T09:18:58 | 2022-04-01T09:18:58 | 95,994,424 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,416 | rd | expand.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/expand.R
\name{expand}
\alias{expand}
\title{expand grid with numerical component}
\usage{
expand(formula, data, res, ...)
}
\arguments{
\item{formula}{a formula}
\item{data}{the data set}
\item{res}{numerical, the resolution for the numeri... |
9ab985603e7e59ef97bc31e0574ac201cfdf33bb | e3dcccd67844008ca512f3823551a746f548e0a1 | /DistritosLima.R | c69858435e196b72e0f38cef505c0753d178c844 | [] | no_license | WilderBuleje/hello-world | 4e7c348d1b97684c6774dc539d77a0f227cf43b9 | bf0a9e5c93f50e925eda2434cc591861aaa16f8c | refs/heads/master | 2021-07-09T09:53:42.241363 | 2020-08-08T07:32:14 | 2020-08-08T07:32:14 | 176,326,335 | 0 | 0 | null | null | null | null | ISO-8859-10 | R | false | false | 983,487 | r | DistritosLima.R | structure(list(IDDPTO = c("15", "15", "15", "15", "15", "15",
"15", "15", "07", "15", "15", "15", "15", "15", "15", "15", "15",
"15", "15", "15", "15", "07", "15", "15", "15", "15", "15", "15",
"15", "15", "07", "15", "15", "15", "07", "15", "15", "15", "15",
"15", "15", "07", "15", "15", "15", "15", "15", "07"... |
84e7b50d46e88a744a795243c2acd75ad51bc25c | 736bb5577b2904128e0433e9d6a6138667da1a9d | /man/ExposureCurvePareto.Rd | 168c2458b13f8f454dddb157b5d27330852e13b4 | [] | no_license | cran/NetSimR | 9bf3d549d67e2f40300d246b5937f29e3e7c34a1 | 1500e8d308b999db4dc3d58a94392eaad00e8e9f | refs/heads/master | 2023-01-20T06:30:10.070555 | 2023-01-17T22:10:02 | 2023-01-17T22:10:02 | 236,631,499 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 890 | rd | ExposureCurvePareto.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Pareto.R
\name{ExposureCurvePareto}
\alias{ExposureCurvePareto}
\title{Exposure Curve from a Pareto severity distribution}
\usage{
ExposureCurvePareto(x, scale, shape)
}
\arguments{
\item{x}{A positive real number - the claim amount... |
dd29f916ecefd16ab841e45661df65a2746c7867 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/rdhs/examples/dhs_countries.Rd.R | 1e2ad34ea9619b5b573725d5a56f394c95afccd1 | [] | 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 | 1,525 | r | dhs_countries.Rd.R | library(rdhs)
### Name: dhs_countries
### Title: API request of DHS Countries
### Aliases: dhs_countries
### ** Examples
## Not run:
##D # A common use for the countries API endpoint is to query which countries
##D # ask questions about a given topic. For example to find all countries that
##D # record data on ma... |
0ea313814822986818e60c77a6a00ad642531466 | 375db54c7e15f903e9757bd592f1c9564b0ef992 | /app.R | 3d1738b5cf78f4f20f58ed9a0d81fb8e37993f06 | [] | no_license | csun28/Animated-Charts-Dashboard | 6f96d6e6c4ed868f14b945d35abf7b3d54f40a57 | 233de5ed91ede3548207c8fc8d225e8b09aa5dc1 | refs/heads/main | 2023-01-04T19:31:51.664004 | 2020-10-13T11:46:08 | 2020-10-13T11:46:08 | 303,667,255 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 13,850 | r | app.R | #import libraries
library(shiny)
library(shinydashboard)
library(gganimate)
library(ggplot2)
library(stringr)
library(gifski)
#import RScripts for cleaning and recoding data
source("newdash.R")
linebreaks <- function(n){HTML(strrep(br(), n))}
#define UI for application
ui <- fluidPage(
#define title and inputs... |
2427f477581d092736d27bf63538fa987fb5448d | b0f8f5a5ec5a7a251735a2bbdee2ce594c53d194 | /UBI/Baby Mama Money - Project.R | db642bc461997728f65f9a82a422cdaf87400b82 | [] | no_license | Thirdhuman/Child-Tax-Credit | 29c831dd979ecc11d7f75f639e3e4528231d0e8c | 25c997d31fb73722a9a52c34d0317fa301caa585 | refs/heads/master | 2020-04-21T13:49:47.337742 | 2019-02-07T17:35:44 | 2019-02-07T17:35:44 | 169,613,412 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,472 | r | Baby Mama Money - Project.R | # name the database files in the "MonetDB" folder of the current working directory
dbfolder <- paste0( getwd() , "/MonetDB" )
#######################################
# survey design for replicate weights #
#######################################
# create survey design object with CPS design information
# using exist... |
479996468d9cc1cbcc6cefb216f445a4cfb8bbdc | b6fa0556a60996953cac111a598435e03da045b2 | /man/create_entity_all.Rd | 9e291615a91a64ea0d060ca2f23fc1d90a8972e1 | [] | no_license | BLE-LTER/MetaEgress | e4f509d608db8d3ba0127bc6d5e3abc2da364330 | 368b710442f1b3978de48411a743a23d4dca6a58 | refs/heads/main | 2023-06-23T05:59:20.330729 | 2023-06-12T18:14:33 | 2023-06-12T18:14:33 | 175,042,133 | 5 | 4 | null | 2023-06-01T23:13:12 | 2019-03-11T16:37:27 | PLpgSQL | UTF-8 | R | false | true | 1,572 | rd | create_entity_all.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create_entity_all.R
\name{create_entity_all}
\alias{create_entity_all}
\title{Quickly create all EML entity list objects.}
\usage{
create_entity_all(
meta_list,
file_dir = getwd(),
dataset_id,
entity_numbers = NULL,
skip_checks = FA... |
f49ac2bdee7414e9a7bb373e1d283526d355be3f | 29585dff702209dd446c0ab52ceea046c58e384e | /LogicOpt/R/logicopt.R | 5ce82c07f784b2feab4438ddf95fe71c298e611e | [] | 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 | 22,797 | r | logicopt.R | 'logicopt' <- function(in_tt=NULL,
n_in=0,
n_out=0,
find_dc=FALSE,
input_sizes=NULL,
exact_cover=TRUE,
esp_file="",
mode="espresso")
##########################... |
354ee7f39dc185a6c96121d55fb9e7e05e9a8182 | d060fad3c33325ba3e6ab2e42ac9df2ff2a5abf0 | /man/check.ordered.to.pa.Rd | 32948afcb92a6b6d523ec83c2cc38b6b6b9ccaff | [] | no_license | cran/bnpa | 0eb35f0d18850e4b3556c7b08c469e04aab97538 | 3f27ca031b7f6fbf30264d8582970f505f8b76ea | refs/heads/master | 2021-01-11T21:51:55.114628 | 2019-08-01T22:20:02 | 2019-08-01T22:20:02 | 78,866,497 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,617 | rd | check.ordered.to.pa.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/check.ordered.to.pa.R
\name{check.ordered.to.pa}
\alias{check.ordered.to.pa}
\title{Verifies if there are ordered factor variables to be declared in the pa model building process}
\usage{
check.ordered.to.pa(bn.structure, data.to.work)
}
\arg... |
5f13724c0bc3fa2b239c0b5c3e046e40db6f64d3 | 647f0aecb1b9d250ac6d5f1bf53a472e4ab050b7 | /2021/week27/rscript.R | d6ee32c9c805670954612ee65fb3dd934debff31 | [] | no_license | kayleahaynes/TidyTuesday | fba1d9cf034f6e854b6f2b590ca9e3a66b75c2b5 | 153196c31ed0f7c629b9658788e58bfddb3c6bac | refs/heads/master | 2023-07-19T02:48:43.375561 | 2021-09-09T22:16:12 | 2021-09-09T22:16:12 | 290,191,442 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,336 | r | rscript.R |
# set up -----------------------------------------------------------------
library(tidyverse)
library(lubridate)
library(extrafont)
loadfonts()
# load data --------------------------------------------------------------
tuesdata <- tidytuesdayR::tt_load(2021, week = 27)
df_data_raw <- tuesdata$animal_rescues
gli... |
b5081d9b7b3ad59cccfeda8dc1b18a73d4a3d9a3 | 18ba9ff84fc08d91bf675e86d3a596ffe777da93 | /src/assignments/spa1/code/crypta2.R | 908c32ce5e40d99bf628b28d492b015f72ae1d3a | [] | no_license | supersubscript/compbio | 0656e2da1ac77d845b87da9ff026a022443b166b | e705b317078ea3cb3582ef80ddd71d5072a22965 | refs/heads/master | 2021-01-17T18:45:56.893352 | 2019-08-01T16:26:33 | 2019-08-01T16:26:33 | 80,166,886 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,124 | r | crypta2.R | ### Returns possible permutations of input
permutations <- function(n) {
if (n == 1)
{
return(matrix(1))
} else
{
sp <- permutations(n - 1)
p <- nrow(sp)
A <- matrix(nrow = n * p, ncol = n)
for (i in 1:n)
{
A[(i - 1) * p + 1:p, ] <- cbind(i, sp + (sp >= i))
... |
46fa349f21c06ab4b5b6673e1487801a42bdfa73 | 039881b907d13512a8e5ca551aba51a739aa7a7e | /R/tm1_run_chore.R | ddaa16a62d228a2aca956fc82622b3817b18a334 | [] | no_license | catgopal/tm1r | 0276bc7df03f0071addcaa09ec5820772f7b0905 | 679b5a556b8ab3e7b4befa238372d0e16a8707ca | refs/heads/master | 2021-09-28T14:06:26.750075 | 2018-11-17T21:33:55 | 2018-11-17T21:33:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,462 | r | tm1_run_chore.R | tm1_run_chore <- function(tm1_connection, chore = "") {
tm1_adminhost <- tm1_connection$adminhost
tm1_httpport <- tm1_connection$port
tm1_auth_key <- tm1_connection$key
tm1_ssl <- tm1_connection$ssl
# added because some http does not know space
chore <- gsub(" ", "%20", chore, fixed=TRUE)
u1 ... |
b1ea4ba8cbebc97ba4a18abcb3be727be3b96b48 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.database/man/neptune_describe_db_clusters.Rd | efcbd991086e6ff3fc2dc2cafd66daef4cbcf131 | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 2,074 | rd | neptune_describe_db_clusters.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/neptune_operations.R
\name{neptune_describe_db_clusters}
\alias{neptune_describe_db_clusters}
\title{Returns information about provisioned DB clusters, and supports
pagination}
\usage{
neptune_describe_db_clusters(
DBClusterIdentifier = NUL... |
c5a00b3bb1e312f316f21ee061d8307978cdfcfe | 438de5ce19f43e5b0f4a3fa92ec30008a851a821 | /mainClusterKMLparameter.R | eb636caa30619d507b6a86d03ba7d4773805ade0 | [] | no_license | hsuanyuchen1/kml2Polygon | f19d2c6c7856737f8a2906c02df76be6e18ebb9e | 227e8ffffe080d1436484eb1d7e6ee103f8d9531 | refs/heads/master | 2022-09-20T00:37:14.506768 | 2020-06-01T14:18:19 | 2020-06-01T14:18:19 | 268,542,119 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,278 | r | mainClusterKMLparameter.R | library(sf)
#library(tmap)
library(rgdal)
library(dplyr)
library(xml2)
library(XML)
library(fpc)
source("D:/Test/clusterKml2Polygon/readKML.r")
# tfile <- list.files(zipfileDir, full.names = T, recursive = T, pattern = "zip")
# tfile <- tfile[!grepl("TAB", tfile)]
#tFileName <- tfile[1]
kml2Tab = fun... |
f674a8903bdb419143ad0c9211fc4af00f423e42 | e87be52c1dfa0d799d7756dc27dc7ae9344bc570 | /R/set_age_comp.R | eef5cab7c8591caa85f2a4749cef32e1426053bb | [] | no_license | MatthVeron/wham | 99b96f27bb2f55082e66b048ebc24b42c0c71bd5 | 0c53be0043ec67963b1ae1b1519ac5004a68b8b2 | refs/heads/master | 2023-09-05T10:28:13.132709 | 2021-08-25T14:21:50 | 2021-08-25T14:21:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,018 | r | set_age_comp.R | set_age_comp = function(input, age_comp)
{
data = input$data
par = input$par
if(is.null(age_comp)){
data$age_comp_model_fleets = rep(1, data$n_fleets) # multinomial by default
data$age_comp_model_indices = rep(1, data$n_indices) # multinomial by default
} else {
if(is.character(age_comp)){ # all use t... |
0ff733a65efe6ea580909494bf8fbfb854684163 | 0a4c7468bee7c14a31282f0dc3b4e005506ffc99 | /R/drawdown.R | d8bf72422da35ecd392bd2089a2f0ee3e431d887 | [
"Apache-2.0"
] | permissive | cestob/backtestGraphics | 0bb6fd1208be4ea0d79504a5465aec93a6de43df | 27eda364121a69b74e68798a9fc48f97e6f5f4f8 | refs/heads/master | 2020-03-18T06:17:47.197107 | 2018-03-20T02:23:57 | 2018-03-20T02:23:57 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,646 | r | drawdown.R | #' The Three Biggest Drawdowns in the portfolio
#'
#' Show the top 3 drawdowns including start and end dates, as well as
#' decrease in returns during the drawdown period. All the information will be
#' returned in a table, with all the numbers properly formatted.
#'
#' If the data set is not big enough that there are... |
e9bc012a1538f7c1a0c5b60a7e8058a9a9754058 | a07b28cb54fd41d3102058cefbfe90a4f1e51aaa | /R01/demography merge.R | be6dd8684886f9e89a55c859b7d42796b2de92f9 | [] | no_license | amyrobyn/LaBeaud_Lab | ed1d05fa2dc1c1df412a106519b69dd79168d978 | fab5c867027a07409006a1f0ed9b80e39db8357c | refs/heads/master | 2021-06-05T20:31:30.379779 | 2021-04-30T18:56:59 | 2021-04-30T18:56:59 | 64,692,795 | 5 | 1 | null | 2017-05-03T05:19:28 | 2016-08-01T18:47:38 | Stata | WINDOWS-1252 | R | false | false | 941 | r | demography merge.R | setwd("C:/Users/amykr/Box Sync/Amy Krystosik's Files/Data Managment/redcap/ro1 lab results long")
demo<-read.csv("R01CHIKVDENVProject_DATA_2017-08-17_1647_demo_merge.csv")
demo_wide<-reshape(demo, direction = "wide", idvar = "ï..person_id", timevar = "redcap_event_name", sep = "_")
demo_wide$gender_equal <- ifelse(demo... |
5674391c2821058bfec5424e621a7a02bc9a69af | a2efed9656dacad11c14628210ceac169e7fe760 | /prueba_Simula_Likert.R | 7d27fd8097c67371546961f6dbb6281fb2665809 | [] | no_license | LafArt/R-util-functions | 01ac9ec64159a60fad5c28a26482400c9daf2547 | 54bf13fc7ecc03ab9f75ee9f62a49a01a73b4fa2 | refs/heads/master | 2020-04-12T21:35:58.695608 | 2019-12-20T21:17:59 | 2019-12-20T21:17:59 | 162,766,058 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,752 | r | prueba_Simula_Likert.R | library(ggplot2)
library(tidyverse)
source("C:/wmd/R-util-functions/Simula_Likert.R")
num_de_items=20
num_de_items2=16
escala_interpretada_1 = c("Muy malo","Malo","Regular","Bueno","Muy bueno")
escala_interpretada_2 = c("Muy baja","Baja","Media","Alta","Muy Alta")
entorno_familiar<-Simula_Likert(escala=1:5,
... |
edcb32a2719f61115e0bdc5b9e127929f3116ec1 | 8be2b600bfee9003095625af795a5a7ab82eec83 | /R/rpivotAddin.R | e93c8dd151bd5b260097e92972f36f586b11813e | [
"MIT"
] | permissive | dkilfoyle/rpivotTable | 85940d48f245d4a5b531b6d76d167d64a66fcbdf | af03e853c822b2bf1c87b49c769f3f111f7dce50 | refs/heads/master | 2021-01-15T08:26:56.407627 | 2016-06-11T05:36:44 | 2016-06-11T05:36:44 | 44,932,678 | 0 | 0 | null | 2015-10-25T22:20:07 | 2015-10-25T22:20:06 | null | UTF-8 | R | false | false | 1,214 | r | rpivotAddin.R | getDataFrames = function()
{
if ((length(ls()) == 0) | (length(sapply(.GlobalEnv, is.data.frame)) == 0) | (any(sapply(.GlobalEnv, is.data.frame))==F))
data(iris)
return(names(which(sapply(.GlobalEnv, is.data.frame))))
}
rpivotAddin <- function() {
library(shiny)
library(rpivotTable)
library(miniUI)
lib... |
be07901b7df8bd58f660ff89ff2bbce653023cc6 | cd3967de736915699aed09431176d4ce7596b64d | /R/usa-map-prep.R | d241e14c01aa3d7ba6b555494783b87a78bc3109 | [] | no_license | mozzarellaV8/ATF-FFL | c3b4a9e2a03f3b5a8f5342bb3d5a6ff4f5e40dfe | 831e48f887b58e5f9d4f506e1c5402f9ea810b8d | refs/heads/master | 2021-01-11T22:35:15.738291 | 2017-12-29T00:52:15 | 2017-12-29T00:52:15 | 78,992,723 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,337 | r | usa-map-prep.R | # ATF-FFL - United States Map Prep
library(maps)
library(mapproj)
library(maptools)
library(sp)
library(fiftystater)
library(dplyr)
library(ggplot2)
# Function: Capwords ----------------------------------------------------------
# from tolower() documentation
capwords <- function(s, strict = FALSE) {
cap <- functi... |
5dc106dc450421aab4fec820387ac54a9bf512fe | 1073de16d38ca0979422a5e617a077864c2293e0 | /cachematrix.R | 743117f606db0165bb986c1cada9366663a0700d | [] | no_license | jgooding/ProgrammingAssignment2 | 0da2d9c5ed262a7ef83c836f2ee5cc358c49733d | dd1ef436fda85f45d7596b1812bae3e7f2c45486 | refs/heads/master | 2021-01-15T17:02:37.664626 | 2015-03-18T08:36:25 | 2015-03-18T08:36:25 | 32,382,275 | 0 | 0 | null | 2015-03-17T09:02:31 | 2015-03-17T09:02:31 | null | UTF-8 | R | false | false | 2,796 | r | cachematrix.R | ## makeCacheMatrix: Returns a list of functions that:
## Set the value of the matrix
## Get the value of the matrix
## Set the value of the matrix inverse
## Get the value of the matrix inverse
makeCacheMatrix <- function(x = matrix()) {
## object to store the cached inverse and set to null
store_inv <- NULL
## ... |
443e4465819be854f0af5f1c02a49b77276bb961 | f6c2bd59af6d11252a05c1b6f86e3621a51f115f | /getEPC.R | 44129550cd830c3dbf87dd49d87b9ae38f5c293e | [] | no_license | borgo-larici/ExData_Plotting1 | 8d3aa7a16ee475da6370f7544ed79459cc5f272f | 7d865aae42ed00403a0c065680841a47d1d6db63 | refs/heads/master | 2021-05-22T19:30:29.924625 | 2020-04-04T21:28:53 | 2020-04-04T21:28:53 | 253,058,740 | 0 | 0 | null | 2020-04-04T17:28:42 | 2020-04-04T17:28:42 | null | UTF-8 | R | false | false | 2,136 | r | getEPC.R | # Function "getEPC"
# Used for Course Project 1 in "Exploratory Data Analysis".
# Checks if object "epc" exists already.
# If "epc" does not exist, downloads data from
# https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip
# to working directory. Then unzips and
# reads specific row... |
c22dcb3c7fc7afaa4189fe49165cf7fd9d233033 | 12b0aa3c8c9b600253a3850f9b0a0466402f30e1 | /R/matchTreeTaxa.R | 9cb9a49bbd0a0843e2da32ac5c83a9f4f9469b27 | [] | no_license | bbanbury/phyloextra | 561ef779c459fc08bcb087069e6977aafd9a6440 | ebebead690e4317be84d9d7165a2d801951c7c55 | refs/heads/master | 2021-01-10T20:50:51.583643 | 2014-11-25T19:36:26 | 2014-11-25T19:36:26 | 5,588,766 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,691 | r | matchTreeTaxa.R | #' Check taxa match in two trees
#'
#' This function will check that taxonomic names in two trees match and if they do not, it will write the pruned trees to file.
#' @param phy1 A phylogenetic tree in the class "phylo"
#' @param phy2 A phylogenetic tree in the class "phylo"
#' @param toFile If TRUE, it will save pr... |
2ba653c217bea93a48edd1bb8ca83eab53388e2c | 59ab02a8f44717477aa134553a5e141e514ece80 | /man/print.facet_trelliscope.Rd | a998ee1cb0bd942417ff1a01a36b9344bf5174a1 | [] | no_license | timelyportfolio/trelliscopejs | 920a3b10d32b23753b881d744543975ddc9017ec | 25b92ae28674d915a327e61178e96c954320093b | refs/heads/master | 2022-08-19T03:12:50.171585 | 2016-11-19T21:38:23 | 2016-11-19T21:38:23 | 74,371,885 | 1 | 0 | null | 2016-11-21T14:29:42 | 2016-11-21T14:29:41 | null | UTF-8 | R | false | true | 357 | rd | print.facet_trelliscope.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/facet_trelliscope.R
\name{print.facet_trelliscope}
\alias{print.facet_trelliscope}
\title{Print facet trelliscope object}
\usage{
\method{print}{facet_trelliscope}(x, ...)
}
\arguments{
\item{x}{plot object}
\item{...}{ignored}
}
\descriptio... |
161e27973244ef81b8e36c9966460dfaca5d338f | 17dc451c33b8726441d03b1d604d7e6ed4a984b8 | /R/SShDFunc.R | 32549e2ec2476bf253970769bb41e7ddfb3dcfe9 | [] | no_license | TWilliamBell/angler | ad8d57bb3b902a0e87b20b9b3f8e2844c7cefd1d | ffa59d8aa92e256b673423c5572c3136ae37e53f | refs/heads/master | 2022-03-12T16:29:48.936809 | 2022-03-03T17:00:11 | 2022-03-03T17:00:11 | 140,886,555 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,360 | r | SShDFunc.R | #' Calculating Sexual Shape Dimorphism
#'
#' This function directly calculates SShD. However it may be a poor estimator for unbalanced designs where there are more of one sex than the other, SShDLM() is more robust.
#' @param Coords Two-dimensional array of coordinates from geometric morphometric analysis (see two.d.a... |
d4ac3bf240971548fbcfb3099d38b2e4a312a918 | 68d2cafca07e71ba36b9456acbf05ab4bed18a01 | /examples/tests.r | 41535b6e304bb23259d62ad1566c1bf387a11b68 | [] | no_license | skyformat99/msgpack2R | 9dd7b32c05e69ccd9c36cec6cc4eaad5f8ff6158 | 22d230a9be3ff523fd9b2011719a8071ee50d288 | refs/heads/master | 2021-01-22T01:47:34.342552 | 2017-09-03T00:42:34 | 2017-09-03T00:42:34 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,074 | r | tests.r | # Tests for testing out the functionality of the package, to make sure it isn't broken
# some references
# //https://github.com/msgpack/msgpack-c/blob/401460b7d99e51adc06194ceb458934b359d2139/include/msgpack/v1/adaptor/boost/msgpack_variant.hpp
# //https://stackoverflow.com/questions/44725299/messagepack-c-how-t... |
e1853531eab5b5112e4c7bfdf85f567977348bc9 | d92a85932e42ecc7935386450a65a6f9a551860a | /as3_v3.R | a604197427363476ef794674cd399239d69f26b7 | [] | no_license | rachelphillip/4113-assignment-3 | ccd0137983dad7ef2b169394b2cf0682d2e43fef | 943917b5d9a77e8b901f43c5df3b6af46c2d7a9f | refs/heads/master | 2021-08-26T06:42:11.699366 | 2017-11-21T23:42:13 | 2017-11-21T23:42:13 | 109,023,324 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 26,131 | r | as3_v3.R | # I confirm that the attached work is my own, except where clearly indicated in the text.
###############################################
#CONFIDENCE INTERVALS &
#COVERAGE FNS
##############################################
b.ests.np <- function(B = 99, data,
h = sd(data)/3, method) {
#Purpose... |
31dfc0bed04a1040e69a48e4c7ab36fa0126d6cd | 637de7478cf00a32de1c1d07f25f75830cc0f00e | /07_Youth, technology, and social media/survey.r | 2595a820f10e88fb7ab275cf3f3aca6960d161b3 | [] | no_license | ajasprica/Data-Science | ac135b8bd5f191d071879a64a807a13fe0408af6 | 9b1d4c8a10362845ec660ed1769eec7c8e660915 | refs/heads/master | 2021-01-17T15:24:35.144554 | 2016-05-25T04:58:07 | 2016-05-25T04:58:07 | 50,744,452 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 167 | r | survey.r | survey <- read.delim("D:/Data-Science/09_Youth, technology, and social media/Raw survey responses.txt", header = TRUE, stringsAsFactors = FALSE)
dim(survey)
#580 1599 |
0f3169ac5e3612db6a9369c3e987853d2da6d2f9 | 137b6fa5752a5076a74a22533de3e54f8b902544 | /man/readAbundanceFile.Rd | 604957ce5f0e1179ca6c7d30218d4c993c626ae9 | [
"MIT"
] | permissive | nickilott/micRowave | a317a3074c15772a64c19ba5ff98a69f3958efaf | d198ecaa5e73f3353c5fe2d0a6a4bcb1fb241f98 | refs/heads/master | 2020-04-15T21:17:38.359780 | 2019-04-26T08:42:58 | 2019-04-26T08:42:58 | 165,027,566 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 421 | rd | readAbundanceFile.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/micRowave.R
\name{readAbundanceFile}
\alias{readAbundanceFile}
\title{Read in an abundance file}
\usage{
readAbundanceFile(abundanceFile)
}
\arguments{
\item{abundanceFile}{.tsv file with first column as feature. Columns are samples}
}
\value... |
7ecd38ed528262482230485c1ba1db123fd9e369 | e27d8d12ec978a1e1a81ad173bb9d012303a97f5 | /analyses/alpha-diversity/combined_alpha_mayjulyonly.R | 7b9c1aef4f4f9fc5424c1ab39370318761ade68b | [] | no_license | baumlab/McDevittIrwin_etal_2019_CoralReefs | 18a9f8b6cd9b19bb1e477bc45836f4bd769828d8 | 6c8edf736912626e3d363397027736d41046ecde | refs/heads/master | 2020-04-07T18:11:36.580668 | 2019-02-11T22:04:17 | 2019-02-11T22:04:17 | 158,600,746 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,961 | r | combined_alpha_mayjulyonly.R | # Combine alpha plots MS
setwd("/Users/jamiemcdevitt-irwin/Documents/Git_Repos/McDevittIrwinetal_Kiritimati16S")
getwd()
library("ggplot2")
# clear my environment
rm(list=ls())
theme_set(theme_bw())
# load the data
# May Alpha
load("data/secondmito/lowreads_pruned/may_coral_alphamodel_combined.Rdata")
# July Alp... |
4e56ccb5da4002e55961196b75bd5480ff23d0bd | 51ef9fa1b2212c659152fac242bda47e7bf15d6a | /man/is_date.Rd | e8c369bf628d57090e684430c1b9fd328019b642 | [] | no_license | cran/rnbp | dc5771835c012e6872cc1a7128ad017234db0dad | 7ccc244007541379fc729d5ab869bd329ef06280 | refs/heads/master | 2021-06-25T03:25:57.463674 | 2021-06-07T06:30:02 | 2021-06-07T06:30:02 | 199,285,520 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 375 | rd | is_date.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils_testers.R
\name{is_date}
\alias{is_date}
\title{Checks if an object is a date object.}
\usage{
is_date(x)
}
\arguments{
\item{x}{object to be tested.}
}
\value{
TRUE or FALSE depending on whether its
arguments is a date object or not.
}... |
6d689a3bc86501b9b6eda1aa7c1fc234b5483e24 | d03e45ed3bbe167143c6919120cb30a7361c1645 | /tests/testthat/test-conversion.R | a960cf6988e6d577e4355b2abbcf984790661a47 | [
"MIT"
] | permissive | thomasp85/farver | 5a56d7937a295b1b10ef756f4f589e02e8001c1f | 9bc85a6fd839dc6d2d919c772feee40740afe53d | refs/heads/main | 2022-11-13T13:24:58.345474 | 2022-07-06T17:48:32 | 2022-07-06T17:48:32 | 125,286,884 | 106 | 13 | NOASSERTION | 2022-09-20T06:00:02 | 2018-03-14T23:32:11 | R | UTF-8 | R | false | false | 1,397 | r | test-conversion.R | context("conversion")
spectrum <- unname(t(col2rgb(rainbow(10))))
reconvert <- function(data, space) {
unname(round(convert_colour(convert_colour(data, 'rgb', space), space, 'rgb')))
}
test_that("basic io works", {
expect_error(convert_colour(spectrum, 'test', 'lab'))
expect_error(convert_colour(spectrum, 'rgb',... |
d351e490a5775281086020eddd5a60346c095cae | 61f8337d2206f5ef458e25cfd88d74adfd492afc | /src/capitalhumano.R | c382c0303bae39aba8a7b634b0661e460d43b033 | [] | no_license | maorjuela73/AnalisisMediosDeVida | 29a406d7228e605621d9862e113636ed77d32021 | 73419e877b2460cfeeb32c9bd96a55702535eab3 | refs/heads/master | 2023-01-31T16:53:34.709403 | 2020-12-17T20:41:27 | 2020-12-17T20:41:27 | 322,356,879 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,721 | r | capitalhumano.R |
# Nivel educativo de los integrantes del hogar ----------------------------
capitalHumano <- function(df_hogares, df_personas){
# Por personas
educacion <- df_personas %>% select(
c(
CONSECUTIVO:A00,
starts_with("p1708")
)
) %>%
mutate(
p1708 = replace_na(p1708, 1),
p1708 = facto... |
a0d6159cb7bd78fc9a4d208417e16b9e6ec6b936 | 2a1841b7ecb2c5da4f48233eb2c7fee8ea052d60 | /src/makeNetwork.R | 48fd13315f70e85bbc88836936571f2302e63e77 | [] | no_license | mosaic-tools/nhd_net | 7277660586e991651b9b4e8498d5878bd6773cdd | 0e46e757b5c26ccf5e8cbdc115cf28a50b143131 | refs/heads/master | 2020-08-27T08:45:14.447903 | 2019-10-24T14:42:56 | 2019-10-24T14:42:56 | 217,304,885 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,730 | r | makeNetwork.R |
library(nhdplusTools)
library(tidyverse)
library(dplyr)
library(magrittr)
#to download full nhdplusV2 on my computer
nhdplus_path("D:/projects/TSS/data/NHDPlusNationalData/NHDPlusV21_National_Seamless_Flattened_Lower48.gdb")
nhd_paths <- stage_national_data()
network <- readRDS(nhd_paths$flowline)
#to download nhd... |
ab1356098e1f31f75817637eabe03d5f7f805727 | e3fe809b3ac97515af6acd231e7382c88ea40f14 | /R/summary.R | f184d6ae3cf78d7674dfa90d8ffe165cfa29caf8 | [] | no_license | kkondo1981/l0araxx | 6c8c4c71930ba273e816380d8e37dfb6638acecd | 8e672fbb1c17942dcd39ecb4ab109f2e15c746bd | refs/heads/master | 2020-03-27T19:10:07.386224 | 2018-08-27T22:51:41 | 2018-08-27T22:51:41 | 146,969,463 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,795 | r | summary.R |
predict.l0araxx <- function(obj, newx, type=c("link", "response", "coefficients", "class"), offset=NULL, ...) {
np = dim(newx)
type <- match.arg(type)
# check offset
if (is.null(offset)) {
offset <- rep(0, np[1])
} else if (length(offset) != np[1]) {
stop("length of offset not equal to the length of... |
913967d37bd737f6e999e2982dc4ffb1c67b081f | d62d9ea2f6aa749fa48455bddbd3208279ce6449 | /inst/extdata/setas-model-new-trunk/shrink-output-trunk.R | 30c4c9591f1002639a2129dbedf2be6bfe613c00 | [] | no_license | jporobicg/atlantistools | 3bffee764cca1c3d8c7a298fd3a0b8b486b7957e | 75ea349fe21435e9d15e8d12ac8060f7ceef31a2 | refs/heads/master | 2021-01-12T03:06:55.821723 | 2017-05-26T04:03:33 | 2017-05-26T04:03:33 | 78,160,576 | 1 | 0 | null | 2017-05-25T23:35:23 | 2017-01-06T00:51:21 | R | UTF-8 | R | false | false | 4,996 | r | shrink-output-trunk.R | library("atlantistools")
file_fgs <- "SETasGroupsDem_NoCep.csv"
file_init <- "INIT_VMPA_Jan2015"
file_gen <- "outputSETAS"
file_prod <- "outputSETASPROD"
# utility functions -------------------------------------------------------------------------------
find_flags <- function(chars) {
ids <- sort(unlist(lapply(c("do... |
b5fcf7c385dd12c887868c301f355de33d375f00 | 10b8c374979669fd8767d240da964924ed9b562c | /scripts/extractAllRowsWithOnlyOneSnpGenotype.R | 1a09611a88f23e74eb5a3faf672c869bafaed84c | [] | no_license | benranco/docs | db253e4d160256ea4c72727903a4bceab48a0761 | 33e3dc82c0a97305747cb2720c78fbb733e820f4 | refs/heads/master | 2023-04-16T13:25:28.630662 | 2023-04-06T16:35:27 | 2023-04-06T16:35:27 | 68,756,861 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,698 | r | extractAllRowsWithOnlyOneSnpGenotype.R |
options(stringsAsFactors = FALSE, warn = 1)
args <- commandArgs(trailingOnly = TRUE)
write("Running extractAllRowsWithOnlyOneSnpGenotype.R.", stdout())
# ########################################################
# Input Parameters:
path <- "/home/benrancourt/Desktop/junjun/region45-SNPpipelineOct2018/reports/Le... |
c464e33bdb421060838fadc2dd892f1abc01742f | 0875bd1def7d09ac710326c6ca3d79d7ab0f1c62 | /shiny/server.R | 4a4522a38747a2f15fba66fbb017a6df6b7e0789 | [] | no_license | domingos86/job-listings | e42aabab3019feb888d65db8bcc862849aaa61fb | d8959c31feb5d96526f4d36bc4f5b2591e8a5c19 | refs/heads/master | 2020-05-26T20:00:42.384388 | 2017-02-20T00:50:14 | 2017-02-20T00:50:14 | 82,500,808 | 10 | 6 | null | null | null | null | UTF-8 | R | false | false | 4,444 | r | server.R | library(shiny)
library(leaflet)
library(leaflet.extras)
library(dplyr)
# library(htmltools)
# library(htmlwidgets)
#
# heatPlugin <- htmlDependency("Leaflet.heat", "99.99.99",
# src = c(href = "http://leaflet.github.io/Leaflet.heat/dist/"),
# script = "leaflet... |
6219c6735b6489468a943d8ebe23bf7c33231dfc | 6b6ad0eab907650113638439e67536cea1748ce6 | /scripts/qtl_overlap.R | cdf703f6b6a7ea415fe97c94ec89080eed54c200 | [
"MIT"
] | permissive | dmgatti/Tufts_TB | a1fe3081e911a81805c8fed8e4123252a39cd56b | 837a7fa73edd36c1dbc557608e3e9a9f8a73c6ef | refs/heads/master | 2023-07-31T14:10:59.159931 | 2021-09-10T20:02:03 | 2021-09-10T20:02:03 | 286,800,946 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,403 | r | qtl_overlap.R | ################################################################################
# Plot of QTL overlap per chr.
# Daniel Gatti
# 2021-02-14
# dmgatti@coa.edu
################################################################################
library(GenomicRanges)
library(tidyverse)
# Set up base directories.
base_dir = ... |
ca45e26cf3d4824cd34739b283dc6275d06a35b0 | 48ef86a36dbc209c441aad10caaa8e865f9a2333 | /man/load_grr.Rd | 6a05c8298a45b27cb4ea9ff9f5dd617aa0fa26ba | [
"MIT"
] | permissive | andrewpbray/gatherer | 09a2cccd47f631013e2c9148dcbb44d999b10418 | dd937094cccbd6f40fb40b22c02b0ea74543679d | refs/heads/master | 2023-01-08T23:00:59.711724 | 2020-11-10T05:06:21 | 2020-11-10T05:06:21 | 299,126,075 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 540 | rd | load_grr.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create.R
\name{load_grr}
\alias{load_grr}
\title{Load \code{grr} object from a template}
\usage{
load_grr(template, modules = "all")
}
\arguments{
\item{template}{Name of template. Run \code{list_templates()} to see current options}
\item{mo... |
7af996b1fdd081a8832f8947bcc36cb5727779b3 | 1332d8b68c6b86c2be5ed064473794f9f808d16a | /binomial/man/bin_cumulative.Rd | 52557ae9975c9b0c1433519660d550ebb8017d60 | [] | no_license | stat133-sp19/hw-stat133-mallikakolar | e7ffe1bbd22c2b9e2d466c12bdc3685db88af096 | bc99e849eebe2c233455053271aed6f3fae8c541 | refs/heads/master | 2020-04-28T14:45:55.706460 | 2019-05-02T22:54:45 | 2019-05-02T22:54:45 | 175,348,070 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 462 | rd | bin_cumulative.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/main-functions.R
\name{bin_cumulative}
\alias{bin_cumulative}
\title{bin_cumulative}
\usage{
bin_cumulative(trials, prob)
}
\arguments{
\item{int}{integer trials}
\item{int}{integer prob}
}
\value{
dataframe with bincum class
}
\description{... |
86cb60ec67eaec92a4bcdf2c05f1c46b7fab6712 | 46d07f08b90ab7019c9a2a1ee1734a5cf7cd7339 | /cachematrix.R | a1b2dd97207b52441acf115d06a83687905d2864 | [] | no_license | Chloex7/ProgrammingAssignment2 | d3c16fe7730c0aa0b563c39da0f47a0c19e6c420 | a98d525d61eeb68cfe7f790a5f8bd4d9379f9a64 | refs/heads/master | 2023-08-14T17:25:57.357851 | 2021-10-14T05:38:18 | 2021-10-14T05:38:18 | 416,327,597 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 763 | r | cachematrix.R | ## This function creates a matrix and its inverse, which will be cached
makeCacheMatrix <- function(x = matrix()) {
a <- NULL
set <- function(y) {
x <<- y
a <<- NULL
}
get <- function() x
setinverse <- function(inverse) a <<- inverse
getinverse <- function() a
list(set = set, get = get,
se... |
bd8730aa58f525729797a3c8f8399bd2e2410820 | 110c41798470fafa38f319a4b6ecf05422bb1c8c | /competitor.R | 7a29e571c6b2ff63ba34a5db4453c988566c4eff | [] | no_license | Coelacanss/C_Digital_Marketing | 358b1e592a5fb2bd870a843ee4e93a1f0ed3d50d | e8e8236f786e002a539809cb5cf7003a840176b1 | refs/heads/master | 2020-12-05T23:13:03.650281 | 2016-08-17T17:14:53 | 2016-08-17T17:14:53 | 65,927,086 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,594 | r | competitor.R | ### This script is to study the use of social media of Genesee's competitor Small Town Brewery
library(Rfacebook)
library(httpuv)
library(RCurl)
library(rjson)
library(httr)
library(RColorBrewer)
library(twitteR)
library(tm)
library(SnowballC)
library(plyr)
################## Facebook ####################
##
## API ... |
0fa5dc5073a5571addb0026dcafa9390820f8b11 | c0fc699f5198b1cdbd5b9b6f46e540580b48cfbc | /zz-need-cleaning/clt1/app.R | f916f69b0543dde3e5b2b12a6e7bca8acd9c4dcd | [] | no_license | tloux/teaching-shiny | 3af6e9deeb518b59f9f0a0727ab34a6b4660f478 | d6d7ac53868d0f51abeda0806668bf25f2b6b198 | refs/heads/master | 2023-06-18T12:16:25.790906 | 2021-07-05T16:25:48 | 2021-07-05T16:25:48 | 155,304,332 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,318 | r | app.R | library(shiny)
ui = fluidPage(
titlePanel('Central Limit Theorem'),
sidebarLayout(
sidebarPanel(
sliderInput('n',
'Sample size:',
min=1, max=50, step=1, value=1,
animate=animationOptions(interval=300,loop=FALSE))
),
mainPanel(
... |
a5bd043238757ccce55da1c065413b9cec576d89 | aebca85114388224fc24481fdfce04be048110db | /R/printMedianQ13.R | a091e0eee61ab7d41acba0f98ddc10c2e5adc015 | [] | no_license | mssm-msf-2019/BiostatsALL | 4f79f2fbb823db8a0cbe60172b3dcd54eac58539 | 0623dd13db576b2501783b31d08ae43340f2080b | refs/heads/master | 2020-05-25T15:16:01.949307 | 2019-05-21T18:11:12 | 2019-05-21T18:11:12 | 187,864,190 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 262 | r | printMedianQ13.R | #' Functions to get median and IQR
#' @description Functions to get median and IQR used by createNiceTable()
printMedianQ13 <- function(vec) {
q <- quantile(vec, na.rm=TRUE)
sprintf("%.1f [%.1f-%.1f]", median(vec,na.rm=TRUE), q["25%"], q["75%"])
}
|
2a874a6692d29dc0e8788a442923ac3f459cfd32 | 2cd54a4365c128d94c120a204aaccf68c3607b49 | /man/plsda_auroc_vip_compare.Rd | f3c6d29da3725a6163b19591f6ee0dd1e82affed | [
"MIT"
] | permissive | tikunov/AlpsNMR | 952a9e47a93cbdc22d7f11b4cb1640edd736a5c7 | 748d140d94f65b93cb67fd34753cc1ef9e450445 | refs/heads/master | 2021-01-13T17:35:29.827357 | 2020-02-23T02:35:30 | 2020-02-23T02:35:30 | 242,443,517 | 0 | 0 | NOASSERTION | 2020-02-23T02:27:15 | 2020-02-23T02:27:15 | null | UTF-8 | R | false | true | 423 | rd | plsda_auroc_vip_compare.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plsda.R
\name{plsda_auroc_vip_compare}
\alias{plsda_auroc_vip_compare}
\title{Compare PLSDA auroc VIP results}
\usage{
plsda_auroc_vip_compare(...)
}
\arguments{
\item{...}{Results of \link{nmr_data_analysis} to be combined. Give each result ... |
bf310f66b63ec08a180cbb5a55365aacc2b13ba5 | ca6d02c14d9cbe93d8460f1d20853203c831eaac | /Automation/00_hydra/Peru.R | c33fb69c69e9397db8d5af9940769c73d61250c4 | [
"CC-BY-4.0"
] | permissive | timriffe/covid_age | f654bea1cdf87e9aa9cc660facfdffb9264a9f5a | 8486772b0bfc0803efab603d8ac751ffe54e4d89 | refs/heads/master | 2023-08-18T04:56:18.683797 | 2023-08-11T10:22:19 | 2023-08-11T10:22:19 | 253,315,845 | 58 | 28 | NOASSERTION | 2023-08-25T11:03:04 | 2020-04-05T19:31:26 | R | UTF-8 | R | false | false | 9,740 | r | Peru.R |
source(here::here("Automation/00_Functions_automation.R"))
#install.packages("archive")
library(archive)
# assigning Drive credentials in the case the script is verified manually
if (!"email" %in% ls()){
email <- "gatemonte@gmail.com"
}
# info country and N drive address
ctr <- "Peru"
dir_n <- "N:/COVerAGE-DB/A... |
df0e22b67859d2f3c973d36c5f8a72399e41baf5 | 4d7fc3da737029516b1dd2eb4468a8f2bc419da2 | /man/FindCorrelatedRegions.Rd | fc9c1ee77dd69e0bbccf850a0bd1fd738e695dd1 | [] | no_license | TransBioInfoLab/rnaEditr | 4e4a2b4ef859833a107cff379e2bf6b4bcf69f13 | 4c83343a9e825e5dd8f4b5c4abfa4cc7d4f01675 | refs/heads/master | 2022-11-27T11:28:22.143395 | 2022-11-24T06:49:44 | 2022-11-24T06:49:44 | 298,858,179 | 1 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,400 | rd | FindCorrelatedRegions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util_FindCorrelatedRegions.R
\name{FindCorrelatedRegions}
\alias{FindCorrelatedRegions}
\title{Find contiguous co-edited subregions.}
\usage{
FindCorrelatedRegions(
sites_df,
featureType = c("site", "cpg"),
minSites_int = 3
)
}
\argumen... |
ca8eef77d5618b68ffcd81e883eaf3038eb4a8c2 | 5d0bc9fa9c48a468d115e9930f5eac66a0764789 | /inst/snippets/Table6.2.R | f5abdaaa9a99de2cf19ecaa47c42f2c10b31be45 | [] | no_license | rpruim/ISIwithR | a48aac902c9a25b857d2fd9c81cb2fc0eb0e848e | 7703172a2d854516348267c87319ace046508eef | refs/heads/master | 2020-04-15T20:36:55.171770 | 2015-05-21T09:20:21 | 2015-05-21T09:20:21 | 21,158,247 | 5 | 2 | null | null | null | null | UTF-8 | R | false | false | 17 | r | Table6.2.R | head(BikeTimes)
|
4b5905b28551b2a2175bf6bd47a79add876cc3b1 | 7dec3545021a28a3209f1234b743886537c0d8ba | /candle_geom.R | 65deda1c961d55b6b0387c51655602f3d1202f54 | [] | no_license | sciprojguy/custom_geoms_R | 4ecc8c13e1f2651e6670fe035b77ffb3e80ec5b2 | d4d419778a33e1c897530e5b7b036d086a84dd4f | refs/heads/master | 2022-08-10T02:28:12.671291 | 2020-05-24T21:48:59 | 2020-05-24T21:48:59 | 266,630,296 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,498 | r | candle_geom.R | library(grid)
library(ggplot2)
library(readr)
library(dplyr)
candleGrob <- function(xc, yc, openc, closec, highc, lowc) {
}
candleGrobs <- function(x, y, open, close, high, low) {
#x,y are the center of the candle rectangle
#high,low define the top and bottom of the glyph
#open/close can be in either order a... |
5c565e4548b0eb55a950e2f9ac89d8da32817fc0 | 136eb68c86c635874692878a3cf54faeb3b36b45 | /examples/MSFTstock.r | 46557136a877829ceaaf4a5ae9e6493c9c538a12 | [
"MIT"
] | permissive | Azure/Azure-MachineLearning-ClientLibrary-R | 84f5a2db2c3c0dd1f417c5c470cee4899c8c3611 | dda06a103f774491de48dd54db8e56b961de7861 | refs/heads/master | 2023-04-14T12:25:46.928784 | 2023-03-28T16:48:16 | 2023-03-28T16:48:16 | 38,313,864 | 22 | 13 | MIT | 2023-03-28T16:48:18 | 2015-06-30T14:27:45 | HTML | UTF-8 | R | false | false | 1,421 | r | MSFTstock.r | ## Linear model for MSFT stock dataset ##
# You can use the setwd() command to change your working directory. Examples below
# Currently using identification for an account on studio.azureml-int.net
# If you would like to see the web services published, please create an account there
# and substitute in your identifi... |
54a22d307f4dfd49db8937ad82a7034ad51ec2c6 | b028a329bb2de517cf3eb6d908b9a596c2e0a633 | /FinalCode_v2.R | a2efe8673ce7fc611b9a20495b67b31216f614be | [] | no_license | caomao1111/6101-bts | c69b3c052f1d0493069f8a62564cb98a452739ea | 86820724af5fb94337340fce1f9549f51cf5033a | refs/heads/master | 2021-09-08T23:09:56.245215 | 2018-02-02T23:33:36 | 2018-02-02T23:33:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,645 | r | FinalCode_v2.R | #' ---
#' title: 6101 Project 2 Final
#' author: TeamBestTeam
#' date: 31Oct17
#' output:
#' html_document:
#' toc: true
#' highlight: haddock
#' ---
#'#######################################
#http://rpubs.com/jassalak/TeamBestTeam_Proj2
#'#######################################
#' ## Environ... |
21c41da93fb9929c41825dce0de60535660205da | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/balance/examples/vlr.Rd.R | 507f6370ec2eaa61e9a6e740782a4d6264a9532d | [] | 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 | 163 | r | vlr.Rd.R | library(balance)
### Name: vlr
### Title: Calculate Log-ratio Variance
### Aliases: vlr
### ** Examples
library(balance)
data(iris)
x <- iris[,1:4]
vlr(x)
|
1f54143a391986c31e3949da5f02cddd5fd75552 | 37794cfdab196879e67c3826bae27d44dc86d7f7 | /Graph/Rigidity.R | 96d865882a74fd4e3496d365707c6bfe71a41fc1 | [] | no_license | discoleo/R | 0bbd53a54af392ef53a6e24af85cec4f21133d17 | e9db8008fb66fb4e6e17ff6f301babde0b2fc1ff | refs/heads/master | 2023-09-05T00:43:32.381031 | 2023-08-31T23:03:27 | 2023-08-31T23:03:27 | 213,750,865 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 12,543 | r | Rigidity.R | ###################
###
### Rigidity Theory
###
### Leonard Mada
###
### draft v.0.1l-formatted
### Rigidity Theory
### Global Rigidity
###################
### 1D Rigidity ###
###################
### Satisfiability:
# - let x be n positive integers;
# - is there a set of coefficients b
# with... |
485a73b2de0bf1d4c99d50994a056e7cea76f435 | 9576cbd2b43057a1f4bd9946f96b1f525b494ef1 | /man/listr.Rd | 94c1efdf1fa7de33e13b5431259ae383711264c4 | [] | no_license | jonocarroll/remedy | b2a55215d9efd395a9c1eb09d01f0d6b10e6281c | b61a8b50f25d1b98d5c84ad22d36c5b415e0e77e | refs/heads/master | 2021-10-20T22:06:47.007957 | 2019-02-27T14:19:19 | 2019-02-27T14:19:19 | 114,829,430 | 1 | 0 | null | 2017-12-20T01:41:38 | 2017-12-20T01:41:37 | null | UTF-8 | R | false | true | 498 | rd | listr.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/listr.R
\name{listr}
\alias{listr}
\alias{olistr}
\title{Convert to list}
\usage{
listr()
olistr()
}
\value{
\code{listr()} returns an unordered markdown list
\code{olistr()} returns an ordered markdown list
}
\description{
Convert selected... |
cc1414db09d26d82ac811fd0096cdfa2dc2c4dca | 52ba5412e051388f2f0660c8c66da21a00dfac40 | /R/qqplot for data (without model).R | a6af9ee837f66c493c312e3d7bf2d17113777586 | [] | no_license | beausoleilmo/handy_r_functions | cd551cd5a23591835a9f1b27a7592f3e394aac94 | dbc25658399a9ec713f933b6370567d0c67ee682 | refs/heads/master | 2021-06-28T19:08:35.735730 | 2021-01-15T15:11:29 | 2021-01-15T15:11:29 | 212,481,697 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 756 | r | qqplot for data (without model).R | #### ### ### ## #### ### ### ## #### ### ### ##
# Created by Marc-Olivier Beausoleil
# 03 Nomvember 2020
# Why: Get the qqplot for any data
# Output:
# Requires:
# NOTES: Inspired from a course named "Learning Statistics with R" from "The Great Courses"
#### ### ### ## #### ### ### ## #### ### ### ##
# Get the da... |
20a18e0b13dd7486d10d3ce3f3d91f0fbdbee3a3 | 1aa43f1b2cd1b30007ceeafd21f5f869b8966760 | /NCAA_Baseball/model.R | 3a12260ce38760b25d1a3fdc27c519b7175aaf01 | [] | no_license | lbenz730/Sports_Analytics | 447e9eaca8447b8cf315254936851882df99f559 | cae7ea66b380f6fe7eb14c014ef3dcf71c4f56a6 | refs/heads/master | 2021-01-01T04:52:50.127640 | 2018-12-14T02:26:07 | 2018-12-14T02:26:07 | 97,263,693 | 10 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,345 | r | model.R | x <- read.csv("scores.csv", as.is = T)
y <- read.csv("tournament.csv", as.is = T)
x$rundiff <- x$teamscore - x$oppscore
# Create Model
lm.bb <- lm(rundiff ~ team + opponent + location, data = x)
# Point Spread to Win Percentage Model
x$winprob <- NA
x$winprob[x$rundiff > 0] <- 1
x$winprob[x$rundiff < 0] <- 0
x$pred... |
f06104ad0df7fa876612e9d3021b177e1484295a | da830d4331e1d851113ac4e93b1728af073f9f60 | /man/granovagg.ds.Rd | 6a0efcd528e2da7595455b7a626977e80ad823e4 | [] | no_license | cran/granovaGG | e1ecd8383edf444c8f1dc2917de62e8ccd28d9ea | 65342433ea3a8bff1a16949ed3add1f5964b865f | refs/heads/master | 2021-01-21T21:39:38.712000 | 2015-12-18T06:43:16 | 2015-12-18T06:43:16 | 17,696,501 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 6,742 | rd | granovagg.ds.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/granovagg.ds.R
\name{granovagg.ds}
\alias{granovagg.ds}
\title{Elemental Graphic for Display of Dependent Sample Data}
\usage{
granovagg.ds(data = NULL, revc = FALSE, main = "default_granova_title",
xlab = NULL, ylab = NULL, conf.level = 0.... |
02598428292f48f78012aa3d048b94c3e4969482 | d8e6354d5fcc6f3f1202fccccaf816f11d6a0518 | /R Files/ps1.R | 055387be23aaa3ab4cbaf36ebc227c0129d8ebb7 | [] | no_license | nishidhvlad/Repository | 4f7ff19c7c4cb92f53fc6d3f4df79dc2e82a7a04 | b10e664b6d9912bb49f5d20d0ab16562f76a90de | refs/heads/master | 2020-03-26T04:29:44.084478 | 2018-08-12T22:36:21 | 2018-08-12T22:36:21 | 144,506,506 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,340 | r | ps1.R | ########################################
#File: Problem Set 1
#Author: Nishidh Lad
#Date: September 7,2017
########################################
rm(list=ls(all=TRUE))
library(data.table)
context1 <- fread('WAGE1.csv')
summary(context1)
lwage <- log(context1$wage)
model1 <- lm(wage~educ, data=contex... |
783e6eb845f68024f38bef75fc41335a08013c1c | c79fa021f5bb195a4abfcf81d88a49b5ae86ce73 | /man/risk_stein.Rd | 98737715264acd15263417c2af53f0e8d7ef4bdb | [
"MIT"
] | permissive | topepo/sparsediscrim | 7c99e48f9552455c494e6a04ab2baabd4044a813 | 60198a54e0ced0afa3909121eea55321dd04c56f | refs/heads/main | 2021-08-08T17:04:45.633377 | 2021-06-28T00:27:34 | 2021-06-28T00:27:34 | 313,120,774 | 4 | 0 | NOASSERTION | 2021-06-28T00:27:34 | 2020-11-15T20:51:32 | R | UTF-8 | R | false | true | 1,388 | rd | risk_stein.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/stein-shrinkage.r
\name{risk_stein}
\alias{risk_stein}
\title{Stein Risk function from Pang et al. (2009).}
\usage{
risk_stein(N, K, var_feature, num_alphas = 101, t = -1)
}
\arguments{
\item{N}{the sample size.}
\item{K}{the number of class... |
94c40463f0c4453a67b597fa78933465a22314c6 | 0ebf0950d351f32a25dadb64b4a256a8a9022039 | /inst/rsp-ex/TCGA,OV,testSet,pairs,fracB/R/zzz.R | 44a3bfb4d0c4f573d561920e8f0c6b4ae26069a8 | [] | no_license | HenrikBengtsson/aroma.cn.eval | de02b8ef0ae30da40e32f9473d810e44b59213ec | 0462706483101b74ac47057db4e36e2f7275763c | refs/heads/master | 2020-04-26T16:09:27.712170 | 2019-01-06T20:41:30 | 2019-01-06T20:41:30 | 20,847,824 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,655 | r | zzz.R | ############################################################################
#
############################################################################
## for the fullNamesTranslator
fntFUN <- function(names, ...) {
pattern <- "^(TCGA-[0-9]{2}-[0-9]{4})-([0-9]{2}[A-Z])[-]*(.*)";
gsub(pattern, "\\1,\\2,\\3", nam... |
52098ce2769ca91910ed988d356f42a4da52bb91 | 306c9c5808cfbbcbfe6b9bf42c0f3ad1a9502879 | /man/subset_proteins.Rd | dbd96b28d739b0a0bda90fb23cf3777348e3b389 | [
"MIT"
] | permissive | YuliyaLab/ProteoMM | 333386474d1d9cf984fad74ab299335c52f8003e | 3058e12d44b9f2a64f74b4165bf563b5c594ed05 | refs/heads/master | 2022-05-15T08:21:13.133808 | 2022-04-10T05:20:14 | 2022-04-10T05:20:14 | 138,552,525 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 4,079 | rd | subset_proteins.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/TwoPart_MultiMS.R
\name{subset_proteins}
\alias{subset_proteins}
\title{Subset proteins}
\usage{
subset_proteins(mm_list, prot.info, prot_col_name)
}
\arguments{
\item{mm_list}{list of matrices for each experiment,
length = number of datasets... |
3837447eeac6c7b8dbab2d139293f4ba6bba39ae | 65c1fa759af61a18c6d551994fe7fa71dd766724 | /tests/testthat/test.utilities.R | d0eee67f3efd52909a3e305fdbda663e1ece3afa | [] | no_license | livioivil/resamplingMCP | ce479f9cc80ab8ba3a2f244860018e0980f1e5e2 | 01b60800f1ba44e07d8dd280eb30e63d34122337 | refs/heads/master | 2021-01-18T11:28:53.636162 | 2015-12-02T09:28:18 | 2015-12-02T09:28:18 | 58,716,277 | 1 | 0 | null | 2016-05-13T08:10:07 | 2016-05-13T08:10:07 | null | UTF-8 | R | false | false | 2,862 | r | test.utilities.R | context("Utilities")
expect_aboutequal <- function(object,expected,digits=4,...){
ro <- round(object,digits)
re <- round(expected,digits)
expect_equivalent(ro,re,...)
}
## test mean diff
n <- 30
m <- 100
x <- rnorm(2*n)
X <- matrix(rnorm(2*n*m),nc=m)
largeX <- matrix(rnorm(2*n*10^5),nc=10^5)
g <- rep(c(0,1... |
2cc534ab287773d4f537d11460f9196bfa3893a5 | c35e0e7a2c2d9f0e15bdc90407faab4c886db76c | /cachematrix.R | d7da4286e3f81d4157f8537f23fb6360477631e9 | [] | no_license | aaditya22/ProgrammingAssignment2 | 84da4b4b068a266ee7a10bae7be9f05da8d1a7b5 | a92835f6551dec9df7ddbafc57f3eb7aa668334d | refs/heads/master | 2020-05-28T04:14:58.695004 | 2019-05-27T17:13:08 | 2019-05-27T17:13:08 | 188,876,751 | 0 | 0 | null | 2019-05-27T16:28:37 | 2019-05-27T16:28:36 | null | UTF-8 | R | false | false | 1,120 | r | cachematrix.R | #The first function, makeCacheMatrix creates a special "matrix", which is really a list containing a function to
#1set the value of the matrix
#2get the value of the matrix
#3set the value of the inverse
#4get the value of the inverse
makeCacheMatrix <- function(x = matrix()) {
inv <- NULL
set <- function(y){
... |
55a9a0b36cba246b926173664f34b3a992c73402 | 57ef89c43665c3fb4523087364918d909c23d2b5 | /Visualization.R | 1b41efe08ea482a7fcea480bbbf914b2b935633e | [] | no_license | Franca97/Web_Data_and-_Digital_Analytics | f2ae3c89be0f58b28789382d235c356699edf29c | e5ba1735744ec9ad0178442d09f00a4946c8e7e6 | refs/heads/master | 2022-07-22T15:49:31.500990 | 2020-05-19T20:50:36 | 2020-05-19T20:50:36 | 256,192,595 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,351 | r | Visualization.R | remove(list = ls())
library("readxl")
library("writexl")
library(assertthat)
library(dplyr)
library(purrr)
library(igraph)
library(ggplot2)
library(ggraph)
library(ggmap)
library(maps)
getwd()
Loc <- read_excel("countries_Location.xlsx")
Loc <- data.frame(Loc) #Changed the excel file into a data frame
colnames(Loc... |
c6a75352a87a10dd02881628b97f50c5a8d413ab | 85c10bc47055f252ceba7ad9d7dcacb412e72c30 | /man/expmFrechet.Rd | 065c1672169071304547047346c4df21abd1d4d7 | [] | no_license | cran/expm | 529e87fb45320487ebfb60f09315c8b7597f965f | 415aa29e1c8aabaa543905a34417fbc03c43fdc1 | refs/heads/master | 2023-01-28T14:42:11.533892 | 2023-01-09T13:30:02 | 2023-01-09T13:30:02 | 17,695,904 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,361 | rd | expmFrechet.Rd | \name{expmFrechet}
\title{Frechet Derivative of the Matrix Exponential}
\alias{expmFrechet}
\encoding{UTF-8}
\description{
Compute the Frechet (actually \sQuote{Fréchet}) derivative of the
matrix exponential operator.
}
\usage{
expmFrechet(A, E, method = c("SPS", "blockEnlarge"), expm = TRUE)
}
\arguments{
\item{... |
832c467c5f5217678c5cc4b3f3eb585f49fd9b39 | 6a675af74d90787ccceba90151a6b2ec52a0c91b | /R/extract_poc_token.R | 6a5bd2217bd64ec8fd5c7e298673f64ddadfb6b5 | [] | no_license | cssat/oliveRconnect | f17f32cfd7e90c75a3862749b07d578ea90e2925 | 3dc44edc0ac3a3800ddbee6fb116a7f5f7ef8223 | refs/heads/master | 2020-04-16T12:24:06.364665 | 2019-01-31T16:54:08 | 2019-01-31T16:54:08 | 165,577,470 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 344 | r | extract_poc_token.R | #' Extract token from Oliver sign-in GET response
#'
#' @param response A response from a GET to one of the oliver Sign-in Domains containing a "poc.t" cookie.
#'
#' @return
#' @export
#'
#' @examples
extract_poc_token <- function(response) {
dat_cookies <- httr::cookies(response)
dat_cookies[dat_cookies$name... |
eb555224783e189987eaf7d202a6056f5abde461 | 775e19784b455fabaeac018079d7a022dad1d274 | /utilities.R | 0a2befe8fab07239cdc0ccaa63d9943d31b403a7 | [] | no_license | NIH-IRP-SingleCell/SC-UsersGroup | 605caeb973887865240299ebc98b665c40cd641e | a1a562ff73b2257b688af1c09101ef2cd8ec4e23 | refs/heads/master | 2023-08-04T11:27:50.907025 | 2023-08-01T15:38:46 | 2023-08-01T15:38:46 | 99,155,428 | 12 | 3 | null | 2019-03-07T15:23:14 | 2017-08-02T19:53:38 | null | UTF-8 | R | false | false | 15,326 | r | utilities.R | # Load required biconductor and CRAN packages
require(BiocGenerics)
# Enable only semi-serious parallel processing - only max of 2 cores
suppressPackageStartupMessages(require("BiocParallel"))
n.cores <- min(2, parallel::detectCores())
BiocParallel::register(BiocParallel::MulticoreParam(n.cores))
# Enable keeping on... |
f51f506a362b00cdc42f05557c8baf49f2966d7b | b3886aa58396fec17f8e3feeac8fe8259071b39e | /Super-Computer-Analysis-With-R-Language/Super-Computer-Analysis-With-R-Language.R | f60b901cf196b4d61856b56e0ac955b3bededef9 | [] | no_license | zeysert/Super-Computer-Analysis-With-R-Language | a69350b77dd5580734aa0279e240f17bd9ae696c | 1e76c47d59cf7b233795a8aee34fcf5a9af8eeba | refs/heads/master | 2022-04-23T08:28:07.368110 | 2020-04-21T09:33:03 | 2020-04-21T09:33:03 | 257,368,475 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,347 | r | Super-Computer-Analysis-With-R-Language.R | library(tidyverse)
library(readxl)
ham_veri <- read_excel("/Users/cenkatlig/Super_Bilgisayar.xlsx") %>% tbl_df()
# Then making the raw data smoother
# It is provided to write separately on each line (originally, systems would sell 2 series)
ara_veri <-
ham_veri %>%
slice(seq(1,nrow(.),by=2)) %>%
c... |
644711f53525e31fa07f36bb5e43d624b4e59066 | 1947642e415118426f8e4d96eedc6d64a12672d6 | /man/model_fun_no_rebal.Rd | c32d7b683ea4bfa259a60a1941fc3906cebd5095 | [] | no_license | cquigley/rPerfFunc | 9917b4332391332842d69566aea0f63f95eb5ec3 | 478aff105bbcacb0e6e56346062c57763ec1647c | refs/heads/master | 2021-01-17T13:25:46.809452 | 2016-08-04T19:17:14 | 2016-08-04T19:17:14 | 64,801,245 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 358 | rd | model_fun_no_rebal.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/performance.R
\name{model_fun_no_rebal}
\alias{model_fun_no_rebal}
\title{identical to model_fun, except does not rebalance}
\usage{
model_fun_no_rebal(vsn, model, namer = "ret", custom_rets = NULL)
}
\description{
identical to model... |
bd48f23b7ddf6ccfd7d88c07dbbcc8ef271e32fd | a7f1a225e0d2e8412c782cfd4901f7c8a73fd857 | /man/MetFragConfig.CompToxCSV.Rd | fee86bcdda3782b86bde2d4e87eb7fdf009daef7 | [
"Artistic-2.0"
] | permissive | tsufz/ReSOLUTION | d8583cfc510b0983df3bd80759ae97c38760b6ec | 030ce38a5d5773ac2b56f6140652b459a1ae81f7 | refs/heads/master | 2022-11-15T04:41:42.829412 | 2021-05-19T10:31:04 | 2021-05-19T10:31:04 | 245,197,287 | 0 | 0 | null | 2020-03-05T15:19:55 | 2020-03-05T15:19:54 | null | UTF-8 | R | false | true | 5,383 | rd | MetFragConfig.CompToxCSV.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MetFragConfigR.R
\name{MetFragConfig.CompToxCSV}
\alias{MetFragConfig.CompToxCSV}
\title{Create MetFrag Config Files with LocalCSV and Scoring Terms from CompTox MetFrag XLS Export}
\usage{
MetFragConfig.CompToxCSV(mass, adduct_type, results_... |
924c2653b8af422c20d85c4cf40fabc60911951d | 8d3cfc073ea47ddd43f9fc3ffe3c4e6e760cdc93 | /treating data confidentiality & statistical disclosure/evaluate_cps.R | 07cd4e1f7812f200d6fb5d634e53e18d228fed70 | [] | no_license | anel-li/MDM-coding | f9313a19a5a95d45135ce16b0c3f9a400fe5234b | 8d6cd82e4d2a2263d3c2d5bf793f3d35c9b4b9d9 | refs/heads/main | 2023-08-25T02:55:15.696914 | 2021-10-16T21:13:30 | 2021-10-16T21:13:30 | 411,427,339 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,141 | r | evaluate_cps.R | #####################################
#####Analytical Validity Evaluations#
#####################################
eval<-function(data){
####quantities of interest
####mean income by gender
####mean age by gender
####returns to schooling
###descriptive statistics
income<-cbind(as.numeric(by(data$income,d... |
6e35d5a2640de8600e44dec1717ec34f56ada2ef | 30427a7015befa1c2923311622f9a60c0b500050 | /R/telfer_func.r | 3f81fc987e65902896fcda55e4a460a6bc93e202 | [] | no_license | ealarsen/sparta | 35c5fe7d3b84077db871e2788f768c63ba233945 | 3f80893fca52de551f7674e3912e60e03df7f6a5 | refs/heads/master | 2021-01-23T01:51:11.148474 | 2014-11-19T10:17:59 | 2014-11-19T10:17:59 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,600 | r | telfer_func.r | # Internal function that uses the implementation of Telfer written by Gary Powney
GP_telfer <- function (taxa_data,time_periods,iterations=10,useIterations=TRUE,min_sq=5){
# Create a vector of all the years to include
for (i in 1:length(row.names(time_periods))) {
run<-time_periods[i,1]:time_periods[i,2]
... |
9ff7269117a693dc9642426ebaffc615a0337431 | 6a341795a260db577ca698a23f6e9fea98d8ed40 | /day10/Untitled.R | aa18f2398a5a53d58eab995c138252ff255de3c5 | [] | no_license | euka96/R | 80dde9b722ce4e54488e38915ca16fd797ee5205 | 59008c8f34ea7b05c28075e0b46315fd368f2e17 | refs/heads/main | 2023-05-06T08:11:30.576731 | 2021-06-03T08:43:22 | 2021-06-03T08:43:22 | 373,421,339 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,967 | r | Untitled.R | hiphop <- readLines("~/Desktop/R/data/hiphop1.txt"); hiphop
hiphop1 <- str_replace_all(hiphop, "\\W", " "); hiphop1 #단어가 아닌 모든 것
hiphop2 <- extractNoun(hiphop1); hiphop2
wordcount <- table(unlist(hiphop2)); wordcount
df_word <- as.data.frame(wordcount, stringsAsFactors = FALSE); head(df_word)
df_word1 <- rename(df_word... |
c2a374a999729eb54eb1d862b7012c75922de2d6 | ab85762f0fdb71e762448a344cd3fd748f7af374 | /build_scatter.R | 38a4a92f7e760282253c35661d6b8b7b77283596 | [] | no_license | soccerdude2014/assignment8 | abad2b124680261a33842e705a442c3b12375d20 | 849ab61fa0ff39d8d6a7452a1ebff1f340993776 | refs/heads/master | 2016-08-09T06:14:45.806163 | 2016-03-02T20:02:30 | 2016-03-02T20:02:30 | 52,653,073 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 780 | r | build_scatter.R | #Function makes a scatter plot. Takes in 4 paramters:
#The data to be made into a plot, the x variable, the y variable, the type of flower to be displayed
build_scatter <- function(data, xvar = 'Petal.Length', yvar = 'Sepal.Length', flower = 'all') {
#Filters down to match the selected flower. Only filters if all is ... |
c9f2cec707226ffdea0b57b91d978f09967f0eeb | b08c25c032524882c6e3e5dae632c7ffc00b7bf1 | /Housekeeping.R | 5b1c8a5840cb8d52d9f660ad611093330868a9ba | [] | no_license | haejung017/BiostatsR | 959e0351b7e356fcefcd5078a95a7711ca962915 | 4937e6978cba002317ae0c4b80ae2d2730f5f531 | refs/heads/master | 2020-04-21T11:15:57.645621 | 2019-02-07T04:45:11 | 2019-02-07T04:48:00 | 169,517,945 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,042 | r | Housekeeping.R | library(Rcpp)
sourceCpp("C:/Users/Jay/Desktop/CompRisk/R/cumh_ED.cpp")
#sourceCpp("C:/Users/Jay/Desktop/CompRisk/R/cumh_IS.cpp")
source("C:/Users/Jay/Desktop/CompRisk/R/Fit_Model.R")
source("C:/Users/Jay/Desktop/CompRisk/R/Logliklihood.R")
### Raw data
BCraw <- read.csv("C:/Users/jay/Desktop/New Era/July31-2017/July31-... |
9240514dc542e6307906456c7c10705cba753e71 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.database/man/timestreamwrite_create_table.Rd | c3f64ba4593cbd5d2a246384bbc6e5471bbbb28c | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 1,662 | rd | timestreamwrite_create_table.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/timestreamwrite_operations.R
\name{timestreamwrite_create_table}
\alias{timestreamwrite_create_table}
\title{Adds a new table to an existing database in your account}
\usage{
timestreamwrite_create_table(
DatabaseName,
TableName,
Retent... |
931d961137311dbee8e0484ce92ca239838a3eae | bc882e24dd0a08aa93b9a5faa968e1016674d6a2 | /man/insert_na.Rd | 1c7a2ddfa5f12422013cff8493b17d02fb10f1b5 | [
"MIT"
] | permissive | dedenistiawan/sknifedatar | 350ecb9725f8819914a1635f306a9c34bb97a167 | af29fe7e755ba926f4c6203bcb936dc225813310 | refs/heads/master | 2023-08-15T23:24:43.467326 | 2021-07-18T16:35:20 | 2021-07-18T16:35:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 843 | rd | insert_na.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/insert_na.R
\name{insert_na}
\alias{insert_na}
\title{Add NA values to a dataframe}
\usage{
insert_na(.dataset, columns, .p = 0.01, seed = 123)
}
\arguments{
\item{.dataset}{data frame.}
\item{columns}{vector that indicates the name of the c... |
d3a4d1b4fa3e2ba4b18c8c9d512f0912d1824fbc | 4cbbfeef9370d5e74ce8b0934be2ae07d60dbeec | /single proportion hyp test and confidence.R | 6baf1f7f8c726eaa1255902ff0cebb8692438dcc | [] | no_license | sharmash937/R-Basics | a77bdb87bf8897038350dabcf1ea149e73483e11 | 50d1bee922c0f30601fcfb6d310878d223441ae1 | refs/heads/master | 2021-04-09T15:00:33.746993 | 2018-03-16T17:09:52 | 2018-03-16T17:09:52 | 125,541,030 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 288 | r | single proportion hyp test and confidence.R | rm(list = ls())
prop.test(98, 162)
#one tailed test with 90% confidence interval
prop.test(98, 162, alt = "greater", conf.level = 0.90)
#-----------------------------
quakes[1:5,]
mag <- quakes$mag
mag[1:5]
t.test(mag)
t.test(mag, alternative = "greater", mu =4)
|
5700f9a599781a28d1802b935e10759dfb333409 | 29ebe0864a6e8a7c8f8b7a29bab5171460a190f8 | /FinID/server.R | e56117d03412c4dd37ecdb0f1f3d2ee6b1ab19ea | [] | no_license | idelgado2/gws_finID_portal | 81f0e6cd564e113b955573a489dcdc1f6390fe07 | 03291412bab71cd0d222c0d899b5790eb0fb66b4 | refs/heads/master | 2020-06-23T01:50:19.341042 | 2019-08-22T18:41:42 | 2019-08-22T18:41:42 | 198,465,891 | 0 | 0 | null | 2019-07-23T16:12:07 | 2019-07-23T16:12:07 | null | UTF-8 | R | false | false | 14,979 | r | server.R | ### This is the SERVER file for our groundUP file ###
library(shiny)
source("fin_shiny_fxns2.R")
shinyServer(
function(input, output, session){
##~~~~~~~~~~~~~~~~~~~~~~~~##
## VARIABLES HERE ##
##~~~~~~~~~~~~~~~~~~~~~~~~##
phid <- reactiveValues() #reactive value to hold majority o... |
a9db858cee3d24fb1d09b46a9792fc8d2ed1cadf | bb0065dff5734b13ca90030ab52e2dd9b5ddd7ad | /R/aggregation_operators.R | 507a19c6ddb5769f4a5d05e03f9867798c3fc31c | [] | no_license | cran/mongopipe | 15a3aeed5a565078f42eca3c46063a80dcfd0fd2 | 86f4810c8c66c8960449e23dc58061cfda3c8032 | refs/heads/master | 2023-03-01T13:36:12.775198 | 2021-01-20T10:50:06 | 2021-01-20T10:50:06 | 334,162,069 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 683 | r | aggregation_operators.R | #' Conditional expression ($cond)
#'
#' Evaluates a boolean expression to return one
#' of the two specified return expressions.
#'
#' @param test Expression which returns a boolean value.
#' @param yes Return this if the test returns true.
#' @param no Return this if the test returns false.
#'
#' @examples
#' \dontru... |
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