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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9bb227772bbda29527e1b67f94be81797630c22d | ff8222567174568ce8288b69947d8cdc8eefc69b | /Code_Global - Copy/variable_importance.R | 995ee52aa77482a7e8a1d2c40b8d411f39be9a2f | [] | no_license | LarsGorter024/Urban-Expansion-Models | 96705c674abf52e0b4f6955737209822d1ee647b | 512dfe7e3c4fd7069ded3f1541c534830d72cf6a | refs/heads/main | 2023-06-15T14:26:46.577229 | 2021-07-06T20:27:23 | 2021-07-06T20:27:23 | 383,587,979 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,955 | r | variable_importance.R | ##%######################################################%##
# #
#### Variable importance function ####
# #
##%######################################################%##
#' Varia... |
4c08f09ffbf7ec36ba11bdad84feecb0de203f44 | 3706460263d12fa53d7bceec01908f6e121ac43c | /shared/R code/eu/simulation.R | bb08f8d1172c112da9d390e44e02115dc40385f5 | [] | no_license | eugene9212/svm_paper | 083737302af25c25911a304a3d72bd2523e359c6 | 24e7ff72bf1997faa223c83637debd615a78925b | refs/heads/master | 2021-10-26T03:15:17.999988 | 2019-04-10T06:10:18 | 2019-04-10T06:10:18 | 149,591,840 | 0 | 0 | null | null | null | null | UHC | R | false | false | 4,264 | r | simulation.R | rm(list = ls())
# load packages
library(mvtnorm)
library(fda)
# load R codes
setwd('C:/Users/eugene/Desktop/SVM_R/shared/R code/')
source('eu/fsvm.1dim.R')
source('eu/fsvm.1dim.fourier.R')
source('eu/gp.1dim.R')
source('fn/fsvm.pi.path.R')
source('fn/fsvm.sub.pi.path.R')
dyn.load("KernSurf/temp/wsvmqp.dll")
sourceDir... |
6faecba81e10c3a4c7e9717d4f6b0d0bdbd8d188 | 90f0c155b0dca1ae98927c7fa9c591cb3e64d3e6 | /man/final04.Rd | 773aa6c6a77a95b66a81f5a7f2455615ae8a27b2 | [] | no_license | desval/wiod | 03a7f9c7465fa468905dcf8962ddaafe98951809 | e2513994dc252948f59639493cf4124ad316a3d2 | refs/heads/master | 2021-01-11T21:20:52.887336 | 2016-09-28T11:22:45 | 2016-09-28T11:22:45 | 78,770,061 | 1 | 0 | null | 2017-01-12T17:35:30 | 2017-01-12T17:35:30 | null | UTF-8 | R | false | true | 200 | rd | final04.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/wiod.R
\docType{data}
\name{final04}
\alias{final04}
\title{WIOD 2004 final}
\description{
WIOD 2004 final demand data
}
|
997a61f51826152b91f2be5b3b7c20d7417dc2fb | f3e9468bc17c47eba0846e443b9ea73cbc80e5c8 | /man/biglasso.Rd | fc9319d844332949c98b9fe8b438074312156aac | [] | no_license | YaohuiZeng/biglasso | d8922b3669ed497221ca5ae7ad4b0f84464e7655 | 8f6ede2f14d196b1e5940ab570eba5e8befa511d | refs/heads/master | 2023-04-12T07:26:23.678416 | 2023-04-07T14:24:05 | 2023-04-07T14:24:05 | 52,933,812 | 112 | 30 | null | 2022-01-06T02:44:26 | 2016-03-02T04:27:32 | C++ | UTF-8 | R | false | true | 11,271 | rd | biglasso.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/biglasso.R
\name{biglasso}
\alias{biglasso}
\title{Fit lasso penalized regression path for big data}
\usage{
biglasso(
X,
y,
row.idx = 1:nrow(X),
penalty = c("lasso", "ridge", "enet"),
family = c("gaussian", "binomial", "... |
4817650e6330a3902c33af9f8848f85e27f09db5 | 15b4b6ce2eac755d366960dc9d90cb0e0a97f60c | /R/translate-sql-base.r | b5536abb325469d7b810a5bb5b7c00aafbd1d14b | [] | no_license | tlpinney/dplyr | 232ecbac123d8a2f06bf8500c918af97696a76cf | b1ff14e91ddfe29bea2b606cf5ead405f4388ebb | refs/heads/master | 2021-01-17T21:56:20.201548 | 2013-09-25T16:21:07 | 2013-09-25T16:21:07 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,259 | r | translate-sql-base.r | #' @include translate-sql-helpers.r
#' @export
#' @rdname to_sql
base_sql <- new.env(parent = emptyenv())
base_sql$`==` <- sql_infix("=")
base_sql$`!` <- sql_prefix("not")
base_sql$`&` <- sql_infix("and")
base_sql$`&&` <- sql_infix("and")
base_sql$`|` <- sql_infix("or")
base_sql$`||` <- sql_infix(... |
b1a938216f863ce622c75bbcd2a64f93200aa2b6 | 618fb0a3bb4520996baa2fb841342bbbf6d4e57a | /R/interMLE.R | 41cd08e2c3a070c9326dc6601d9e005d8c0a0923 | [] | no_license | cran/AssetCorr | ac654a865db222476bf1648d65f65b663dbf1bb9 | fb249d30060a8722786315638780d8922c05c003 | refs/heads/master | 2021-06-03T23:25:10.299461 | 2021-05-05T14:30:02 | 2021-05-05T14:30:02 | 136,313,140 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,889 | r | interMLE.R | interMLE <-
function(d1,n1,d2,n2,rho1,rho2,B=0, DB=c(0,0), JC=FALSE,CI=-1, plot=FALSE){
Estimate_Bootstrap=NULL
Estimate_Jackknife=NULL
Estimate_Standard=NULL
if(is.numeric(d1)){d1=d1}else{stop("d1 is not numeric")}
if(is.numeric(n1)){n1=n1}else{stop("n1 is not numeric")}
i... |
728cf0a449be3ba7a5a0007f86bb805c6093a51c | ebe9b48ab47175a028db4f87ac8dc9a0382e7b02 | /man/colloc_leipzig.Rd | 27f2f54515d70d51dd0311a993f44774f2bf46a0 | [
"MIT"
] | permissive | gederajeg/corplingr | 21b0a3018901304e1824b58cec114dc0ba01c445 | c260a68260bc499df085ab8fac585209bf657a5a | refs/heads/master | 2021-11-30T02:04:06.974202 | 2021-11-12T13:34:46 | 2021-11-12T13:34:46 | 226,963,221 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,069 | rd | colloc_leipzig.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/corplingr_colloc_leipzig.R
\name{colloc_leipzig}
\alias{colloc_leipzig}
\title{Generate tidyverse-style window-span collocates for the Leipzig Corpora}
\usage{
colloc_leipzig(
leipzig_path = NULL,
leipzig_corpus_list = NULL,
pattern = N... |
e008e5f456c3bc85255f2e5c3c0cf08d5f9c1029 | 73d79d8a9a12652412d04d7e894e9bf7c27a35f6 | /man/gap.binary.Rd | 363f787ca1c1ffa2ffbc122131aeeb90f9ce81ec | [
"Artistic-2.0"
] | permissive | hjanime/clustermap | 133a9899bb9c75977ff4635213fee06b1ceb1db8 | a9af01cc2b2a59d582e0fdc3ade978d3be3ca596 | refs/heads/master | 2020-10-01T20:39:50.347531 | 2019-12-12T14:07:37 | 2019-12-12T14:07:37 | 227,621,177 | 0 | 0 | Artistic-2.0 | 2019-12-12T14:06:26 | 2019-12-12T14:06:25 | null | UTF-8 | R | false | true | 386 | rd | gap.binary.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clustermap.R
\name{gap.binary}
\alias{gap.binary}
\title{gap.binary}
\usage{
gap.binary(X, linkage, B, K = 6)
}
\arguments{
\item{X}{matrix}
\item{linkage}{Linkage for clustering.}
\item{B}{integer.}
\item{K}{integer. Default set to 6.}
}
... |
862f56a76385776fcd63197f677e739e79d99e7e | 92e597e4ffc9b52cfb6b512734fb10c255543d26 | /man/safeColumnBind.Rd | 30e45d6e47cc177c036afae2b9ffc72725f0546d | [
"MIT"
] | permissive | KWB-R/kwb.utils | 3b978dba2a86a01d3c11fee1fbcb965dd15a710d | 0930eaeb9303cd9359892c1403226a73060eed5b | refs/heads/master | 2023-05-12T15:26:14.529039 | 2023-04-21T04:28:29 | 2023-04-21T04:28:29 | 60,531,844 | 9 | 1 | MIT | 2023-04-21T04:28:30 | 2016-06-06T13:52:43 | R | UTF-8 | R | false | true | 694 | rd | safeColumnBind.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/column.R
\name{safeColumnBind}
\alias{safeColumnBind}
\title{"Safe" version of cbind.}
\usage{
safeColumnBind(x1, x2)
}
\arguments{
\item{x1}{first object to be passed to \code{cbind}}
\item{x2}{second object to be passed to \code{cbind}}
}... |
f779ac3aef3ca7675725ef67f8e4c7b7eeabcd52 | 32cb83f49a7218c9a208ad5bef561c3573ed944c | /ALHE/src/tests.R | e229f6b43170117f0015d784c90c556b49dea0f3 | [] | no_license | przemo509/alhe-modified-differential-evolution | f577ceee6b0bb89f3fc7a9f38555f458e8f9bab1 | cd6918733551b46fe5d1aa780a46047597340d65 | refs/heads/master | 2016-09-05T18:36:41.113706 | 2013-04-04T20:34:42 | 2013-04-04T20:34:42 | 32,258,962 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,915 | r | tests.R | # Testy wydajnościowe, czyli o ile lepiej wypada jedno podejście od drugiego.
# 1. testCecCalls() - wołanie funckji dla parametrów przygotowanych w różny sposób
#
# Author: Przemo
###############################################################################
library("cec2005benchmark");
source("../src/utiliti... |
6f8c477b8023c3eee4d04f339d1b128be862c1e4 | e835097454b8559248d5e19c667fba9402d60f29 | /script/subscript_model/model_functions.R | ec36f453bbcd83e0041c38c60cdb762fa429ce6a | [] | no_license | friend1ws/SF3B1_project | a2854ae697716da1611f3955fd5d2e3b8f5cb7ae | 1a7953125e793d1736f67c62970e0f5da4e6dafc | refs/heads/master | 2020-03-31T15:26:46.755868 | 2019-03-06T01:43:57 | 2019-03-06T01:43:57 | 152,337,248 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,791 | r | model_functions.R | library(VGAM)
bb_mloglLikelihood <- function(params, values) {
p_alpha <- params[1]
p_beta <- params[2]
v_n <- values[[1]]
v_k <- values[[2]]
ML <- 0
ML <- ML + sum(lgamma(v_n + 1) - lgamma(v_k + 1) - lgamma(v_n - v_k + 1))
ML <- ML + sum(lgamma(p_alpha + v_k) + lgamma(p_beta + v_n - v_k) - lga... |
bcb3761f9a14f6e178bfac6dffbe06dbbc20b5c6 | f9fb8361c3ab28ba67f6345978ef01ac5a997599 | /Class_Practice/NetworkAnalysis/nba_passing.R | c28d08adb2ed506a3bda22a06b3c05017f576a5c | [] | no_license | sahNarek/CSE_270_Practice | cb14736d0253cf578154ef0b407502235f109a3e | 9347947eae4d532f6cd32dd3482c0b89e7761394 | refs/heads/master | 2020-07-29T15:02:38.199858 | 2019-12-10T18:27:56 | 2019-12-10T18:27:56 | 209,854,014 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,787 | r | nba_passing.R | library(SportsAnalytics270)
library(igraph)
library(network)
library(intergraph)
library(ggplot2)
library(circlize)
load("passing.rda")
load("gsw.rda")
x <- gsw$PLAYER_ID
passing <- passing[passing$PASS_TYPE == "made",]
passing <- passing[passing$PASS_TEAMMATE_PLAYER_ID %in% x,]
i_pass <- graph_from_edgelist(
as.... |
e96b5c7325720e570e4a3a85dc1aefa2dd63ce84 | f757cf4f30fed7d2cdf6176b351160ce14a9f5f6 | /inst/Ratfor/gethgl.r | f8866194c20cfecea4ae852e33a9cd5d4db412e6 | [] | no_license | cran/hmm.discnp | 88942124fca13d158ec445bb3b16b0edb88c3c8e | 059ed3c6e3ad67418e2ee00405d71b0d7e22a85d | refs/heads/master | 2022-10-03T00:38:43.262652 | 2022-09-26T08:10:06 | 2022-09-26T08:10:06 | 17,696,666 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,578 | r | gethgl.r | subroutine gethgl(fy,y,ymiss,tpm,xispd,d1pi,d2pi,kstate,n,
npar,d1p,d2p,m,d1f,d2f,alpha,alphw,a,b,aw,bw,
xlc,ll,grad,hess)
implicit double precision(a-h,o-z)
double precision ll
integer y(n)
integer ymiss(n)
dimension fy(kstate,n)
dimension tpm(kstate,kstate), xispd(kstate)
dime... |
502ae84c29ea29500b5c1173eaa112c38adcc94b | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/pryr/examples/partial.Rd.R | 8ec0552b65cd325f4ac43848cd959c316b51aeb7 | [] | 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 | 903 | r | partial.Rd.R | library(pryr)
### Name: partial
### Title: Partial apply a function, filling in some arguments.
### Aliases: partial
### ** Examples
# Partial is designed to replace the use of anonymous functions for
# filling in function arguments. Instead of:
compact1 <- function(x) Filter(Negate(is.null), x)
# we can write:
co... |
41cbbc9bd9138f119e49fe95fca5bfd432fbae93 | 502161d749fed214a0036450f29895a3b84e1d3d | /eQTL_mapping/3_Run_eigenMT_using_all_CAS_genotype.R | 4af3a458e0b4a136df209f3d05d149e17309a299 | [] | no_license | QinqinHuang/CAS_eQTL | a5e1f16775a135cb20a6a4f809a7691443605246 | 519ac9d3c68631e931cf93fd7616d1dbe398afc2 | refs/heads/master | 2021-05-21T19:11:12.985786 | 2020-10-26T20:12:54 | 2020-10-26T20:12:54 | 252,765,611 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,172 | r | 3_Run_eigenMT_using_all_CAS_genotype.R | #----------------------------------------------
# 2018-05-05
# 1. Prepare Genotype/SNP pos file for each
# chromosome (eigenMT input)
# 2. Run eigenMT.
#
# Davis et al. recommended using genotype data
# for all individuals and running eigenMT once
# to get the estimated number of effective tests;
# don't have to run i... |
c37d0107323458d210e21a8c35ee085bf583f028 | 4f9e68e37bf9130e891136ca90ce8b8faec53b61 | /R/explore_avey.R | 432d8eae816bec68671df621b834e436c295d291 | [] | no_license | robertamezquita/vitech-yhack16 | 218eb3a07f2d8f374197021fb574bc012ab4c60c | 2ccacbb9eb910f001ab406f4694f0e91be0f1f47 | refs/heads/master | 2020-08-04T01:11:34.135757 | 2016-11-12T22:23:06 | 2016-11-12T22:23:06 | 73,532,760 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,918 | r | explore_avey.R | ###################################################################################
## Explore Vitech data ##
###################################################################################
options(stringsAsFactors = FALSE)
##############
## Packages ##
###... |
0515847a1333b31767334fc83c3e226aa4244d3d | f91418dcbd255478e021a6081e60e0416a0a7873 | /R/test_dbi_driver.R | 70a7b9ecbec6d959ea8c7bd7065588951faa8d64 | [
"MIT"
] | permissive | zozlak/useR2015 | f1cb821a958944f1961258c8d17201f93d7f1133 | 88b8deb14975d1d1965b878084507e6d56122520 | refs/heads/master | 2020-04-02T13:47:34.921172 | 2015-07-02T11:35:29 | 2015-07-02T11:35:29 | 38,427,023 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,047 | r | test_dbi_driver.R | #' @title tests a given dbi impelementation
#' @description
#' Given a handler to the database tests capabilities of the DBI driver.
#' @param conn connection to the database opend using DBI::dbConnect()
#' @return list describing driver capabilities - see test_...() functions
#' description
#' @import DBI
#' @impor... |
08b626b8f02fd9d08b3f7ef16d683eca712b63a9 | ce3bc493274116150497e73aa7539fef1c07442a | /man/slackSend.Rd | 0e0e5c69fa5625c08f69f3cc8bedac49316c2cf6 | [] | no_license | laresbernardo/lares | 6c67ff84a60efd53be98d05784a697357bd66626 | 8883d6ef3c3f41d092599ffbdd4c9c352a9becef | refs/heads/main | 2023-08-10T06:26:45.114342 | 2023-07-27T23:47:30 | 2023-07-27T23:48:57 | 141,465,288 | 235 | 61 | null | 2023-07-27T15:58:31 | 2018-07-18T17:04:39 | R | UTF-8 | R | false | true | 1,639 | rd | slackSend.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/slack.R
\name{slackSend}
\alias{slackSend}
\title{Send Slack Message (Webhook)}
\usage{
slackSend(text, title = "", pretext = "", hook = NA, creds = NA)
}
\arguments{
\item{text, title, pretext}{Character. Content on you Slack message.}
\ite... |
14a40f998d18b2b7b01a7a105db6f4a8e97ace7d | cab7c0d9dc98d7d9495a67cb6f94cc3d98eb87a7 | /sampling.R | 86024825439bc26d5fe22d5b2de430a9d5b81dea | [] | no_license | wikimedia-research/SEO-Experiment-SameAsProp | fe478bc1f2b1062ea166a2e68ccb528b12de5c40 | c760b5e685cde8b0eaa3a0be3567d9e1c0f9f366 | refs/heads/master | 2020-04-10T01:05:15.879567 | 2019-03-06T17:10:58 | 2019-03-06T17:10:58 | 160,705,145 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,856 | r | sampling.R | library(glue)
library(magrittr)
snapshot <- "2019-01"
# Excluded from test:
# Indonesian: idwiki
# Portuguese: ptwiki
# Punjabi: pawiki, pnbwiki
# Dutch: nlwiki, nds_nlwiki
# Korean: kowiki
# Bhojpuri: bhwiki
# Cherokee: chrwiki
# Kazakh: kkwiki
# Catalan: cawiki
# French: frwiki
# Yoruba: yowiki
# Kalmyk: xalwiki
ex... |
2f2617019674c35d3b0b2cb209dbbe3906ea0f69 | 5241969456b343da0cafa603f6b373c3bc0863eb | /R/data_CCspec.R | 4511d78e2c063fd77b6d4fd6b2c9e005edfb66dd | [] | no_license | cran/IDmeasurer | 880fc937e1eda6c7ca891eeaf3e516d3a5675032 | c89c6d520a594207d3e099f9edd66287837f4560 | refs/heads/master | 2020-05-21T00:44:51.684846 | 2019-05-09T14:10:10 | 2019-05-09T14:10:10 | 185,838,467 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,357 | r | data_CCspec.R | #' Corncrake, \emph{Crex crex} - spectrum properties
#'
#'\itemize{
#' \item \strong{Species:} Corncrake, \emph{Crex crex}
#' \item \strong{Number of individuals:} 33
#' \item \strong{Number of calls per individual:} 10
#' \item \strong{Number of acoustic variables:} 7
#' \item \strong{Individual identity:}... |
b3a13553201bc03596c14da59cb4dd31f04385a8 | f49961347a44b3137a465182b70f0158885fbca7 | /man/qapi_list_surveys.Rd | e576af53525479a7e901e720048d33bc1a117b55 | [
"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 | 278 | rd | qapi_list_surveys.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api.R
\name{qapi_list_surveys}
\alias{qapi_list_surveys}
\title{qapi_list_surveys}
\usage{
qapi_list_surveys()
}
\value{
DF of surveys
}
\description{
QAPI call to list all surveys that a user owns
}
|
800cb8891e348eae47598fad478dfcf290a3c1ae | 45722b21b67a4c4b734043f266b89c5ae9f30e59 | /plot1.R | c8bdbee54d42ae89eca7f0db24252828c5d4b602 | [] | no_license | amyr206/ExData_Plotting1 | d3e79d356b80e84fbcb880f04841819ef6cbb6a7 | dcc7ca63abda2d098b7bbcb4df7393a34d76ddda | refs/heads/master | 2021-01-18T07:49:20.336074 | 2015-02-08T02:30:35 | 2015-02-08T02:30:35 | 30,278,172 | 0 | 0 | null | 2015-02-04T02:57:56 | 2015-02-04T02:57:56 | null | UTF-8 | R | false | false | 2,081 | r | plot1.R | # Copyright Amy Richards 2015
# PURPOSE:
# --------
# This script fulfills #1 of 4 deliverables for Course Project 1 for the Johns Hopkins
# Coursera Data Science Specialization class, Exploratory Data Analysis.
# Project description:
# https://class.coursera.org/exdata-011/human_grading/view/courses/973505/assessmen... |
6ad302199c1256709c35e7acbfa77ba8ec3c6207 | ae729fb624fe40e003e0440bf42d9c4fdb03127d | /1. R Basics/DataTypes.R | 32b42e786aa15b9d1bf343be19f31e34e21b280b | [] | no_license | GUY625-del/Data-Science-and-Machine-Learning-with-R | bd3afc8bd3e0686685fda075a9f7d79fc65e04b3 | 08cd4f3b19974b8367faa515acad4594267d802b | refs/heads/master | 2023-03-08T04:46:53.950737 | 2021-02-25T01:37:46 | 2021-02-25T01:37:46 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 207 | r | DataTypes.R | # Data Types
# Numeric (float)
a <- 2.2
# Logical (boolean)
b <- TRUE
c <- FALSE
d <- T
e <- F
# Characters (strings)
f <- 'hello'
g <- "hello"
# Data Type
print(class(a))
print(class(b))
print(class(f)) |
33727cb36b86b9c2468aef64cd7a3ca6cc3659e8 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/hyper2/examples/hyper2-package.Rd.R | 6ca37fd62d6c83fa3457a754ad9ea5d035bc77bc | [] | 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 | 388 | r | hyper2-package.Rd.R | library(hyper2)
### Name: hyper2-package
### Title: A generalization of the Dirichlet distribution
### Aliases: hyper2-package hyperdirichlet2
### Keywords: package
### ** Examples
data(chess)
maxp(chess) # MLE for players' strengths
H <- hyper2(pnames=letters[1:5])
H <- H + order_likelihood(rrank(100,5:1)) # pr... |
0c52e76b9105ed554f305a8210359f9130ab16ad | bef5e21ee3a7fb88e714d22e3e21b3a2162335a4 | /scripts/additional_analysis/plots_silencing_classes.R | 7e6b0e14777d56e4ed725009520bd2f2eac7023d | [] | no_license | lisa-sousa/xci_epigenetic_control | 6afbe40a75fca87105a285eadc30e2c4560940b3 | 99b06220923e31c816b16bfd731c6b798939e326 | refs/heads/master | 2021-07-08T11:45:30.531661 | 2020-01-28T15:31:29 | 2020-01-28T15:31:29 | 222,667,602 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,970 | r | plots_silencing_classes.R | ###################################################################################
#libraries
###################################################################################
library(Cairo)
library(ggplot2)
library(cowplot)
library(gridExtra)
library(here)
#########################################################... |
1c0f6091362dbe96df7d4c3bde602dbc4409d3ba | 55700238a9edb9ffcc94ee9eca9e10f4c151457a | /assignment/Homework04/HW04_63130500106/HW04_63130500106.R | fa985d0eff39147c193870efcae76a6d0e0b3f61 | [
"MIT"
] | permissive | kannika2545/027-Quickest-Electric-Cars | d0ddf30a0e39cb6b15497fa80d9bcd81b2833643 | 35b42294de49b039f9d29689f685700f2c468bce | refs/heads/main | 2023-08-29T04:35:39.200572 | 2021-10-27T05:08:10 | 2021-10-27T05:08:10 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,309 | r | HW04_63130500106.R | # Import library
library(readr) #read .csv file
library(dplyr) #for use %>% function
library(DescTools) #use some function find Year from Date column
library(forcats)
library(stringr) #rename column
library(ggplot2) #use plot graph
library(scales) #use find percent
#Import dataset
Orders <- r... |
d445d334c11c30cb3503c7b924050d3c70585fa1 | 2f15b2dc16de0471e7bee43f6739b6ad8522c81d | /man/replace_dimension.Rd | 12668812cc67e506e106099326a3eb5abacca2c9 | [
"MIT"
] | permissive | billster45/starschemar | 45566be916c95778727a3add3239143d52796aa9 | 5f7e0201494a36f4833f320e4b9535ad02b9bdc1 | refs/heads/master | 2022-12-20T13:45:06.773852 | 2020-09-26T03:44:12 | 2020-09-26T03:44:12 | 298,796,838 | 1 | 0 | NOASSERTION | 2020-09-26T11:10:30 | 2020-09-26T11:10:30 | null | UTF-8 | R | false | true | 697 | rd | replace_dimension.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/star_schema_replace_dimension.R
\name{replace_dimension}
\alias{replace_dimension}
\alias{replace_dimension.star_schema}
\title{Replace a star schema dimension}
\usage{
replace_dimension(st, name, dimension)
\method{replace_dimension}{star_s... |
82be792a4181f7b6c7b6fbfcee5cdc10214f7108 | c7a0d98d6246d238811f9ad271109748e0206d0c | /R/n3_freq.r | edb15a9a5ca7e5f8a2ddddc8b1b80a57be5b0776 | [
"MIT"
] | permissive | HVoltBb/kodonz | 68e42eaf260ccace9bf2b5d2aecb021d0142b604 | 5fd777eca9f07a983c485be76de981a52efa42f5 | refs/heads/master | 2020-04-09T16:01:08.607738 | 2020-01-09T18:35:08 | 2020-01-09T18:35:08 | 160,441,942 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 786 | r | n3_freq.r | #' Nucleotide at the third position of the codon
#'
#' Calculates the nucleotide frequency at the third position of the codon
#' @param x a list of KZsqns objects.
#' @return a matrix of nucleotide composition at the third position
#' @export
n3_freq <- function(x){
if(!is.list(x)){
cat("Just one perhap... |
0fb1005c7732e93b90bad2e42f14b7882b90139a | cf05cffc62ce53e1dd12d1e1ed71a107c0e1f63b | /R/methods-plot.R | e7595b29b475a03f4da9ae28628624d22a6b82b2 | [] | no_license | cran/UncerIn2 | 418fc36b97be0a7b285a28e9d153b1a16c2b48d3 | 1d87b9b175f8f3bb9c4669ef30c9be8cd833bd99 | refs/heads/master | 2021-01-10T13:12:18.757019 | 2015-11-24T18:37:19 | 2015-11-24T18:37:19 | 48,090,721 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,877 | r | methods-plot.R | ## This file is part of the UncertaintyInterpolation 2.0 package.
##
## Copyright 2015 Tomas Burian
#' @title
#' Plotting S4 class UncertainInterpolation
#'
#' @description
#' This function provides the plotting of S4 object class \code{UncertainInterpolation}.
#'
#' @param object Input data type of S4 ob... |
df325ff89dc1f69abfbc10014579feb38523d67d | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/easyformatr/examples/easy_format.Rd.R | 8423e96ec1c389cbb11f0bbe4af9bf83abd58049 | [] | 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 | 336 | r | easy_format.Rd.R | library(easyformatr)
### Name: easy_format
### Title: Easily build format strings
### Aliases: easy_format
### ** Examples
easy_format(year, month, day, integer, octal, double)
easy_format(decimal(second) )
easy_format(before_decimal(double, 3) )
easy_format(month,
roman(list(day,
... |
9e4b562043992c18b6cdfc409fe7e4bcbc3f65c7 | 6c6334d3d716da34aae8079f7f673c2324ddf480 | /tests/testthat/test-function-get_elements_by_type.R | a5fa1e60effed351c462904fbab6c1a75c091037 | [
"MIT"
] | permissive | KWB-R/kwb.code | 94f80f51b2977cd0c0fda094f3c7796e1cea95cf | bc81324403e3881124fa2230c023807eba26e32d | refs/heads/master | 2023-08-17T07:40:18.766253 | 2023-07-15T05:50:50 | 2023-07-15T05:50:50 | 140,209,624 | 0 | 0 | MIT | 2023-08-06T22:33:32 | 2018-07-08T23:23:47 | R | UTF-8 | R | false | false | 305 | r | test-function-get_elements_by_type.R | test_that("get_elements_by_type() works", {
f <- function(...) kwb.code:::get_elements_by_type(..., dbg = FALSE)
expect_error(f())
x <- parse(text = "square <- function(x) x * x")
result <- f(x)
expect_type(result, "list")
expect_true("language|call|<-|3|" %in% names(result))
})
|
64ec6f4d073d5f95025a3295b5fe859a581cb10e | c306b1271e76b4e72520afcbf5652dc4c841c32b | /man/get_my_stancode.Rd | ef3c436b5685173f2e191b1c0d506bbd63500f10 | [] | no_license | EoinTravers/mystanmodels | 0e91f17d620f01e62e4efcba9f91004b76569477 | 1cb8a9a3fe734726563960d161704030e728af09 | refs/heads/master | 2022-12-28T04:04:54.010410 | 2020-10-09T11:23:14 | 2020-10-09T11:23:14 | 302,617,809 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 278 | rd | get_my_stancode.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/main.R
\name{get_my_stancode}
\alias{get_my_stancode}
\title{Get the stan code for the model specified}
\usage{
get_my_stancode(model_name)
}
\description{
Get the stan code for the model specified
}
|
7825ff754a74a7ab41508cbb1d49684ccb543be9 | ecf3302ee7a156bf04f05d0e48f1bf8e9565e642 | /R/fmi_stations.R | dcc866def92344b90efb4e5038ce0ca30d3f3706 | [
"MIT",
"CC-BY-4.0"
] | permissive | rOpenGov/fmi2 | cbe82285b5fcb096cdc2da3ce0de03905f308615 | 5194d67c282f40acb4c9f6a1c71bcbf5b32d357e | refs/heads/master | 2023-07-25T05:54:43.900512 | 2023-07-13T13:29:52 | 2023-07-13T13:29:52 | 144,606,564 | 8 | 3 | MIT | 2020-11-23T20:13:22 | 2018-08-13T16:36:08 | R | UTF-8 | R | false | false | 2,516 | r | fmi_stations.R | # function fmi_station()
#' Get a table of active FMI observation stations.
#'
#' Data is retrieved using a FMI API stored query.
#'
#' @return a \code{tibble} of active observation stations
#'
#' @seealso \url{https://en.ilmatieteenlaitos.fi/observation-stations}
#'
#' @author Joona Lehtomaki \email{joona.lehtomaki@@... |
901f8308dd2e576e238568eea5ad8c47e711332f | aeae7b5585706a01f0cb70ba92920cf4054e80ce | /man/cross_paste0.Rd | 6218c5a2f6b26eb1af31d56210eb2ae8ee490674 | [
"MIT"
] | permissive | jixing475/manuscriptsR | d3c395511cb34571e770de08126f5c213eb06910 | f56670fb42ac04f4fc3aaa7ea1a9c7f60c7c77a8 | refs/heads/master | 2023-05-01T12:07:34.129853 | 2021-05-20T01:48:11 | 2021-05-20T01:48:11 | 299,823,539 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 854 | rd | cross_paste0.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils.R
\name{cross_paste0}
\alias{cross_paste0}
\title{Create a concatenation cross product of chracter vectors}
\usage{
cross_paste0(chars1, chars2)
}
\arguments{
\item{chars1}{A character vector of string prefixes}
\item{chars2}{A charact... |
1888e1ea4dc28be5d4542c6351d2b2304c2ec3ec | ad9063f4e1d86ec15e194ccd7f623d50b410029b | /Analysis.R | 5dffc6eb7beffb996c6b2ae5340efa3004b7e0fe | [] | no_license | M-Pass/ConceptualSpan | e9bfc7b3e8a851710f3485e6b2f59a4fdd60f20f | 8861de55b53942729511e4447e9324a0a9fc81f4 | refs/heads/master | 2022-11-29T15:46:30.425402 | 2020-07-31T07:40:47 | 2020-07-31T07:40:47 | 283,974,106 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,138 | r | Analysis.R | # Environment setting
rm(list=ls())
library(psych)
library(lavaan)
# Loading Conceptual span data
data <- read.csv("CSitems.csv")
### FACTOR ANALYSIS ###
data_CFA <- data[,4:13]
model <- "F=~ item1 + item2 + item3 + item4 + item5 + item6 + item7 + item8 + item9 + item10
"
fit <- cfa(model, data=dat... |
54179fb63d3c48b4e02d193d2dc94f71154dff0f | 75db022357f0aaff30d419c13eafb9dddfce885a | /inst/IP/comparisonOfDaysFishedAcrossYears.r | 449ee8fcfc960ec15b03b85c0ccb244075f0535d | [] | no_license | LobsterScience/bio.lobster | d4c553f0f55f561bb9f9cd4fac52c585e9cd16f8 | b2af955291cb70c2d994e58fd99d68c6d7907181 | refs/heads/master | 2023-09-01T00:12:23.064363 | 2023-08-23T16:34:12 | 2023-08-23T16:34:12 | 60,636,005 | 11 | 5 | null | 2017-01-20T14:35:09 | 2016-06-07T18:18:28 | R | UTF-8 | R | false | false | 1,009 | r | comparisonOfDaysFishedAcrossYears.r | require(bio.lobster)
require(bio.utilities)
a = lobster.db('process.logs.unfiltered')
aa = aggregate(DATE_FISHED~LFA+SYEAR+VESSEL_NAME+LICENCE_ID,data=a,FUN=function(x) length(unique(x)))
#Potential Fishings Days
dat = lobster.db('season.dates')
dat$DF = dat$END_DATE - dat$START_DATE
dF = aggregate(DF~SYEAR+LFA,data... |
d5647b83ac8fd2324b33569769f84dd30048180c | 1ded44fc1e8ed7f621c8d19654b7efa910d0610f | /man/Kronspec.Rd | 39e01f6120c120a193c06a8183775096f51be967 | [] | no_license | cran/MTS | a0099c7b4ef497190e2088fb6d9abbf1cee26edb | a78f81c43d0ac4d54b2b58c0b427c5d7286dd89e | refs/heads/master | 2023-04-21T22:42:23.122748 | 2022-04-11T13:32:30 | 2022-04-11T13:32:30 | 17,680,790 | 6 | 9 | null | 2023-04-08T13:17:28 | 2014-03-12T19:31:12 | R | UTF-8 | R | false | false | 773 | rd | Kronspec.Rd | \name{Kronspec}
\alias{Kronspec}
\title{Kronecler Index Specification
}
\description{For a given set of Kronecker indices, the program
specifies a VARMA model. It gives details of parameter specification.
}
\usage{
Kronspec(kdx, output = TRUE)
}
\arguments{
\item{kdx}{A vector of Kronecker indices
}
\... |
3c06c1fc3126911714dd8203c69002dcf5977cd3 | 58ed380e48045a368c06701b61aac8fac41419e7 | /man/fit_pi.Rd | 7631df4ed7f95c48b75e4f9ee4f41616faedf741 | [
"MIT"
] | permissive | systats/deeplyr | 5c6419316ce23eb1569b0189a18816f81bb91b94 | 3248e73a24527a7717a01e0e5c8e3021d5b8b823 | refs/heads/master | 2021-07-05T04:40:23.502291 | 2020-10-02T14:49:12 | 2020-10-02T14:49:12 | 185,884,771 | 11 | 0 | null | null | null | null | UTF-8 | R | false | true | 177 | rd | fit_pi.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/api_pi.R
\name{fit_pi}
\alias{fit_pi}
\title{fit_pi}
\usage{
fit_pi(self)
}
\description{
fit_pi
}
|
83b80ab1b8748cc4041bf75bff7d653f7e2cb83c | 6a54ede8ce395cd20b3cf027fea709ff454d3511 | /Lecture 4/04.RawCode.R | 53a40671e4436f8c58fc21f8a9242b2859e1a932 | [] | no_license | zmarion1/BayesianGymnasium2018 | 6718471839bc13c8ba304cd3f9a4eb6f48a5293b | 7d50d14ab21ff225b125c251ae4a0c865e1c0a3f | refs/heads/master | 2021-05-05T06:29:52.086947 | 2018-05-02T15:38:31 | 2018-05-02T15:38:31 | 118,805,349 | 0 | 4 | null | null | null | null | UTF-8 | R | false | false | 815 | r | 04.RawCode.R | library(shinystan)
library(rstan)
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores())
setwd("YOUR DIRECTORY")
obs <- rep(c(1,0), times=c(7,3)) # our Bernoulli observations
nObs <- length(obs) # number of observations
alpha <- 1 # Prior for alpha
beta <- 1 ... |
bc41077e26de48e7656c3137cf9df9418ec0786c | 5314fc7db5f93546cb11bebd526f75d95db2fa0c | /solutions/day_04.R | c7dedcee9b28c785d676cf3a96ac5c9d57f85d52 | [] | no_license | vicnett/AOC-2020 | 36dbb8a3f2e019614bc78353b551eaf033147da2 | a305e72b1262042e31e8a8072e23495e42bbe3f1 | refs/heads/main | 2023-02-03T20:17:16.176421 | 2020-12-23T01:04:43 | 2020-12-23T01:04:43 | 317,705,813 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,459 | r | day_04.R | # Advent of code 2020
# Day 4
# Load libraries
library(tidyverse)
# Set working directory to file location
setwd(dirname(rstudioapi::getActiveDocumentContext()$path))
# Load input
inputData <- read_file("../inputs/day_04")
# Part 1
# Input is "passport" data.
# Determine which passports have all required fields.... |
caafc61eabdb293397a0c539ac94d7cc9d03a854 | a69d9dc1182b184f876435733db2da4f33910811 | /man/param.mode.Rd | a1358317b9f48f5e2fc7cc9f6d09b84d432c0d5d | [] | no_license | taylors2/PeriodCPT | 8d829ab01571da214dbff6d52bff958561413dfe | fd8c5f1f9fa863f876ac74748558c4a84f3ecf25 | refs/heads/master | 2022-11-26T03:49:27.828966 | 2020-07-30T17:02:21 | 2020-07-30T17:02:21 | 259,919,812 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 643 | rd | param.mode.Rd | \name{param.mode}
\alias{param.mode}
\title{
Generic Function -- param.mode
}
\description{
Generic function
}
\usage{
param.mode(object)
}
\arguments{
\item{object}{
Depending on the class of \code{object} depends on the method used (and if one exists)
}
}
\details{
Generic Function
}
\value{
Depends... |
24d29153304d330e46e99496fea0e5e746847868 | aac60cb63641ac946f473d702eddcdc1bbc9f940 | /man/getExpData.Rd | a9779f92991468a657ba8414f146e7febb27cb1b | [] | no_license | bhklab/RPharmacoDB | 0a95fa40ad604825d3c11073817e9295cc7e2363 | 13b221943bd6568e8d31d4c7a323de38e459d772 | refs/heads/master | 2020-04-10T23:41:45.822032 | 2015-12-10T03:11:19 | 2015-12-10T03:11:19 | 41,569,735 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,670 | rd | getExpData.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/getData.R
\name{getExpData}
\alias{getExpData}
\title{Obtain a data set according to a study name}
\usage{
getExpData(cellline = NULL, drug = NULL, summary = FALSE, stats = NULL)
}
\arguments{
\item{cellline}{[vector] vector of cell l... |
66852ee2b56759dec3b3234ebbdff54dd75562d6 | cba027bab5eb9c7c26ffce776923eab4cafd1d8c | /Scripts/Miscellaneous/Wilcox_test.r | 0ad1a94b6c093ddb9d31ca1e0fc1fe5cfa2dd434 | [] | no_license | antonio-mastropaolo/automatic-variable-renaming | 733b34e13e306e3ee1e9b82b75b67195c35c678a | f808db3a70d86ed4e8fe9eae5fb6bd65e6a23b03 | refs/heads/main | 2023-04-18T17:35:52.915552 | 2022-12-27T09:40:59 | 2022-12-27T09:40:59 | 440,521,300 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,233 | r | Wilcox_test.r | library(effsize)
setwd(paste("statistical-Analysis/Box_Plot/NGRAM/","Large-Scale",sep=""))
data<-read.csv("data_reduced.csv",header=TRUE)
perfect <- data[which(data["IS_PERFECT"] == TRUE),]
wrong <- data[which(data["IS_PERFECT"] == FALSE),]
#p-value < 0.05 to be significant
#Tokens
wilcox.test(perfect$Tokens,wron... |
e0e5ac433ea1349e8514aff7bbef669ed502a657 | 6f9ab236999fff566b0ed76f6fc2146d63e3f7f1 | /rotations/R/preliminary.R | ce8ef8f13caaba53f32208f613f956a1a390ba8d | [
"MIT"
] | permissive | stanfill/rotationsC | d4733140b6e40c61b2d9312474c1a8786f1974fb | 66722f095a68d81e506c29cfac7d4a8a69e664cf | refs/heads/master | 2022-07-22T01:17:54.917073 | 2022-06-24T21:27:24 | 2022-06-24T21:27:24 | 9,582,475 | 0 | 3 | null | 2021-03-11T21:43:23 | 2013-04-21T16:51:07 | C++ | UTF-8 | R | false | false | 18,770 | r | preliminary.R | #' Rotational distance
#'
#' Calculate the extrinsic or intrinsic distance between two rotations.
#'
#' This function will calculate the intrinsic (Riemannian) or extrinsic
#' (Euclidean) distance between two rotations. \code{R2} and \code{Q2} are set
#' to the identity rotations by default. For rotations \eqn{R_1}{R1... |
cb5889970bb86075a8ca5cf6c69c082ddbcaa2d1 | cab285249f5e5e1fbd40897c522870ff97031a7b | /man/bowlerEconRate.Rd | af3888403e176b33795656be4414642606dbe60e | [] | no_license | dharmang/cricketr | 61bd5a107fb143d471f36e256132b6f10092891a | 4e09953d4f9d427771ce928bf8b815398a83206c | refs/heads/master | 2020-05-26T09:22:51.262187 | 2019-03-08T01:24:46 | 2019-03-08T01:24:46 | 188,184,725 | 1 | 0 | null | 2019-05-23T07:36:12 | 2019-05-23T07:36:11 | null | UTF-8 | R | false | false | 1,553 | rd | bowlerEconRate.Rd | \name{bowlerEconRate}
\alias{bowlerEconRate}
\title{
Compute and plot the Mean Economy Rate versus wickets taken
}
\description{
This function computes the mean economy rate for the wickets taken and plot this
}
\usage{
bowlerEconRate(file, name = "A Bowler")
}
%- maybe also 'usage' for other objects documented here.
\... |
591b95107a05f5c12a0480d28fb60a08b13ee8ff | 2bec5a52ce1fb3266e72f8fbeb5226b025584a16 | /ProbReco/man/sim_hierarchy.Rd | 914f9e147ab5919c5d826e9a8541b87e25361a4b | [] | no_license | akhikolla/InformationHouse | 4e45b11df18dee47519e917fcf0a869a77661fce | c0daab1e3f2827fd08aa5c31127fadae3f001948 | refs/heads/master | 2023-02-12T19:00:20.752555 | 2020-12-31T20:59:23 | 2020-12-31T20:59:23 | 325,589,503 | 9 | 2 | null | null | null | null | UTF-8 | R | false | true | 625 | rd | sim_hierarchy.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.R
\docType{data}
\name{sim_hierarchy}
\alias{sim_hierarchy}
\title{Synthetic hierarchical data from stationary Gaussian ARMA models.}
\format{
A tibble with a time index Time and one column for each of the seven variables in
the hierarc... |
1c0d746d80259280fb4a9f240e9abfff94e2abf3 | 24cc0a2786cef571aeceffa4008fe0cf7c14b6c6 | /script/Bil69_NA_plot_enrich.R | 3a11b572f7d3a7cc60a60c237c1cc6dd89066fbb | [] | no_license | nicwulab/N2_evol_contingency | 568c94c8667ebbb994d2feb50c322f04cea4666c | 039816375a249bb3d089556557baad5ddffdda27 | refs/heads/main | 2023-04-11T18:35:54.918988 | 2022-10-11T15:32:47 | 2022-10-11T15:32:47 | 376,881,476 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,347 | r | Bil69_NA_plot_enrich.R | #R code
library(ggplot2)
library(scales)
library(RColorBrewer)
library(readr)
library(tidyr)
library(reshape)
library(stringr)
library(dplyr)
library(ggrepel)
library(gridExtra)
require(cowplot)
PlotCompareFit_Rep <- function(Bil69_data, graphname){
textsize <- 8
p <- ggplot() +
geom_rect(data=NULL,... |
2308e5b477e5281c8cdc5c3723401b7678df7bde | 15f94600eb4d598d1a46626d3320eb388bd3d914 | /cachematrix.R | 53e15b3aa269a14c63912a50b41afd04ed775017 | [] | no_license | Akshaydalal2511/ProgrammingAssignment2 | caecffb223ab975eb651b308d668fc1db50eaad5 | a8c63b960369d6ff901639fe8fc5a4b67c9a2377 | refs/heads/master | 2021-05-01T07:37:41.214807 | 2018-02-12T10:53:20 | 2018-02-12T10:53:20 | 121,159,649 | 0 | 0 | null | 2018-02-11T19:36:07 | 2018-02-11T19:36:07 | null | UTF-8 | R | false | false | 1,032 | r | cachematrix.R | ## Caching the inverse of a Matrix
## First Function Caches the matrix and its inverse
## If the same matrix is asked inverse of second function caches the inverse
## rather than recomputing.
## Caches the matrix and its inverse and returns a list
makeCacheMatrix <- function(x = matrix()) {
i <- NULL
set <- f... |
8b3e666d92bf4698f249f5d8a3ca83d5fd7bb0d8 | dd8fd76523c4338755517e437e7e9b57bf8e3e15 | /scripts/build_sce.R | af27c91bf90966bc8d19b774689a099f570554b4 | [] | no_license | jperales/data_KuppeIbrahim2020 | d887eba107c9d2227be03659271f45be55019170 | 6919eec100906d0d4dac357788d75118fd34777f | refs/heads/main | 2023-03-07T12:28:55.710467 | 2021-02-22T10:39:04 | 2021-02-22T10:39:04 | 341,155,912 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,467 | r | build_sce.R | ## Setting the environment
### Internal variables
set.seed(1234)
OUTDIR <- "./data/CD10negative/"
### Load libraries
library("Matrix")
library("SingleCellExperiment")
library("scran")
## Load data
dat <- Matrix::readMM("./data/CD10negative/kidneyMap_UMI_counts.mtx")
rowDat <- read.table("./data/CD10negative/kidneyMap... |
a68da64ec93d835f5737a814cec4e47ab8cf8a65 | 5898e63d46de41245d5018c298de944559d70825 | /kili_nov2013/map/src/map.R | c64cb874969f17a602d5552277535ed9d4ac22a2 | [] | no_license | fdetsch/snippets | d7de9ddd77376a40b68912e39c107a363db15cc6 | 8085d950cb247d6e8068ed72201a76c525ef0d5e | refs/heads/master | 2021-01-17T09:30:19.170821 | 2017-02-13T13:26:24 | 2017-02-13T13:26:24 | 10,215,881 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 6,783 | r | map.R | ### Environmental settings
# Clear workspace
rm(list = ls(all = T))
# Set working directory
switch(Sys.info()[["sysname"]],
"Linux" = setwd("/media/permanent/phd/kili_nov2013/map"),
"Windows" = setwd("E:/phd/kili_nov2013/map"))
# Load required packages
lib <- c("OpenStreetMap", "raster", "rgdal", "do... |
c2ace96c4a4fe64aa19b12b11345ef2e1f105896 | 796b5a173db8207364467bccbc3459d0adb30e57 | /man/uscolleges.Rd | 9a58b6cbe5d39e730dd1922cf086772275dfcc3d | [] | no_license | jonthegeek/uscolleges | 296a16a8bddd93aef573efa030bd9198da77e6ec | ebf048511e3d5f7aab922a68c282f30676400b4e | refs/heads/master | 2020-03-07T13:35:54.288245 | 2018-04-03T14:18:06 | 2018-04-03T14:18:06 | 127,505,113 | 6 | 3 | null | null | null | null | UTF-8 | R | false | true | 654 | rd | uscolleges.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/01data_definitions.R
\docType{data}
\name{uscolleges}
\alias{uscolleges}
\title{Tidy US college scorecard data}
\format{A tibble with 7593 observations of colleges in the United States, and
622 variables. The variables are described ... |
479b00416b2bb16ad12e901d7497d7105fbc828a | efa104bf0b9232288455017b8c12b50cf62c3f17 | /plot1.R | 36be9977325241b63e061fb13474f23043145047 | [] | no_license | jai-angle/ExData_Plotting1 | c9a51ce85b6c354aa00f4f34bad41e815f70202f | db3b2e269279986a5438f5de9f8ee11a79a9e43e | refs/heads/master | 2021-01-17T21:38:27.348829 | 2016-05-19T12:02:24 | 2016-05-19T12:02:24 | 59,017,879 | 0 | 0 | null | 2016-05-17T11:51:13 | 2016-05-17T11:51:13 | null | UTF-8 | R | false | false | 822 | r | plot1.R | ## This is the first of the plot assignment.
## It plots the histogram based on Global Active Power data from the household_power_consumption.txt file.
filetoread <- "./ExData_Plotting1Data/household_power_consumption.txt"
##get all the data first
alldata <- read.table(filetoread, header = T, sep = ";", na.strings = ... |
614a68be24206902c8a4195ab063f4bf6ff0ebda | 6a28ba69be875841ddc9e71ca6af5956110efcb2 | /An_Introduction_To_Statistical_Methods_And_Data_Analysis_by_R_Lyman_Ott_And_Michael_Longnecker/CH3/EX3.6/Ex3_6.r | de4780a4ed349d53318d51065d0e7c1681601ac7 | [] | permissive | FOSSEE/R_TBC_Uploads | 1ea929010b46babb1842b3efe0ed34be0deea3c0 | 8ab94daf80307aee399c246682cb79ccf6e9c282 | refs/heads/master | 2023-04-15T04:36:13.331525 | 2023-03-15T18:39:42 | 2023-03-15T18:39:42 | 212,745,783 | 0 | 3 | MIT | 2019-10-04T06:57:33 | 2019-10-04T05:57:19 | null | UTF-8 | R | false | false | 448 | r | Ex3_6.r | # Page No. 83
ClassInterval <- c("16.25-18.75", "18.75-21.25", "21.25-23.75","23.75-26.25", "26.25-28.75", " 28.75-31.25", " 31.25-33.75", "33.75-36.25","36.25-38.75", "38.75- 41.25", "41.25- 43.75")
freq <- c( 2,7,7,14,17,24,11,11,3,3,1)
mid_interval<- c(17.5,20.0,22.5,25.0,27.5,30.0,32.5,35.0,37.5,40.0,42.5)
fmi<-f... |
5a312e99c8c76ff864919a369a356352a5bf30bb | 583c2374b676c60cdb64ffae1d48e0d0f2cf5e7f | /man/BIC.mmlcr.Rd | 542dd47c18907cb3e7696353b15d7f6dcd765891 | [] | no_license | cran/mmlcr | cf8e1c575b226a20484158f16998ca05bb4573a9 | d4426714daa734cb546f34441719a80e38344ccc | refs/heads/master | 2021-01-21T11:45:59.129520 | 2006-04-10T00:00:00 | 2006-04-10T00:00:00 | 17,719,035 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,548 | rd | BIC.mmlcr.Rd |
\name{BIC.mmlcr}
\title{Bayesian Information Criterion}
\usage{
\method{BIC}{mmlcr}(object, ...)
}
\alias{BIC.mmlcr}
\arguments{
\item{object}{a fitted mmlcr object.}
\item{\dots}{optional fitted model objects.}
}
\description{
This generic function calculates the Bayesian information criterion,
also known as S... |
81513df1a005646ed3b83ee91c0297071920d394 | 2bec5a52ce1fb3266e72f8fbeb5226b025584a16 | /steps/man/habitat_dynamics_functions.Rd | 60b0bc72d8a1463245d92a33f24912f2874407ad | [] | no_license | akhikolla/InformationHouse | 4e45b11df18dee47519e917fcf0a869a77661fce | c0daab1e3f2827fd08aa5c31127fadae3f001948 | refs/heads/master | 2023-02-12T19:00:20.752555 | 2020-12-31T20:59:23 | 2020-12-31T20:59:23 | 325,589,503 | 9 | 2 | null | null | null | null | UTF-8 | R | false | true | 563 | rd | habitat_dynamics_functions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/habitat_dynamics-functions.R
\name{habitat_dynamics_functions}
\alias{habitat_dynamics_functions}
\title{Functions to modify the habitat in a landscape object.}
\description{
Pre-defined functions to operate on habitat suitability (and carryi... |
87171ba449e95c26ec4a6346c6e848b905ff676b | d8a5e3b9eef3c76bb7ca64d29ef2746cebd4c542 | /man/isWhitespace.Rd | c41264711513653458737b3961b13c46258d0d06 | [] | no_license | cran/qmrparser | 0539ad4bf5b97039e50b2bffa16c3012899c6134 | bb1bb2b50b358d79f6400d521f995e1d2a55a784 | refs/heads/master | 2022-05-09T03:49:13.511049 | 2022-04-23T23:00:05 | 2022-04-23T23:00:05 | 17,698,845 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 485 | rd | isWhitespace.Rd | %do not edit, edit noweb/qmrparser.nw
\name{isWhitespace}
\alias{isWhitespace}
\title{
Is it a white space?
}
\description{
Checks whether a character belongs to the set \{blank, tabulator, new line, carriage return, page break \}.
}
\usage{
isWhitespace(ch)
}
\arguments{
\item{ch}{character to be checked}
}
\value{
TR... |
a53eab8c429577683af2190aad7da9045ef34438 | 387511286d1a2927a596847a423ff63d4aa08782 | /kml2ndvi.R | 7377136e680579babb4c480d1d973b4883ace431 | [] | no_license | ahernan/kml2ndvi | 00590b14c06b845182536516be9cf2dfbe966597 | 645e82b9b106a11aa84e529789c348c4ca00dc48 | refs/heads/master | 2021-01-12T11:15:28.537884 | 2016-11-06T13:43:53 | 2016-11-06T13:43:53 | 72,789,377 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,627 | r | kml2ndvi.R |
#------------------- METADATA -------------------
# Descripcion del Script: Retorna un recorte y un reporte de un raster
# a partir de un poligono vectorial
# Raster: Se considera del producto MOD13Q1 de MODIS la banda NDVI y EVI.
# En este caso recortes proporcionados por Patricio Or... |
be22b15684a08f7ad4186d9df9b824aa2cd4ff60 | b706bd176b23ade74d16d0997ea209a2a940f688 | /fikspdfs.R | f5e492ed82091ca2a20c417cb79edce82a7dd4a9 | [] | no_license | chrilur/brassranking | 7920a91e174845b2d847273bb97bc03ae7eee9ca | f236745fe70c552d6081c716a06c4a05f2134bf9 | refs/heads/master | 2021-01-22T06:07:05.848172 | 2017-02-12T20:40:41 | 2017-02-12T20:40:41 | 81,736,132 | 0 | 0 | null | null | null | null | MacCentralEurope | R | false | false | 736 | r | fikspdfs.R | setwd("C:\\Users\\n633164\\Documents\\R\\brassrank")
library(stringr)
fiks.nm <- function(navn, Śr, div, konk) {
fil <- read.csv(navn, stringsAsFactors = FALSE, header=FALSE, fileEncoding="UTF-8")
fil[,1] <- gsub("[0-9]", "", fil[,1])
fil[,1] <- gsub("\\.", "", fil[,1])
fil[,1] <- gsub("^\\s+|\\s+$", ""... |
df8d14bd89461a63b31066c7ebad954263f0d574 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/crunch/examples/loadDataset.Rd.R | 48dd522d9cff3da0ce7362d08963f942db427e7d | [] | 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 | 211 | r | loadDataset.Rd.R | library(crunch)
### Name: loadDataset
### Title: Load a Crunch Dataset
### Aliases: loadDataset
### ** Examples
## Not run:
##D dsName <- listDatasets()[1]
##D ds <- loadDatasets(dsName)
## End(Not run)
|
47a5f54ad8126b81c30d6f94095c581040c773de | c6ccaabb627f8b29a7cb32c5b3fe19b72d07e188 | /R/swarm.R | 97c871a89d3ae1e7eba818eedadc6f8c14616342 | [] | no_license | cran/particle.swarm.optimisation | 5f5a14944f95bfa095c6088f9fbbbe971095ad42 | e8d7e4b31817a8be4c2e2a52437397c445ee01a8 | refs/heads/master | 2023-04-30T00:25:00.363880 | 2021-05-21T07:00:02 | 2021-05-21T07:00:02 | 369,583,860 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 24,659 | r | swarm.R | #' @title Swarm
#' @description Particle Swarm, used to launch the Particle Swarm Optimisation, The PSO is used to maximise the fitness.
#' @import rgl
#' @importFrom R6 R6Class
#' @export
#' @examples
#' # In this example we use the PSO to solve the following equation:
#' # a * 5 + b * 25 + 10 = 15
#'
#' fitness_func... |
0417d23457c60d2e6e28fdb5ef0d7547abbaa00f | 2e5cc9b036338bd6b257e1c95f69c4edd6db6b4d | /Data_Analytcs_practice/tidyr_dplyr.R | b36f6b1995434b0ab3791b14af028487503298a0 | [] | no_license | abhik-ghosh/R-Labs | c808874eb8665b844f082bc8531a677e48baca6d | 53dd985c42d97f3dc49d8a65c158cad257097e9c | refs/heads/master | 2020-03-12T07:23:04.073530 | 2018-04-28T03:31:30 | 2018-04-28T03:31:30 | 130,505,020 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 925 | r | tidyr_dplyr.R | #install.packages("dplyr", dependencies=TRUE, INSTALL_opts = c('--no-lock'))
#install.packages("tidyr", dependencies=TRUE, INSTALL_opts = c('--no-lock'))
#library("dplyr", lib.loc="~/R/x86_64-pc-linux-gnu-library/3.2")
#library("tidyr", lib.loc="~/R/x86_64-pc-linux-gnu-library/3.2")
rm(list=ls())
iris_data <- iris
#... |
75edd2cb979946e607879a2317d7c7f2b03d5d56 | 52075930747540d6815040bdf3b9ceca5c7387d7 | /coursera/data_science_specialization/r/assignments/w4_hospital/rankall.R | 9f9be0841e64a69f6bdc6b032627bd9126fa31a8 | [] | no_license | lorenzoconti/courses | d03b83d8c4b33c161dd49cd01c670c37cc459932 | 05664e938007a59f4214132e707fd185437c7819 | refs/heads/master | 2023-01-28T17:34:41.944637 | 2020-12-09T10:15:14 | 2020-12-09T10:15:14 | 297,916,865 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 601 | r | rankall.R | # Data Science Specialization
# Ranking hospitals in all states
rankall <- function(outcome, num = "best") {
source('rankhospital.R')
outcome_data <- read.csv('data/outcome-of-care-measures.csv', colClasses = 'character')
states <- unique(outcome_data$State)
result <- data.frame(hospital = character... |
4f2b1f6628c60bb32ad540c18581329132e18c0f | 6e2df1994ecddfa44072c99c72f8a06f3092f1b7 | /R/tmle3_Spec_risk.R | 835437ae104c0bf7cce041ad1898fce46181d659 | [] | no_license | child-growth/longbowRiskFactors | 13cade10925688c58ba0db45f3a3e212115f5e91 | 1758b0cbec3cdfab05c352f1cb9681e7af88a5d0 | refs/heads/master | 2020-03-14T10:12:09.332962 | 2019-05-03T21:53:50 | 2019-05-03T21:53:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,471 | r | tmle3_Spec_risk.R |
#' Defines a tmle (minus the data)
#'
#' Current limitations:
#' @importFrom R6 R6Class
#' @importFrom tmle3 tmle3_Spec Param_delta
#'
#' @export
#
tmle3_Spec_risk <- R6Class(
classname = "tmle3_Spec_risk",
portable = TRUE,
class = TRUE,
inherit = tmle3_Spec,
public = list(
initialize = function(baseline... |
f791eeb0efaa33b519747c6733bf2910d3724998 | 6e84f9ba461b7c077b77a23bc7e074ca5ec196dd | /cachematrix.R | 860dd9be60cd93bf933f1d6213a678859bdc3c17 | [] | no_license | brianschlatter/ProgrammingAssignment2 | 8eeec20a762ec857015884fe408ad83141e55de6 | 00d0774c4e4574d9c996ab2aea7696f689030f0b | refs/heads/master | 2021-01-21T16:34:54.930474 | 2014-04-25T19:58:39 | 2014-04-25T19:58:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,721 | r | cachematrix.R | ## A couple helper functions that allow for caching the inverse of the matrix
## Usage:
## Initialization...
## a <- makeCacheMatrix(matrix(1:16, 4))
## To see your matrix...
## a$get()
## To get the inverse of this matrix...
## a$getinv()
## Note: The first this is ca... |
de49b086674ef6da432d384aea750361005d62e8 | b40ff801c83d048177b37e46ab3f4cbc60d51f30 | /Rpackages/Rcapture/tests/testValidMath.R | 58c95644cc0285156465b18b14abdf07db249838 | [] | no_license | murphyjames04/sablefish | 3423d64c1d07e6a1848826604874f03bbe444cdb | ef790f9775c82921604c2dcb72ce6690c9c30e13 | refs/heads/master | 2020-05-17T09:19:51.620950 | 2013-07-23T22:18:09 | 2013-07-23T22:18:09 | 11,323,999 | 0 | 1 | null | null | null | null | ISO-8859-1 | R | false | false | 7,449 | r | testValidMath.R | context("Mathematical validation")
test_that("the .t and .0 'closedp' and 'closedpCI' functions give the same results for the same models", {
data(hare)
res.t <- closedp.t(X=hare, dfreq=FALSE)
res.0 <- closedp.0(X=hare, dfreq=FALSE)
fct.t <- closedpCI.t(X=hare,dfreq=FALSE,m=... |
cdad7b1c881b43ff1ec40ab63cd6f3068037945a | c22d5d3203f3a83bbedb2029a5728a067280558d | /2_Statistical_modelling_I:Introduction/practicals/loglikelihoods/linear_regression.ll.R | 92efff5ff2fb6a58ebdba800e300a13be81da6d7 | [
"LicenseRef-scancode-unknown-license-reference",
"MIT"
] | permissive | crichgriffin/statistics-course | 745ab897cbe646f2954136b82d12293940e000f9 | 54febc4576044b0f127b3d22bfcd9f0976db6dd8 | refs/heads/main | 2023-01-20T08:14:11.513858 | 2020-11-25T12:39:41 | 2020-11-25T12:39:41 | 316,202,064 | 1 | 0 | MIT | 2020-11-26T10:54:15 | 2020-11-26T10:54:14 | null | UTF-8 | R | false | false | 233 | r | linear_regression.ll.R | linear_regression.ll <- function(
outcome,
params = list(
beta,
sigma2
),
X
) {
predictor = X %*% params$beta
gaussian.ll( outcome, params = list( mean = predictor, sigma2 = params$sigma2 ))
}
|
447e2f8a6907aae763c92f49761e80c37ed28189 | dc1a2a89d6f02e366d31ac695d918066ad144bc8 | /ressources/getOriginalDatabase.R | 5d15e6432a524cca9f2c9aeb3fc2acba4a696949 | [] | no_license | absabry/instragram | 98bea0f67f37107483b365e02c82a856d010a580 | 280686fdedf5a0ab5c1452460c14f19e3b6e5b32 | refs/heads/master | 2021-09-20T03:31:01.005240 | 2018-08-02T18:55:03 | 2018-08-02T18:55:03 | 115,888,313 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,076 | r | getOriginalDatabase.R | setwd('C:\\Users\\HP\\Projet')
library(DBI)
dbname=""
host="127.0.0.1"
port=3305
password=""
user=""
dateHistorique = "2014-05-01"
dateDebut="2014-06-1"
dateFin="2014-06-30"
nbPhotosMin=1
con <- dbConnect(RMySQL::MySQL(), dbname = dbname, user=user, password=password, host=host, port=port,encoding = "latin1")
SQL=p... |
688efc5d48b811789e4c59f9c4b251a94e71faa2 | ee788a605dfd2b054cb4dc5d769728babfb5dd92 | /man/lsh_query.Rd | 64e18f80baa549a09b25544205c5c343ab649ad0 | [
"MIT"
] | permissive | felipegonzalez/textreuse | e49236ef00cf1a4a33bfbbeb28d40f2e078658da | 789fcdae7aa76ca9c207bc0ed41ff0dcf20feb5a | refs/heads/master | 2021-05-16T16:10:41.929945 | 2018-02-01T16:16:59 | 2018-02-01T16:16:59 | 119,786,401 | 0 | 0 | null | 2018-02-01T05:17:04 | 2018-02-01T05:17:04 | null | UTF-8 | R | false | true | 1,044 | rd | lsh_query.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lsh_query.R
\name{lsh_query}
\alias{lsh_query}
\title{Query a LSH cache for matches to a single document}
\usage{
lsh_query(buckets, id)
}
\arguments{
\item{buckets}{An \code{lsh_buckets} object created by \code{\link{lsh}}.}
\item{id}{The d... |
7766b8d3e48f2b046ee5de9ed665da3d6269d58d | cf2d25a2bf4cdc94eec42b92329f72d988f42cc4 | /bcw-RocchioClusteringSVM.R | 7782c8f5e44f67edb850290fe2653c788227efab | [] | no_license | sneha123456789/data-scooping | 547c75bf37f8b01c5e262c287c792169f6a8ad8e | 8eb04ad5ba931f49e58c97db3ed94986ec589ec0 | refs/heads/master | 2021-05-07T15:05:32.287846 | 2017-12-19T04:36:35 | 2017-12-19T04:36:35 | 109,973,333 | 0 | 0 | null | 2017-11-08T12:31:25 | 2017-11-08T12:31:24 | null | UTF-8 | R | false | false | 3,992 | r | bcw-RocchioClusteringSVM.R | source("bcw-RocchioSVM.R")
bcw.getReliableNegativeWithRocchioClustering <- function(bcw.PS, bcw.US) {
bcw.data <- bcw.getReliableNegativeWithRocchio(bcw.PS, bcw.US)
## Split into the sets
bcw.PS <- bcw.data[bcw.data$rocLabel == 4, ]
bcw.RN <- bcw.data[bcw.data$rocLabel == 2, ]
bcw.US <- bcw.data[bcw.data$r... |
387c88a1d567d97668816b44b0b17068f6f594b3 | a7b53116bf28e416e6bcf470dd8cc4d60da905a2 | /mixture_model.r | 0d70cf367536791f59472442f80f0cd491063ed9 | [] | no_license | IanMadlenya/Bayesian-Data-Analysis | 6af1c7216e82e80cf9ea41b6e024df4624be519d | 255ab88392918379fa241c3362d559a73cf671b6 | refs/heads/master | 2021-01-25T13:46:55.660504 | 2017-11-20T05:07:24 | 2017-11-20T05:07:24 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,163 | r | mixture_model.r | set.seed(666)
setwd("C:/Users/Wei/Documents/Purdue STAT 695 Bayesian Data Analysis/HW5")
data = read.csv(file="mix_reg.txt", header=TRUE)
X = data$x
y = data$y[order(X)]
X = sort(X)
n = nrow(data)
X = cbind(1, X, X^2)
### Part 1
shape = 1
scale = 1000
std = 1000
library(invgamma)
sigmoid = fu... |
b122bc2314c62926b51579501910940f62a9b5f9 | 00297979d896712ad90a266af4b7da15657583d0 | /SetGoalsStatistics/ads/ad-analysis.R | c9100b206139e190b88f118777e2b36cc957f111 | [] | no_license | Jeremywhiteley/SetGoals | ac7e72fb8bc765fd70e698d6288aad0a76ddd3f8 | e5692ea164371ec063dda458d6fb2b5ba3e87af2 | refs/heads/master | 2020-07-09T20:38:47.180434 | 2019-06-01T12:24:46 | 2019-06-01T12:24:46 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,290 | r | ad-analysis.R | library(dplyr)
### Functions
AddCostPerConvUsd <- function(matrix, nokCost){
# 90 Day average: 1 NOK = 0.11604 USD
# 20.05.19, Source: https://www.xe.com/currencyconverter/convert/?Amount=1&From=NOK&To=USD
CostPerConvUSD <- round(nokCost * 0.11604 , digits = 2)
names(CostPerConvUSD) <- "CostPerConvUSD"
... |
085c542c62ea883dfeb608a63f813de6cfea3249 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/miceadds/examples/mice.impute.2lonly.function.Rd.R | 97ed6047b1630441c7d909d19217625ee1687dba | [] | 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 | 2,272 | r | mice.impute.2lonly.function.Rd.R | library(miceadds)
### Name: mice.impute.2lonly.function
### Title: Imputation at Level 2 (in 'miceadds')
### Aliases: mice.impute.2lonly.function
### ** Examples
## Not run:
##D #############################################################################
##D # EXAMPLE 1: Imputation of level 2 variables
##D ######... |
8dfc630b2e903367b1dcfa69386082b257622978 | 051880099402393c9249d41526a5ac162f822f8d | /man/tg.sample.Rd | d5b921d4478e08b91fb8a7f529288820c82df500 | [
"MIT"
] | permissive | bbTomas/rPraat | cd2b309e39e0ee784be4d83a980da60946f4c822 | 4c516e1309377e370c7d05245f6a396b6d4d4b03 | refs/heads/master | 2021-12-13T19:32:38.439214 | 2021-12-09T18:42:48 | 2021-12-09T18:42:48 | 54,803,225 | 21 | 7 | null | null | null | null | UTF-8 | R | false | true | 310 | rd | tg.sample.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rpraat_sampleData.R
\name{tg.sample}
\alias{tg.sample}
\title{tg.sample}
\usage{
tg.sample()
}
\value{
TextGrid
}
\description{
Returns sample TextGrid.
}
\examples{
tg <- tg.sample()
tg.plot(tg)
}
\seealso{
\code{\link{tg.plot}}
}
|
6b0e7c40f3ba46ca294a8f79c6c29b93d0cd0ce9 | af77cc9ccadb9cf4d451831fdd07abe13503a879 | /yelp/wekafiles/packages/RPlugin/mlr/mlr/R/task.desc.r | c07e5d90ac273a7389ef1d6f00d8c4ec3f4be48d | [] | no_license | tummykung/yelp-dataset-challenge | 7eed6a4d38b6c9c90011fd09317c5fa40f9bc75c | 84f12682cba75fa4f10b5b3484ce9f6b6c8dad4a | refs/heads/master | 2021-01-18T14:10:55.722349 | 2013-05-21T09:30:37 | 2013-05-21T09:30:37 | 9,527,545 | 4 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,073 | r | task.desc.r | #' @include object.r
roxygen()
#' Description object for task.
#'
#' Getter.\cr
#'
#' \describe{
#' \item{id [string]}{Id string of task.}
#' \item{label [string]}{Label string of task.}
#' \item{is.classif [boolean]}{Classification task?}
#' \item{is.regr [boolean]}{Regression task?}
#' \item{has.weights [boole... |
3791f7c5a3204e7294309614748f9322880bf261 | 35709bafc00f6e6b03d730f39fe5e9523883d581 | /GBM&RFcv.R | 7e8feeb4e849658b23dc01b15c8594c8d9ff5ecc | [] | no_license | hzz1989118/R-ETS-RandomForest | 0874121d4eb4a4dea4f185c9b836dd0085a8460d | 7eda3d636c45249d68878e4b31e954258fa38a72 | refs/heads/master | 2020-03-19T03:48:35.120999 | 2018-06-01T22:29:35 | 2018-06-01T22:29:35 | 135,765,017 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,132 | r | GBM&RFcv.R | #####################
### Votat_group #####
#####################
cleandat_cate <-readRDS("C:/Users/Zhuangzhuang/Downloads/cleandat_cate.rds")
deletedVar <- c("AA", "SA", "SDD", "SR", "SRA", "RR", "ARR", "RRA",
"DDD", "RA", "AR", "DA", "AD", "AE", "DE",
"AAE", "ARE", "DDA", "ADE", ... |
b303f069e7937cbabd2e28d3308affd970eac6ce | 0e7c5a92009f315e4eb88e416587e6c369097f68 | /plot1.R | 5bea85e4728872f54054fe58da3659af85fc47cd | [] | no_license | kierlan/ExData_Plotting1 | 011966fc4a1cd0e20de76b822fa0e130506fd935 | a5dbb95fe83629405867a3f8bb64d4195698b734 | refs/heads/master | 2021-01-22T13:17:51.254008 | 2014-05-11T19:44:46 | 2014-05-11T19:44:46 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,079 | r | plot1.R | ##For this to work, you need to
#1. Download the data from here:
# https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip
#2. Unzip it into your working folder.
##If all steps were followed, you should have a .txt file named 'household_power_consumption.txt" in your working folder
##... |
da86e2096c34ceeec466f6e46c8aa00c204a2329 | a90d70d6762234d76978856e18043c6b939f7def | /코드/4.모델적합.R | bbda74fcd9cee1163becb07f684f17516ae5a953 | [] | no_license | changyong93/project_Analysis-of-small_business-Data | 82e18868d2aa8e3280092e20ebdfe35b7baed0fe | edc25b62bccf7244cbd4dd046d65dcee970385f4 | refs/heads/main | 2023-03-30T04:59:18.270955 | 2021-03-30T19:00:35 | 2021-03-30T19:00:35 | 331,337,366 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 20,219 | r | 4.모델적합.R | rm(list = ls())
library(tidyverse)
#파일 불러오기
setwd("C:/Users/ChangYong/Desktop/나노디그리/1.정규강의 학습자료/1차 프로젝트/소상공인/2. 데이터")
load("dataset_set.rda")
#다중선형회귀분석 모델
#모델 적합
vars10_20 <- c(vars_10up[(vars_10up %in% vars_20up)==F])
loc10_20 <- which(colnames(trainset) %in% vars10_20)
#상관계수가 0.2미만 제거한 데이터셋 생성
trainset2 <- trainset... |
8c0882015082dd2f1bce70729d73be8b5a8e15b9 | ed0699c3fc9de97b79a3ceeb52077a2e1ccac5f7 | /plot1.R | 9e4b0a0629bb8d668e19add4c7940d1bb1047fa9 | [] | no_license | rcg-student/ExData_Plotting1 | 956efd94c835a8bfce7ed3de18fb47c05f1bbeb3 | e0eff9e673c8066b19f6a84372276d3420c112f4 | refs/heads/master | 2020-12-26T04:05:21.876189 | 2015-12-12T20:44:21 | 2015-12-12T20:44:21 | 47,610,274 | 0 | 0 | null | 2015-12-08T08:54:28 | 2015-12-08T08:54:26 | null | UTF-8 | R | false | false | 684 | r | plot1.R | #reading data and using the days we want
electric <- read.table("household_power_consumption.txt", header =TRUE, sep=";")
electric_to_use <- electric[ ((electric$Date == "1/2/2007") | (electric$Date == "2/2/2007"))&(electric$Global_active_power != "?") ,]
#decimal formatting for the plot
electric_to_use$Global_active_... |
970b8cae0186fe34bd1afca5240ee325758c564a | d4ecad10911cb7035bc70c46b772a79ad03a142b | /RFig5.R | c5d47f8072df2152c19a32f56894f404acc3e63c | [] | no_license | yteo/epigenetic-analysis-of-cfdna-from-human | a76cca28e6fa5545d891823d28eaa10b7f2d8517 | ed909be5b72d03e0c03fb83e9722ae20fa9ac3b4 | refs/heads/master | 2020-04-27T03:31:11.797231 | 2019-08-28T20:47:27 | 2019-08-28T20:47:27 | 174,026,798 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,216 | r | RFig5.R | # adjust %s for sample name accordingly
multi<-read.table(sprintf("%s\\%s_L1HS_multi_frac.txt",sample,sample,sep="\t"))
count<-read.table(sprintf("%s_L1HS_consensuscoord_count.txt",sample,sample,sep="\t"))
num<-read.table(sprintf("%s_L1HS_consensuscoord_num.txt",sample,sample,sep="\t"))
colnames(count)<-c("Pos","Co... |
f994345c9c047e5ebb10a50b2deb9d8c9bb88438 | 8c658d4e178a8b17aa03c4cc93d76e5201a6bed8 | /Simulating-Sampling-Distributions/server.r | 813c395f4205936cc801de91784673e8be977aad | [] | no_license | hiteshtulsani/Developing-Data-Products-Project | 610ce7c3ba26035b18fcdcdcbd2d1820160f035c | 6b82f3fa3cb67527ff5f0fd5f5a975352539d632 | refs/heads/master | 2020-05-17T08:15:28.267593 | 2014-12-15T07:31:45 | 2014-12-15T07:31:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,986 | r | server.r | library(shiny)
library(ggplot2)
shinyServer(
function(input,output) {
output$newPlot <- renderPlot({
input$simulate
isolate({
set.seed(23051983)
if(input$select == 1) {
means <- apply(matrix(rexp(input$number.samples * input$nosim, input$lambda),
input$nosim), 1, mean)
theoretical.mean <- 1/inp... |
8b89303ba182a60d1cb0f592d8f82ac3cce25e76 | 66698ecc6835ac9c903260fa83c994a027bd0aa3 | /src/scripts/R-setup.R | 6a6f338bf62d65add98a45e0a163b81da5682f81 | [] | no_license | twineapp/vagrant | 51798d4f75ef45c796a738a0951896e70bbeeea6 | 28c46fd91735ee982cf28a586899899e94e2b7af | refs/heads/dev | 2021-01-18T21:29:02.320566 | 2015-08-19T12:22:51 | 2015-08-19T12:22:51 | 9,557,922 | 1 | 1 | null | 2015-01-20T17:27:28 | 2013-04-20T02:04:30 | Shell | UTF-8 | R | false | false | 76 | r | R-setup.R | install.packages(c('jsonlite', 'Rserve'), repos = "http://cran.case.edu" )
|
de019b3cedbb7cc632338e3076a673747040765d | 9d64e54ac35e8adec9577790d543214225769132 | /R/variance_boxplot.R | ac59027f4cfe8ddf2790149bc07fd61a4448738a | [] | no_license | biopaw/MetaboDiff | 5960f8c3e62352e4dcf1d94808750822e60871e1 | 6b1e31aa7c5737e0a9acc4e74a4e98434a341c1f | refs/heads/master | 2023-01-06T01:16:01.638917 | 2020-10-27T19:43:11 | 2020-10-27T19:43:11 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,006 | r | variance_boxplot.R | #' Boxplot comparing the distribution of variance in metabolic measurements across the pathways
#'
#' @param met MultiAssayExperiment object with slots "raw", "imputed", "norm" and "norm_imputed"
#' @param rowAnnotation character name of rowAnnotation to stratify metabolites
#' @return Boxplot comparing the distributio... |
eed8a8611bebc108d8423cef8bb4c72b76463e91 | 8b3cd7ee200564b65db2d76ca8ab953466e091e2 | /man/lrflip.Rd | d5b2eff9b1772b18f6529787b07cd2f64b4a7fdd | [] | no_license | alicejenny/project011 | 3df759dfb96e5a7276bde4dd315bbc81f812a98c | 7de1339bc4c148bfe41264acb3da9307a605e863 | refs/heads/master | 2021-01-10T14:30:09.381069 | 2015-07-15T20:17:40 | 2015-07-15T20:17:40 | 36,937,861 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 426 | rd | lrflip.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/leftrightflip.R
\name{lrflip}
\alias{lrflip}
\title{Left-Right Split & Flip}
\usage{
lrflip(sample, filename, folder)
}
\arguments{
\item{sample}{The input data frame. 3 named columns (x, y, and z, in that order).}
}
\description{
Spl... |
656537183bcd5f1c2c63f2962599738420ed278b | c01177a666c08b1c5f8bc18877f6674b44178cb5 | /man/category_search.Rd | c300819bb9dbd61f210a130de3a36dff73c4c4df | [
"MIT"
] | permissive | mitchellbuchan/trebek | 70293923841e888716b14f1425011ab5aa8f5c5b | 476a75a8ed3c3d05f7ec43c9fe6b73e8a4710809 | refs/heads/master | 2022-06-03T12:02:44.286728 | 2020-05-04T03:20:06 | 2020-05-04T03:20:06 | 261,059,105 | 0 | 0 | MIT | 2020-05-04T01:56:19 | 2020-05-04T01:56:18 | null | UTF-8 | R | false | true | 651 | rd | category_search.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_categories.R
\name{category_search}
\alias{category_search}
\title{Allows a user to see their category options.
Defaults to all options, or shows those that contain the provided query as a substring.}
\usage{
category_search(query = "")
}... |
e5c932a7c53ecf2b72b6f3b35eca3054d9d79632 | 7678b6b87290c4b30808075736e179c1334d0725 | /Hands-On Programming with R/9 loop .r | f115b669ebd2dd1a241ff40b2e1a84dfde05fe41 | [] | no_license | xiemeigongzi88/Basic_R | eebf48ec032b44d850010139119cd0492be2e25d | 39b723f486b81b37cffda1a43823ce257b9b61e7 | refs/heads/master | 2020-06-04T23:23:53.858024 | 2020-03-18T16:44:17 | 2020-03-18T16:44:17 | 192,035,946 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,685 | r | 9 loop .r | 9 loop
page 168
9.1 期望值
9.2 expand.grid
expand.grid （） 函数可以写出 n 个向量元素的所有组合
> die<-c(1:6)
> rolls<-expand.grid(die,die)
> rolls
Var1 Var2
1 1 1
2 2 1
3 3 1
4 4 1
5 5 1
6 6 1
7 1 2
8 2 2
9 3 2
10 4 2
11 5 2
12... |
227b2b59e78b16d3184f4cc75b3768236d53fbcd | 4127dd6771c46682d42b7af9d00613dcbda8c1d0 | /R/networks-module.R | 625de320b29ce845077a9bf583de0d2efe3564f3 | [
"Apache-2.0"
] | permissive | brainy749/chirp | 25ae98bfd373f0f7a891accf55d86174b37b7142 | 74c0a1c086226adeb54035f95ac7952fe5eb9711 | refs/heads/master | 2020-04-25T20:36:52.657588 | 2019-02-27T23:03:08 | 2019-02-27T23:03:08 | 173,054,322 | 1 | 0 | null | 2019-02-28T06:25:51 | 2019-02-28T06:25:51 | null | UTF-8 | R | false | false | 28,138 | r | networks-module.R | networks_ui <- function(id){
ns <- NS(id)
tagList(
tags$a(
icon("pencil-ruler", class = "fa-lg"),
onclick = "pushbar.open('save_pushbar');",
class = "btn btn-primary",
`data-pushbar-target` = "save_pushbar",
id = "optsBtn"
),
tags$a(
icon("database", class = "fa-lg"... |
a174be6a278c0883c32696f0673d4e8533bf0d83 | cfc816b9a950b290115918a73b7fb32a8691ede5 | /scripts/readmission/LTH_ICNARC/1_extract_patients.R | 6d7aea0efcecaf7cb6dd7fa1a1628031bf8410ff | [] | no_license | btcooper22/MIMIC_ICU | abcf30a8298fe2c961938952cf7d5ba0cb71aee2 | 41c231d9c74a88ff516ce74dcbebd65647189818 | refs/heads/main | 2023-06-24T07:10:51.708553 | 2021-07-27T17:12:38 | 2021-07-27T17:12:38 | 326,666,861 | 1 | 0 | null | 2021-05-25T11:04:40 | 2021-01-04T11:48:05 | R | UTF-8 | R | false | false | 2,857 | r | 1_extract_patients.R | # Packages
require(bigrquery)
require(DBI)
require(dplyr)
require(magrittr)
require(tibble)
require(purrr)
require(readr)
# Find project name
bq_projects()
# Find datasets
bq_project_datasets("prd-proj-decovid-358375")
# Find tables
bq_dataset_tables("prd-proj-decovid-358375.icnarc_analytics")
# Set ICNARC table as... |
f3081a3be1c49799b2ef2f57233098438b6141ed | 875e363e73bd4d06daccad49d030ee9d6a3a5290 | /man/hot_table.Rd | 561e4d4afe6ac0a207df7eb396e34b791f76bd46 | [
"MIT",
"BSD-3-Clause",
"BSD-2-Clause"
] | permissive | cran/rhandsontable | d8f2a0a6d86899e64de6c8b24d8db21aec3a7944 | 796904290381cad5a53988be1bf36c0176090f53 | refs/heads/master | 2021-06-14T09:52:46.604189 | 2021-05-27T10:50:03 | 2021-05-27T10:50:03 | 37,997,493 | 1 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,635 | rd | hot_table.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rhandsontable.R
\name{hot_table}
\alias{hot_table}
\title{Handsontable widget}
\usage{
hot_table(
hot,
contextMenu = TRUE,
stretchH = "none",
customBorders = NULL,
highlightRow = NULL,
highlightCol = NULL,
enableCom... |
ceb538cc78edd69b508cbbdbce2f197208e962ad | 9262e777f0812773af7c841cd582a63f92d398a4 | /inst/userguide/figures/Covar--Covar_sec6_05_month-factor-marss-params.R | a1c63c92a9ffbe873eed1b4879a0a7be9e78a7c8 | [
"CC0-1.0",
"LicenseRef-scancode-public-domain"
] | permissive | nwfsc-timeseries/MARSS | f0124f9ba414a28ecac1f50c4596caaab796fdd2 | a9d662e880cb6d003ddfbd32d2e1231d132c3b7e | refs/heads/master | 2023-06-07T11:50:43.479197 | 2023-06-02T19:20:17 | 2023-06-02T19:20:17 | 438,764,790 | 1 | 2 | NOASSERTION | 2023-06-02T19:17:41 | 2021-12-15T20:32:14 | R | UTF-8 | R | false | false | 747 | r | Covar--Covar_sec6_05_month-factor-marss-params.R | ###################################################
### code chunk number 15: Covar_sec6_05_month-factor-marss-params
###################################################
# Each taxon has unique density-dependence
B <- "diagonal and unequal"
# Independent process errors
Q <- "diagonal and unequal"
# We have demeaned the... |
9f23b642a8a511a961cbdee26475fa2babb4a84d | 6ad7738a48f862ac9b022c7422d2b5e7aefb0a1c | /R/lsPreview.R | 8ccab930de93547df8b9ad04f3c2c87ece708bf2 | [] | no_license | cran/RGISTools | 79949265b94d74cd95f7f697b283687d7bf8fbb5 | 101bb144ed9463c0fc807dadf74934942c8d42b7 | refs/heads/master | 2020-12-22T17:58:59.781343 | 2020-05-20T13:20:06 | 2020-05-20T13:20:06 | 236,882,001 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,404 | r | lsPreview.R | #' Preview Landsat-7 or Landsat-8 satellite images
#'
#' \code{lsPreview} shows a preview of the \code{n}-th image from a set of
#' search results on an interactive map.
#'
#' The function shows a preview of the \code{n}-th output image from a search
#' in the Landsat archives (\code{\link{ls7Search}} or \code{... |
2b1349ebf4b595a9e02db7274279575079abb865 | 19acf16c1c613e606e992204645c4fbabcfe6f80 | /RScript02_SeqCompTest.R | 1f3529e965a303fdd22a70e04f1ab914038df9ce | [] | no_license | snandi/RScripts_BAC | d146b2a4a500f334143e2392cdc0c654f548bb42 | b8c46d12134f00d77a944c7570b592eea6179110 | refs/heads/master | 2021-01-10T03:33:30.828352 | 2017-01-05T17:34:07 | 2017-01-05T17:34:07 | 46,696,462 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,238 | r | RScript02_SeqCompTest.R | rm(list=ls(all.names=TRUE))
rm(list=objects(all.names=TRUE))
#dev.off()
########################################################################
## This script reads the sequence data from the fasta files, creates
## GCAT ratios for each interval, creates the ggplot objects for the
## sequence plots, and the signals (... |
a61c426d4a52b8f3c402d992ed3557da06231c15 | 72cf63cd0879026594008fcb437ed6c4f074b863 | /old-code/simulation-code-FDA.R | adb019988e07375080306df5500c9e5132463d4f | [] | no_license | JiaweiXu-code/BACPAC | 5dd8b1efd407560cfebc30af458f1bca424537e2 | d4c066fe597a001312546df79c890eee3e06bde4 | refs/heads/main | 2023-04-18T03:50:17.609420 | 2021-05-11T14:12:28 | 2021-05-11T14:12:28 | 344,529,079 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,485 | r | simulation-code-FDA.R |
source("C:/D/R-package/gibbs.R");
#source("/pine/scr/j/i/jiawei/Rpackage/gibbs.R");
## set seet for reproducibility;
set.seed(1);
## Historical Data (to define power prior);
hst_n = 25.0; ## sample size;
hst_mn = 0.0; ## azm cfb mean (also mean of normal power prior);
hst... |
9e9c01a4794f58c62981fdfb1e14ffd49e9d443f | 44ea20642e56ff6cc836029bcda5a29390335b30 | /man/d.binormal.Rd | e5f0224f8974269db4e51f68cf5095cd9e3997af | [] | no_license | cran/idr | e8906789b0be3ba0663d46da33f36ea46c2cfd96 | 4fa51a408935584f97292a091cf32c6e307d9cc6 | refs/heads/master | 2022-07-18T03:32:18.278592 | 2022-06-21T06:30:07 | 2022-06-21T06:30:07 | 17,696,749 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,544 | rd | d.binormal.Rd | \name{d.binormal}
\alias{d.binormal}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Log density of bivariate Gaussian distribution with symmetric marginals
}
\description{
Compute the log-density for parameterized bivariate Gaussian
distribution N(mu, mu, sigma, sigma, rho).
}
\usage{
d.binormal... |
6f3cc6c7f66f38c99d47490fb6afe672fa77ae7c | bf378a66012b6470250c2c9b1e8aa9fd33c67da9 | /R20190807_17.R | 062fd6d642c71214bfd23a72a6500082285a2c49 | [] | no_license | meenzoon/R-programming | baa30902c9ca232b00f62c988c13e59de97109b8 | 9065fb9f7168b5487dc314a1a82c4456fd981ee2 | refs/heads/master | 2022-01-21T02:11:42.853224 | 2019-08-12T08:51:24 | 2019-08-12T08:51:24 | 198,178,623 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,725 | r | R20190807_17.R | # 17일차 수업 - 20190807(수)
library(dplyr)
library(ggplot2)
library(readxl)
##########
### 11번째 프로젝트 - 지역별 연령대 비율
# < 1단계 > 변수 검토 및 전처리(지역, 연령대)
# 1-1. 지역 변수 확인, code_region 변수를 통해 region 파생변수를 생성
# code_region - 1:서울, 2:수도권(인천/경기), 3:부산/경남/울산, 4:대구/경북, 5:대전/충남, 6:강원/충북, 7:광주/전남/전북/제주도
class(welfare$code_reg... |
efdacd744e3c5b135fef7c9fbd2cc0889bfc8d49 | 6cbc6e80ae07b8fb1fff0a5cad4ddcd29c358c0a | /man/ezr.tbl_to_image.Rd | 64772c9b0f7dce5449b661b8612ee11d27f19c2c | [] | no_license | lenamax2355/easyr | d99638b84fd9768774fa7ede84d257b10e0bacf6 | 37ab2fe5c28e83b9b5b3c0e3002f2df45708016b | refs/heads/master | 2022-01-09T20:43:17.801623 | 2019-05-13T02:49:48 | 2019-05-13T02:49:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 830 | rd | ezr.tbl_to_image.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ezr_image_to_table.R
\name{ezr.tbl_to_image}
\alias{ezr.tbl_to_image}
\title{Table to Image}
\usage{
ezr.tbl_to_image(dataset, n_records = 10, only_columns = NULL,
exclude_columns = NULL, theme = NULL)
}
\arguments{
\item{dataset}{Dataframe... |
dc169062f9db44b23ab7cbc081780e0d4fce9945 | 1be7bdfb44a4b4ae98cdc48046042f0739fefde1 | /LSKAT/R/longskat-plink.r | 57e2ab0e1b38b9069c62eaa8f73c23209c57f133 | [] | no_license | wzhy2000/LSKAT | c521ebe4247fb592a2bec3d2110a41a523e5ca2c | d1dee4cc874195eaaab854c9f5f812a4f17ad27b | refs/heads/master | 2020-04-15T10:53:49.427329 | 2018-06-22T20:21:00 | 2018-06-22T20:21:00 | 52,325,786 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 12,814 | r | longskat-plink.r | setRefClass("PLINK.refer",
fields = list(
options = "list",
snp = "list",
gen.list = "list",
ind.list = "list"),
methods = list(
show = function()
{
cat("Reference PLINK class", classLabel(class(.self)), "\n")
cat("PLINK BED=", options$file.plink.... |
c9cbfd2830bc769de7c79b83e4e024ed95d607ff | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/WaveletComp/examples/USelection2016.Instagram.Rd.R | 499329e2631d4488e45e98b1250895b30fc064d3 | [] | 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 | 896 | r | USelection2016.Instagram.Rd.R | library(WaveletComp)
### Name: USelection2016.Instagram
### Title: Hourly time series of the number of candidate-related media
### posted on Instagram during the week before the 2016 US presidential
### election
### Aliases: USelection2016.Instagram
### Keywords: datasets
### ** Examples
data(USelection2016.In... |
90d795c45c51e4b9c191f81b878da12593e7091c | de0935ade1f6cfece090e7ff7057692e1404c24f | /Scripts/ss_initial_scrub.R | 62f3beea7f5ca80ccc82a07c7c19aa673e032612 | [] | no_license | sofisinozich/SURV622_Assignment-2 | 501b09d79eadfd14392b337332e8f42f05de346d | 51f821f13c67589f1333f23fa46ad35adcc96367 | refs/heads/master | 2022-04-11T12:07:04.570317 | 2020-03-23T19:25:40 | 2020-03-23T19:25:40 | 244,040,529 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 370 | r | ss_initial_scrub.R | library(rtweet)
library(qdap)
library(tidyverse)
library(magrittr)
oneday_tweets <- parse_stream("Data/ss_streamed_tweets.json")
oneday_tweets %>% select(text)
oneday_scrubbed <- oneday_tweets$text %>% scrubber() %sw% qdapDictionaries::Top200Words
link_regex <- "https : / / t. co / [a-z0-9]{10}"
oneday_scrubbed %<>% g... |
846f9a7ac4c081e0e8e99ca2593120b1a6cfd245 | dce4f2712b1cb826893c77c47d951a25d763630d | /man/Rect.Rd | ceb3de8f3bc7670109587c1e6b6015adfccde66e | [] | no_license | Displayr/flipPictographs | dacfad5c35df6bb8dfad1deb397052616a461178 | b416b465b3bd603cf85bdbe11995eed21ae59fc5 | refs/heads/master | 2023-05-25T05:44:35.410505 | 2023-05-22T09:13:03 | 2023-05-22T09:13:03 | 60,046,387 | 0 | 1 | null | 2023-08-17T05:55:04 | 2016-05-31T00:25:48 | R | UTF-8 | R | false | true | 566 | rd | Rect.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/rect.R
\name{Rect}
\alias{Rect}
\title{Rect}
\usage{
Rect(color = "red", opacity = 0.9, print.config = FALSE)
}
\arguments{
\item{color}{One of 'red', 'green' or 'yellow' or a hex color code.}
\item{opacity}{A numeric value between 0 and 1.}... |
e40b107c8170269331f3a7d0d9efd2ef6256f6bf | c981caf103a3540f7964e6c41a56ca34d67732c4 | /R/lm_cluster_compute_vcov.R | ababdec8e6b042c5b8cb2f64f36e5e74c9518b34 | [] | no_license | alexanderrobitzsch/miceadds | 8285b8c98c2563c2c04209d74af6432ce94340ee | faab4efffa36230335bfb1603078da2253d29566 | refs/heads/master | 2023-03-07T02:53:26.480028 | 2023-03-01T16:26:31 | 2023-03-01T16:26:31 | 95,305,394 | 17 | 2 | null | 2018-05-31T11:41:51 | 2017-06-24T15:16:57 | R | UTF-8 | R | false | false | 383 | r | lm_cluster_compute_vcov.R | ## File Name: lm_cluster_compute_vcov.R
## File Version: 0.01
lm_cluster_compute_vcov <- function(mod, cluster, data)
{
require_namespace("sandwich")
if ( length(cluster) > 1 ){
v1 <- cluster
} else {
v1 <- data[,cluster, drop=TRUE]
}
dfr <- data.frame( cluster=v1 )
vcov2 <- san... |
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