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91d27c736ebfc3975b22a1725237365b94db2540 | a0e84488a6bf4cecf049784104095b05fcba19f8 | /man/run_mHMM.Rd | da6a9ef50d0a14aa02a1707e023fec72822cec12 | [
"MIT"
] | permissive | JasperHG90/sleepsimR | 2a149bb8af60619c84eab6b9e79caa21c70faef6 | 75fca083bd2304b98290d9ba945d91b6073cb17a | refs/heads/master | 2021-01-09T13:49:05.095474 | 2020-05-14T06:48:51 | 2020-05-14T06:48:51 | 242,324,165 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,731 | rd | run_mHMM.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/run_model.R
\name{run_mHMM}
\alias{run_mHMM}
\title{Run an mHMM on a simulated sleep dataset}
\usage{
run_mHMM(
data,
start_values,
mprop,
hyperprior_means,
model_seed,
mcmc_iterations = 2000,
mcmc_burn_in = 1000,
show_progres... |
6205116b7083ec2a1cb3979f5fbd109d3bdb74a6 | c4788fa46ef6504065e8b31d6e3f82432ef3954e | /pkg/tests/dataframe.R | 87d1cbdc7a8be796139b71f4ab6b11dd4ed09247 | [] | no_license | RevolutionAnalytics/plyrmr | bb8c2d6946e141cb51971f17ee5480071d3a168c | ce54c98c5d23045e70e83b4b0e833424ce97a4cf | refs/heads/master | 2023-08-31T17:19:14.978193 | 2015-03-19T04:51:05 | 2015-03-19T04:51:05 | 11,489,876 | 30 | 21 | null | 2015-03-25T00:40:06 | 2013-07-17T23:19:10 | R | UTF-8 | R | false | false | 1,957 | r | dataframe.R | # Copyright 2014 Revolution Analytics
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed... |
d2504ca055bf76ac79367cd8c0e672ae1bd84815 | 3e50dd3332d32c68e8de65e8172832edb5f88356 | /run_analysis.R | e0c19da3e8e36b252de77cf817e6c03638b8cbe4 | [] | no_license | LourdesC/Getting-and-Cleaning-Data-Course-Project | f06ad3d071b2e65637fb39724151cec43fbb9403 | 920155f410b0a59707d6acf6fb5b72193138d76d | refs/heads/master | 2021-01-22T11:51:28.893337 | 2015-02-17T20:48:27 | 2015-02-17T20:48:27 | 30,932,110 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,771 | r | run_analysis.R | ####Getting and Cleaning Data Course Project####################################
# You should create one R script called run_analysis.R that does the following.#
# #
# 1.- Merges the training and the test sets to create one data set. ... |
aeb2096622cad68498dbea47c78960f8b3392b0f | c05ffccc08a88027d6d303f70eb6bec29e8e3eee | /P5_Trends_Graphs.R | a3e7477922fa2baf726495184868ef29ab42d2fa | [] | no_license | melitanick/NCMP | 00c0f89e0cbfb1ce4f1f2ff8ce8b1b94422e5c79 | 9f133d239166157cbee5bc46d06596ef68d779e4 | refs/heads/master | 2021-09-02T02:16:27.038672 | 2017-12-29T17:46:37 | 2017-12-29T17:46:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 26,960 | r | P5_Trends_Graphs.R | ###################################################################################
# #
# The R-NCMPs package has been developed by the ET-NCMP. #
# P5_Trends_Graphs.R ... |
c84ad19879f82107acd9a2f71dc82a8af0adf802 | ea967eeccfccc59acc2a79793826049f5ed7bc91 | /man/chac.Rd | a56477640afe9390bcf0b00e7d3f7fe827be1e96 | [] | no_license | pneuvial/adjclust | 0d9cffb36b3313defec73b783e01ef68f059fe58 | e3532a2ba23f54572fbbb8b81e31b29a7b7708e5 | refs/heads/develop | 2023-05-07T15:16:27.161557 | 2023-04-26T07:24:06 | 2023-04-26T07:24:06 | 61,875,551 | 15 | 17 | null | 2023-04-28T06:44:33 | 2016-06-24T10:02:56 | R | UTF-8 | R | false | true | 4,905 | rd | chac.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/chac.R
\name{chac}
\alias{chac}
\alias{as.hclust.chac}
\alias{print.chac}
\alias{head.chac}
\alias{summary.chac}
\alias{plot.chac}
\alias{diagnose}
\alias{diagnose.chac}
\alias{correct}
\alias{correct.chac}
\alias{cutree_chac}
\alias{cuttree_... |
a80fb30e56433ab172279fc9f4f60d740cdaec02 | d119af4b62debd9019a54971ff19ff97560001da | /base_codes/allele_distribution_effects.R | 91a20a21c5b7b4e318808bb4ff9d7f53d8ea4645 | [] | no_license | kenoll/U19-Ab | 3f438a45bc551f0f3a02475023c31ee3a98985b7 | a48446d8916f99025e743d121d373fe295869734 | refs/heads/master | 2021-01-22T04:09:33.558744 | 2017-10-12T17:59:09 | 2017-10-12T17:59:09 | 81,491,368 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,469 | r | allele_distribution_effects.R | #2016_11_23 updated to used average scores that encompass recombinations within locus
setwd("~/Dropbox/Heise/ELISA Antibody/")
chrom=read.csv("qtls/d10/snps/chr5_68-75_scores.csv")
##### strain averages #####
dat=dat.10
Map.dat=summaryBy(IgG1+IgG2ac+IgG2b+IgG3+IgM+TotalG ~
RIX + day, data=dat, F... |
8390d43655a8d95a945a4df417c426900a9ba033 | 427db53b82601e0d8d344410c624a3c3e2797bbe | /R/Monty Hall.R | 40907e870fbcc194ba7d5ce0b5b84c45f29ed539 | [] | no_license | idjs2/montyhall | f053da5204a9e3d93050775f665b91df62ae52ac | ee4ec14f0c1c22b116f6af5b76717eb9785b04c1 | refs/heads/master | 2022-07-09T05:45:48.275628 | 2020-05-10T10:15:01 | 2020-05-10T10:15:01 | 262,764,566 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,612 | r | Monty Hall.R | #' 몬티홀 딜레마함수 montyhall(k)
#'
#' 함수 설명
#' 몬티홀문제를 3가지 경우로 나누어 어떠한 선택에도 결론(선택을 바꾸는 것이 유리하다.)을 도출할 수 있다는 것을
#' 증명한 함수입니다.
#' 각 케이스의 첫째 행은 쇼의 주인공이 모르는 문 뒤의 상황입니다. (k는 주인공이 선택한 문의 번호입니다.k=1,2,3)
#' 두번째 행은 주인공의 선택(Choice)과 사회자가 열어서 보여준 염소(Open)의 위치입니다.
#'
#' @example
#' montyhall(1) 1번문을 선택한 경우
#' [1] "CASE1"
#' [1] "염소" ... |
775117988f0d64053d337f76b87b80a2bf68193e | a1e3f742d80a225e9a2a35e8e88b3054f5408037 | /R/boot.gomp.R | 5907670e1b3af38ef30e326c3f56556396abbd31 | [] | no_license | cran/MXM | 7590471ea7ed05944f39bf542c41a07dc831d34f | 46a61706172ba81272b80abf25b862c38d580d76 | refs/heads/master | 2022-09-12T12:14:29.564720 | 2022-08-25T07:52:40 | 2022-08-25T07:52:40 | 19,706,881 | 0 | 4 | null | null | null | null | UTF-8 | R | false | false | 1,059 | r | boot.gomp.R | boot.gomp <- function(target, dataset, tol = qchisq(0.95, 1), test = "testIndLogistic", method = "ar2", B = 500, ncores = 1) {
runtime <- proc.time()
sel <- NULL
n <- dim(dataset)[1]
if ( !is.matrix(target) ) dim(target) <- c(n, 1)
if ( ncores <= 1 ) {
for (i in 1:B) {
ina... |
a80376cd9b0fe46f068ff452e7ecbd596fff2388 | 9a5b39ad69a9e79ef101711aa20f892b4d50316f | /man/modelHomotypic.Rd | e474d97abf5f324ef417e7bf2212cbd2601e7f2f | [] | no_license | chris-mcginnis-ucsf/DoubletFinder | 207dc938574b2647d5dc73a47c520fc9eb782548 | 1b1d4e2d7f893a3552d9f8f791ab868ee4c782e6 | refs/heads/master | 2023-09-01T19:51:25.819412 | 2023-08-18T22:26:49 | 2023-08-18T22:26:49 | 138,660,553 | 288 | 76 | null | 2023-08-18T22:26:50 | 2018-06-25T23:32:45 | R | UTF-8 | R | false | false | 1,344 | rd | modelHomotypic.Rd | \name{modelHomotypic}
\alias{modelHomotypic}
\title{modelHomotypic}
\description{
Leverages user-provided cell annotations to model the proportion of homotypic doublets. Building on the assumption that literature-supported annotations reflect real transcriptional divergence, homotypic doublet proportions are modeled as... |
06155c366e9b60df5c4f6560342dc00ce3614142 | 13ab7466ef1fe4d688eaea3668ea79e549ca5467 | /src/FeatureSelection.R | ec307169bc6e1e29447a5a1aad1797f79ca3e426 | [] | no_license | mina2796/Ensayo | f038346d68ef65235d6e674a097da32d55bce35e | 6a4eb6156f9853a9647e8f36cf9a3b50bbecdc39 | refs/heads/master | 2021-07-24T14:20:42.836051 | 2017-11-06T04:53:26 | 2017-11-06T04:53:26 | 109,647,183 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,619 | r | FeatureSelection.R | library(mlbench)
library(caret)
library(reshape2)
set.seed(7)
# function to fing High correlated variables
mosthighlycorrelated <- function(df, numtoreport){
cormatrix <- cor(df)
upperTriangle <- upper.tri(cormatrix, diag = F)
cor.upperTriangle <- cormatrix
cor.upperTriangle[!upperTriangle] <- NA
... |
e54b217a195ba89ed6f1a8705cd2212eadd17906 | 2e9faf2f73476db35ee7a72359a8979b79a86605 | /R/tiplength.R | 366b27e73efa5b8e3c38ec00dee4594086b106a3 | [] | no_license | Hackout3/saphy | 0450efe1014b5e1d850850709ce77adb6347e923 | d588c1788a29cd9f18441f2c9ffa095b2b099d4d | refs/heads/master | 2021-01-19T07:09:56.358549 | 2016-06-23T22:42:08 | 2016-06-23T22:42:08 | 61,653,942 | 4 | 6 | null | 2016-06-24T18:52:00 | 2016-06-21T17:36:19 | R | UTF-8 | R | false | false | 674 | r | tiplength.R | #' Extracts the length of a tip from a tree
#'
#' \code{tiplength} returns the length of a tip of a tree, given either (a) the tip name or
#' (b) the index of the tip (in the order of the tip labels in the tree).
#'
#' @param tree a phylogenetic tree (as a \code{phylo} object)
#' @param tipname the tip name, as a cha... |
11d4b5bfcf158fb9166550778428c529fac8889f | 28d40f7881898e499127d49c573028b93ba512f6 | /load_data.R | b2cc85447c0285a7fae32a20fe70de5d82f1eee4 | [] | no_license | dwolffram/covid19-ensembles-retrospective | 1b55e016677fdbaa5664f18b0f2f7799cdf2553b | b9ed03cb541b6d27f4b548e8dac8e04871b4727a | refs/heads/main | 2023-09-04T06:00:04.633212 | 2021-11-04T15:54:28 | 2021-11-04T15:54:28 | 402,688,755 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,599 | r | load_data.R | library(tidyverse)
Sys.setlocale("LC_ALL", "C")
next_monday <- Vectorize(function(date){
date + (0:6)[weekdays(date + (0:6)) == "Monday"]
}
)
load_truth <- function(target="incident_cases", as_of){
truth <- read.csv(paste0("https://raw.githubusercontent.com/dwolffram/covid19-versioned-data/main/data/",
... |
0370699f080ae63584d4b15ee18bde2e67accb1c | 8cf4416f7e4c9016d85a616aaae3fbf0d48cf9a4 | /r/Old/Sparrow20090715.r | 616760d00030492c9c0ba8582e9e06db8ec26eed | [] | no_license | willbmisled/MRB1 | 35f9bb4ef9279f55b1348b8b3fbda6543ddbc70d | af39fb697255df15ae41131d76c6fcf552a55a70 | refs/heads/master | 2020-07-20T08:43:00.460675 | 2017-06-14T14:09:38 | 2017-06-14T14:09:38 | 94,337,564 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,805 | r | Sparrow20090715.r | rm(list=ls(all=T)) #clear workspace
# Read data-****Make Sure the Path Is Correct****
require(RODBC) #Package RODBC must be installed
con <- odbcConnectAccess("//AA.AD.EPA.GOV/ORD/NAR/USERS/EC2/wmilstea/Net MyDocuments/EPA/Data/Sparrow/MRB1Sparrow/MRB1Sparrow.mdb")
get <- sqlQuery(con, "
SELECT MRB1_WBIDLakes.WB_... |
0e3f9a17a6e7258d5f414dd61d8ad0c40f6dc9e6 | ec15073d91ea3d63bfd93d4fcb0ff1d963a0d251 | /bayesian_methods/challenger.R | ad0fa8c246bab67b3e06adbe2b627d3fdd263256 | [] | no_license | nishkavijay/data-analysis | e56079649ab4798a6d49bcec16a559fccaf4a377 | 95d962b4fad31501b1aa5e6def13179417b7f270 | refs/heads/master | 2021-01-15T11:56:36.993456 | 2014-07-23T16:51:48 | 2014-07-23T16:51:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,277 | r | challenger.R | # a.Prepare analysis of the type we did for Bioassay problem,
# with the covariate being the temperature and the response variable being
# #of primary O-rings in field joints with Erosion or blowby.
# There are 6 primary O-rings per shuttle.
# Challenger was launched at temperature of 31 degrees.
input<-function(LL... |
cf70a9ac2da5781aa7431d45da4a06ca20d22acb | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/catR/examples/EPV.Rd.R | a75efc6045de372723a87e523899e062e23b8102 | [] | 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 | 1,595 | r | EPV.Rd.R | library(catR)
### Name: EPV
### Title: Expected Posterior Variance (EPV)
### Aliases: EPV
### ** Examples
## Dichotomous models ##
# Loading the 'tcals' parameters
data(tcals)
# Selecting item parameters only
bank <- as.matrix(tcals[,1:4])
# Selection of two arbitrary items (15 and 20) of the
# 'tcals' ... |
f2758eead6d3f6c5bc72fbae3b9a8a0e7966b0ed | 0e3935889a98eed7f993c88df5b86f4809769f28 | /brier.R | 2c687fd95986e487232de9d07ed5a4d25714e685 | [] | no_license | tbruning/R-functions | aeb02507c07a617792a61978feb4ea269beaa545 | efcfa581fdc8a14204d47b4b4a859db7cc46805e | refs/heads/master | 2021-01-21T13:11:32.513505 | 2016-05-12T14:07:06 | 2016-05-12T14:07:06 | 49,440,558 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 114 | r | brier.R | brier <- function(prob, happened = 0) {
ifelse(happened == 1,
2 * (prob - 1)**2, 2 * (1 - prob - 1)**2)
}
|
2d6fa47fa711cf66f5371660106fbe959bd97f06 | b3d411d09b7e92545f4a52273ca7777b83b9bee8 | /functions.R | d836f7a9c92d0047a1b3eae5c717109ea14817a8 | [
"MIT",
"CC-BY-3.0"
] | permissive | rafalab/maria | 14f8fbb377bbc9c583a270943cc1a9c26cd77d11 | 30973de794b6c0b6cba82211cde9eccb0319b218 | refs/heads/master | 2020-03-27T23:50:47.460493 | 2018-09-09T02:18:53 | 2018-09-09T02:18:53 | 147,352,312 | 4 | 3 | null | null | null | null | UTF-8 | R | false | false | 8,874 | r | functions.R | ## day of the year skipping 2/29
my_yday <- function(x) ifelse(year(x)%%4 == 0 & month(x)>2, yday(x)-1, yday(x))
## function to create harmonic model
fourier_trend <- function(x, k=3){
H <- lapply(1:k, function(k){
cbind(sin(2*pi*k/365*x), cos(2*pi*k/365*x))
})
return(do.call(cbind, H))
}
## for vectors l... |
e9a7149659857485a7fa2faa130ed546e554e4e3 | dc7c1016493af2179bd6834614be0902a0133754 | /forcats.R | a08e0a3b56760fb9a3d2d75ddf87cb88babfa25c | [] | no_license | ashishjsharda/R | 5f9dc17fe33e22be9a6031f2688229e436ffc35c | fc6f76740a78d85c50eaf6519cec5c0206b2910c | refs/heads/master | 2023-08-08T13:57:05.868593 | 2023-07-30T13:51:56 | 2023-07-30T13:51:56 | 208,248,049 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 85 | r | forcats.R | library(forcats)
gss_cat %>%
count(race)
ggplot(gss_cat, aes(race)) +
geom_bar()
|
f923d899a967b0d93b106b4a94212e5b50d94611 | 4fd6dedc1b65f6575990f5c4e7c85a966561c4c2 | /Functions-sim-true-spp/Sim-spp-funcitons.R | 504fa87cf9fcb4d4207078b9d5361770caf5e1d7 | [] | no_license | gerardommc/Niche-centroids | ed6233e48d1a6c0e1183ed6d3cf63908dc9536d7 | 3667a2885fbbe6d0a0a240400ba4f56699435357 | refs/heads/master | 2023-04-09T15:44:40.994073 | 2022-02-02T19:34:11 | 2022-02-02T19:34:11 | 296,682,843 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 291 | r | Sim-spp-funcitons.R | temp.optim <- function(x, k = list(k1, k2, k3, k4, k5, k6, k7)){
y <- with(k, (k1*(x - k2)^k3)/(k4^k3 + (x - k2)^k3) - exp(k7 - (k5 - (x - k2))/(k5 - k6)))
return(y)
}
rain.resp <- function(x, k = list(k1, k2)){
y <- with(k, k1 * (1 - exp( - k2 * x)))
return(y)
}
|
9203db8e8cadcde9ddb23d226b1ff7dd40b4a63f | 53a794aff945938f5a183e154b4b54216aea4020 | /R/h2o-package/R/h2oWrapper.R | 57a75d7747b737205c7f0783d8ffd3b4ab2789e1 | [
"Apache-2.0"
] | permissive | jmcclell/h2o | 510989cecdf63b50f49106779c942b1c7b18aa7e | 753b2e5baed9c5305e7b5e7335b27243e93abb7c | refs/heads/master | 2021-01-21T15:43:45.395213 | 2013-12-12T01:38:08 | 2013-12-12T01:38:08 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,090 | r | h2oWrapper.R | setClass("H2OClient", representation(ip="character", port="numeric"), prototype(ip="127.0.0.1", port=54321))
setGeneric("h2o.init", function(ip = "127.0.0.1", port = 54321, startH2O = TRUE, silentUpgrade = FALSE, promptUpgrade = TRUE) { standardGeneric("h2o.init") })
# setGeneric("h2o.shutdown", function(ip = "127.0.0.... |
0a5d24746f65be149dae3a284ae8c64d2054eb68 | 3281ca220cb0c99a6c763ecf78c99a67812537b6 | /multi-regression.R | fec3a0559dc875594e2d0b510a749990827bc39b | [] | no_license | deokju12/-multi_variable_analysis | d7d406042ae6221d606c52d190649f357158ec54 | 285249ff0a2ab97a978cb47c212e208a25476099 | refs/heads/master | 2020-05-28T02:59:10.889960 | 2019-05-27T14:57:56 | 2019-05-27T14:57:56 | 188,861,704 | 0 | 0 | null | null | null | null | UHC | R | false | false | 2,880 | r | multi-regression.R |
# 1번
#Houseprice.csv는 주택판매가격(price)과 이에 영향을 줄 것으로 판단되는 4가지 설명변수인 세금(tax; 만원), 대지평수(ground; 평), 건물평수(floor; 평), 주택연령(year; 년)을 27개 주택에 대해 조사한 것이다.
# 1. 5개 변수들에 대한 산점도 행렬을 작성하고 변수들 간의 관계를 설명하여라. 특히 판매가격과 세금의 산점도를 보면 특이값 3개가 나타난다. 이들 값의 특성은 무엇인가?
houseprice <- read.csv("houseprice.csv")
head(Houseprice)
pairs(Hou... |
a37af7cfabcf58c01681e5469753074f8ac9c9d0 | 4201e9b754760dc35fc0aeef9df5a8b9d801c47f | /bin/R-3.5.1/src/library/base/man/Bessel.Rd | 85a91ad64a696096c39e11f27944118f52693f00 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"GPL-2.0-only",
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"LGPL-2.1-only",
"LGPL-3.0-only",
"GPL-3.0-only"
] | permissive | lifebit-ai/exomedepth | cbe59cb7fcf2f9183d187f8d466c6620fb1a0c2e | 5a775ae5e2a247aeadc5208a34e8717c7855d080 | refs/heads/master | 2020-03-27T12:55:56.400581 | 2018-10-11T10:00:07 | 2018-10-11T10:00:07 | 146,578,924 | 0 | 0 | MIT | 2018-08-29T09:43:52 | 2018-08-29T09:43:51 | null | UTF-8 | R | false | false | 6,574 | rd | Bessel.Rd | % File src/library/base/man/Bessel.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2018 R Core Team
% Distributed under GPL 2 or later
\name{Bessel}
\title{Bessel Functions}
\alias{bessel}
\alias{Bessel}
\alias{besselI}
\alias{besselJ}
\alias{besselK}
\alias{besselY}
\usage{
besselI(x, nu, expon... |
79a889afb5b0e5b3c0c4b5ced50601dc3cd7ff9c | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googlecivicinfov2.auto/man/RepresentativeInfoResponse.divisions.Rd | 8772cef9d1c4b0fca5cfc25fc224307c00242181 | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 646 | rd | RepresentativeInfoResponse.divisions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/civicinfo_objects.R
\name{RepresentativeInfoResponse.divisions}
\alias{RepresentativeInfoResponse.divisions}
\title{RepresentativeInfoResponse.divisions Object}
\usage{
RepresentativeInfoResponse.divisions()
}
\value{
RepresentativeInfoRespon... |
702c27a1ba89b0caf97acd6ad239da370658bae7 | ca0fce0ee341c347193036d0dc36142d5a841d48 | /ECL_PROJECT_SCRAP.R | 3cec4d69ce52c0bda9ed145a3f6f348faab1cd51 | [] | no_license | seanh21/UCL_Awat_Goal_Rule_Analysis | ad1514192221832d7f36edc33506918a8ae38fc9 | 762299525deb0bc87bd494ac6e18f3301da16e15 | refs/heads/master | 2023-06-10T12:02:37.360429 | 2021-06-29T02:05:18 | 2021-06-29T02:05:18 | 380,922,953 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,055 | r | ECL_PROJECT_SCRAP.R | library("tidyverse")
league_data <- read_csv("ginf.csv")
colnames(league_data)
head(league_data)
hg_sum <- sum(league_data[, "fthg"])
ag_sum <- sum(league_data[, "ftag"])
Venue <- c("Home", "Away")
Goals <- c((hg_sum+hg_ecl_sum),(ag_sum+ag_ecl_sum))
df_sum_of_lg <- data.frame(Venue,Goals)
ggplot(df_sum_of_lg, aes(... |
b9056b8a6b0c8babc6923d99f5db6b1fe1f02605 | f466eb68f09190a8e5972c679f086221021422bd | /man/get_tbl.Rd | a3907341b3d511d7ba046d1e59a4778706fbc02c | [] | no_license | mdelhey/mdutils | 1ffbd4bbcf737133c67c96d69d4539e4e26f98cd | a05ab2cc7fdab24d711b2994db4dcc53f0e2520c | refs/heads/master | 2020-04-10T04:00:27.037351 | 2016-06-02T20:25:29 | 2016-06-02T20:25:29 | 21,291,060 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 464 | rd | get_tbl.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/sql.r
\name{get_tbl}
\alias{get_tbl}
\title{get all rows from a table}
\usage{
get_tbl(con = NULL, x, hive = FALSE)
}
\arguments{
\item{con}{dbi connection}
\item{x}{table name}
}
\description{
get all rows from a table
}
\seealso{
O... |
7b1aaf0e19da8e54dd8156684802841082294f99 | 9cb659691e96fdcf3b0485e880cdcae47c7271c4 | /man/mac_to_binary_string.Rd | f000a8c3cb9785e5d7040dc53148fa8bb4ffdebb | [] | no_license | petr0vsk/MACtools | eecc5e99ff7762667a98e09c99a0355052b81ac6 | 4750d83608b977c64e47fd6753c641e9d604c575 | refs/heads/master | 2020-05-02T19:03:37.420472 | 2019-01-28T17:14:34 | 2019-01-28T17:14:34 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 809 | rd | mac_to_binary_string.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mac-to-binary-string.R
\name{mac_to_binary_string}
\alias{mac_to_binary_string}
\title{Convert MAC address character vector to a binary string representation}
\usage{
mac_to_binary_string(x)
}
\arguments{
\item{x}{character vector of MAC addr... |
8efe42b191395ddc6b7c4718ca0abd181b2e5220 | 04d93fbc0fb3a160cdfbc8aa3d5c258df7b0d0af | /man/plotSpliceGraph.Rd | d332c4bfd7b1b909060ae4a70d396a16d6f04344 | [] | no_license | ldg21/SGSeq | b279000a73e58514a681d3aa802cdf7ec91a3716 | 6c67388c39853ba5df50c94b5c3fd2457288e825 | refs/heads/master | 2021-01-24T08:49:50.563432 | 2020-10-14T19:36:26 | 2020-10-14T19:36:26 | 122,996,617 | 5 | 1 | null | null | null | null | UTF-8 | R | false | true | 4,621 | rd | plotSpliceGraph.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plots.R
\name{plotSpliceGraph}
\alias{plotSpliceGraph}
\title{Plot splice graph}
\usage{
plotSpliceGraph(x, geneID = NULL, geneName = NULL, eventID = NULL,
which = NULL, toscale = c("exon", "none", "gene"), label = c("id",
"name", "label"... |
10c9ce24f2b70cedf8b9e6cc9b56223c56a39c7f | 1e9d315bd9880ded26e11acf8ba2a3ebf0eb0fde | /sigma.R | 5391fbab2a79f13c15c96b550252e061ba5e17eb | [] | no_license | DmitryKokorin/diffmc | cce7de67949037e111ee12003aaa5217dfd0aa6f | 42490984581eb6967540bb443042890212ecd806 | refs/heads/master | 2021-01-19T00:41:46.154106 | 2014-04-05T10:54:48 | 2014-04-05T10:54:48 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,137 | r | sigma.R | #!/usr/bin/Rscript
options <- commandArgs(trailingOnly = TRUE)
params.inputFilename <- options[1]
params.outputFilename <- options[2]
params.width <- as.integer(options[3])
data <- read.table(col.names=c("t",
"x", "y", "z",
"x2", "y2", "z2",
... |
233e1612fefbf76cd4bdbcc61fbabf3e73c63b96 | bad132f51935944a52a00e20e90395990afd378a | /R/ISOCarrierOfCharacteristics.R | 9244ec655ec2a712cfea9f385cc91d4b1c8604de | [] | no_license | cran/geometa | 9612ad75b72956cfd4225b764ed8f048804deff1 | b87c8291df8ddd6d526aa27d78211e1b8bd0bb9f | refs/heads/master | 2022-11-10T21:10:25.899335 | 2022-10-27T22:45:13 | 2022-10-27T22:45:13 | 92,486,874 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 952 | r | ISOCarrierOfCharacteristics.R | #' ISOCarrierOfCharacteristics
#'
#' @docType class
#' @importFrom R6 R6Class
#' @export
#' @keywords ISO carrierOfCharacteristics
#' @return Object of \code{\link{R6Class}} for modelling an ISOCarrierOfCharacteristics
#' @format \code{\link{R6Class}} object.
#'
#' @references
#' ISO 19110:2005 Methodolo... |
d0c63880b0ea9508ac2e9bc5239e28c30245a36e | babdbc9f4b726eba0f6cb3ee496b0c7d8b722a60 | /pipeline_cytof/R/CYTOFclust.R | beec66d614613bd335040b7e3d18bdb12e7d8e51 | [] | no_license | Tariq-K/CYTOF | a8f08ebd970fb5a26a3f38820b57fcd230570d5d | 685e43587bece01e30d811ebba3ab0de2e8924cd | refs/heads/master | 2020-03-28T06:16:55.286232 | 2020-02-27T13:13:52 | 2020-02-27T13:13:52 | 147,824,756 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,157 | r | CYTOFclust.R | # packages
stopifnot(
require(cytofkit),
require(optparse),
require(Rphenograph)
)
# options
option_list <- list(
make_option(c("--infile", "-i"), help="normalised CYTOF data"),
make_option(c("--outfile", "-o"), help="RData object containing clustering info"),
make_option(c("--k"), default... |
facf3299e898a1017614b959ab88feed3e07bcf5 | 27f53c5a9aa2d0962b5cd74efd373d5e9d9e0a99 | /todo-files/TuneControlMies.R | 34bfbe7bcbe24588139b56f09edce8a8390bb11b | [] | no_license | dickoa/mlr | aaa2c27e20ae9fd95a0b63fc5215ee373fa88420 | 4e3db7eb3f60c15ce2dfa43098abc0ed84767b2d | refs/heads/master | 2020-12-24T13:44:59.269011 | 2015-04-18T19:57:42 | 2015-04-18T19:57:42 | 31,710,800 | 2 | 0 | null | 2015-04-18T19:57:43 | 2015-03-05T11:29:18 | R | UTF-8 | R | false | false | 1,077 | r | TuneControlMies.R | ##' @include TuneControl.R
#roxygen()
#
##' Control structure for MI-ES tuning.
##' @exportClass TuneControlMies
##' @seealso \code{\link{makeTuneControlMies}}
#
#setClass(
# "TuneControlMies",
# contains = c("TuneControl")
#)
#
#
##' Create control structure for MI-ES tuning.
##'
##' @title Control for MI-ES tuni... |
515ad11488ed3349ef204ead3c6c7770de239171 | c64b12fb6dcf0122e5dd8417dfef59987508a764 | /tests/testthat/test_inspecting.R | 9dc8f54ca28d7555d63313dcc1097e26755ef9a7 | [] | no_license | SciDoPhenIA/phenomis | 611a6c92e59c40ab049c2d6f14c078e04afbc773 | 1e83ce6997a8d16b89ce5f0f899a1570004ebc0e | refs/heads/master | 2022-06-12T16:43:07.328260 | 2022-06-09T12:40:17 | 2022-06-09T12:40:17 | 253,553,101 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,862 | r | test_inspecting.R | testthat::context("Testing 'inspecting'")
testthat::test_that("inspecting-se", {
sacurine.se <- reading(system.file("extdata/W4M00001_Sacurine-statistics", package = "phenomis"))
sacurine.se <- inspecting(sacurine.se,
figure.c = "none",
report.c = "none... |
c15f3bb5ac2a58db8678178da08ea01bc468911a | a05cd3990215b3b6213d0feee3c928ec9fd19aaa | /tests/testthat.R | 29b3ce8929e321a5e1866f66eabdfef8345370a8 | [] | no_license | cran/rfinterval | e215d6af113f8350bc74878d31404b4fa9907303 | ad2d8758c179a2bd068e8e1c764ca5881bf7126a | refs/heads/master | 2020-12-22T17:58:21.738122 | 2019-07-18T15:40:04 | 2019-07-18T15:40:04 | 236,881,683 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 962 | r | testthat.R | #context("Coverage")
library(testthat)
library(rfinterval)
#test_check("rfinterval")
BeijingPM25 <- BeijingPM25[sample.int(n=nrow(BeijingPM25), nrow(BeijingPM25)), ]
#devtools::use_data(BeijingPM25, overwrite = TRUE)
output <- rfinterval(pm2.5~.,
train_data = BeijingPM25[1:1000, ],
... |
d6055571bcd5f25551280e78ecd9b99a7122e46a | 1cacac56c2f368f02c814966086f22d0c9ef734d | /man/tokens_dutchclauses.Rd | 7a98487f379e29bc4fb3d0747dfd06b6e5073c52 | [] | no_license | vanatteveldt/rsyntax | 5dff4da5c05acd4925aab083c103683a922fda99 | 531f864da09aedaed88cc385b16eae05167b069a | refs/heads/master | 2022-06-22T09:46:21.871170 | 2022-06-06T13:00:41 | 2022-06-06T13:00:41 | 44,437,830 | 32 | 7 | null | null | null | null | UTF-8 | R | false | true | 322 | rd | tokens_dutchclauses.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data.r
\docType{data}
\name{tokens_dutchclauses}
\alias{tokens_dutchclauses}
\title{Example tokens for Dutch clauses}
\format{
data.frame
}
\usage{
data(tokens_dutchclauses)
}
\description{
Example tokens for Dutch clauses
}
\keyword{datasets... |
c78bb549ebcc735f18ba888fd8fa39de72aa7a81 | a6f39c13bb49c330337cf24a9a502326fa6d8199 | /granule-functions/findNearestMovers3.R | 51fc087729992b8284a4f4f3bf2f6a00a720d031 | [] | no_license | apadr007/GranMod | 5779448e91f4fa0466bb6e1b1433246e656c3690 | 1cb0dd96cf20a66d0789d3ee341d4397bc08886a | refs/heads/master | 2020-04-03T07:10:16.879088 | 2017-06-01T21:41:01 | 2017-06-01T21:41:01 | 46,621,577 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 726 | r | findNearestMovers3.R | findNearestMovers3 = function(t){
x=matrix(); x2=list()
y = matrix(); y2 = list()
for (i in 1:nrow(t)){
for (j in 1:nrow(t)){
if (abs(t[i,1] - t[j,1]) <= 0.4) {
x[j] = j
} else { x[j] = NA }
if (abs(t[i,2] - t[j,2]) <= 0.4) {
y[j] = j
} else { y[j] = NA }
... |
753a0670d2ba5dbae10b202d640b541ff5937fdd | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googleplusDomainsv1.auto/man/Activity.object.statusForViewer.Rd | bbbb360fd812a6d29e02c15fdd451917f7129882 | [
"MIT"
] | permissive | GVersteeg/autoGoogleAPI | 8b3dda19fae2f012e11b3a18a330a4d0da474921 | f4850822230ef2f5552c9a5f42e397d9ae027a18 | refs/heads/master | 2020-09-28T20:20:58.023495 | 2017-03-05T19:50:39 | 2017-03-05T19:50:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,177 | rd | Activity.object.statusForViewer.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plusDomains_objects.R
\name{Activity.object.statusForViewer}
\alias{Activity.object.statusForViewer}
\title{Activity.object.statusForViewer Object}
\usage{
Activity.object.statusForViewer(canComment = NULL, canPlusone = NULL,
canUpdate = NU... |
19c0ad92e18f495310e733693c3234d699fea9d5 | 7f83d592c5e502a6675aedb199708856fda304c9 | /R/trunckGUI.R | 01c9e0ce48b791a32a06b584a510021de2db3f0b | [] | no_license | cran/StatFingerprints | f3dd923caacc8b73a27ee9eed6bcfee991a48f33 | 7c31db057c4cc796f3951eaace3854413b2bd2aa | refs/heads/master | 2020-06-04T10:33:56.131798 | 2010-05-26T00:00:00 | 2010-05-26T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,827 | r | trunckGUI.R | trunckGUI <-
function()
{
checkprofile()
if(sum(mat.align)==length(mat.align))
{
tkmessageBox(message="Attention: profiles are not aligned")
stop()
}
if(sum(mat.baseline)==length(mat.baseline))
{
tkmessageBox(message="Attention: baseline must be proceed before range to be efficient")
st... |
202715de63da05ef85ed48760f3ea09cd1951ae3 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/shiny/examples/exprToFunction.Rd.R | 3b9e6d1a09fb87af1185d17a5e30c69baae02813 | [] | 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 | 859 | r | exprToFunction.Rd.R | library(shiny)
### Name: exprToFunction
### Title: Convert an expression to a function
### Aliases: exprToFunction
### ** Examples
# Example of a new renderer, similar to renderText
# This is something that toolkit authors will do
renderTriple <- function(expr, env=parent.frame(), quoted=FALSE) {
# Convert expr t... |
686304b754d14b4eca70ce6bf505a436cccb138f | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/SoyNAM/examples/BLUP.Rd.R | 140d6b5c82cca493c9095da984869479b67e4b73 | [] | 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 | 160 | r | BLUP.Rd.R | library(SoyNAM)
### Name: BLUP
### Title: Best Linear Unbias Predictor
### Aliases: BLUP ENV
### ** Examples
Test=BLUP(trait="yield",family=2:3,env=1:2)
|
7815d2bbd00c527d583f2e4a09779f52dd751cef | 1d0a2f1495a9a9c7e4d31ee1a99de93aee360ac7 | /tests/testthat/test_dynamics.R | 0694b088765844f88b81be17c36cadb8d0f7ec55 | [] | no_license | cran/dfvad | 3e47cb142308135cec2d64796df8e8d4b7438469 | 2cff6b6e48e1e10521a295670819cea2fc40c876 | refs/heads/master | 2021-10-27T23:53:00.254621 | 2021-10-15T08:30:02 | 2021-10-15T08:30:02 | 245,387,739 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 459 | r | test_dynamics.R | context("Testing firm dynamics")
test_that("Firm dynamics with different methods", {
list_test <- readRDS(system.file("extdata", "test_dynamics.rds", package = "dfvad"))
df <- list_test[[1]]
for (i in c("bhc", "gr", "fhk", "bg", "df", "mp")) {
dym <- dynamics(df, "tfp", "s... |
a6c8c2cdb082e8323069deccb136b24894c323df | 02aa5b132bc995fcb21a00f403c432b2b6b82e76 | /man/associations.Rd | 3e3ebcb152fdfd7d3856a1eb4a5d63863986911e | [] | no_license | ropensci/rusda | ea9257c1705e57392c4595f6f737418360abe6dc | fb492630f040a9e355b28606179a0863f753cc74 | refs/heads/master | 2021-06-19T06:57:26.450830 | 2021-01-28T13:31:15 | 2021-01-28T13:31:15 | 40,041,385 | 15 | 6 | null | 2021-01-28T13:31:16 | 2015-08-01T09:07:41 | R | UTF-8 | R | false | true | 3,182 | rd | associations.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/associations.R
\name{associations}
\alias{associations}
\title{Downloads associations for input species from SMML Fungus-Host DB}
\usage{
associations(x, database = c("FH", "SP", "both"),
spec_type = c("plant", "fungus"), clean = TRUE, syn_... |
f0517e8fe258a1d39b4cae7c03d03cfb7be1e1db | 0f104ea64886750d6c5f7051810b4ee39fa91ba9 | /inst/test-data/project-survey/expected/default.R | 460731323113bac284a2400cb2a83e8058c34cbb | [
"MIT"
] | permissive | OuhscBbmc/REDCapR | 3ca0c106e93b14d55e2c3e678f7178f0e925a83a | 34f2154852fb52fb99bccd8e8295df8171eb1c18 | refs/heads/main | 2023-07-24T02:44:12.211484 | 2023-07-15T23:03:31 | 2023-07-15T23:03:31 | 14,738,204 | 108 | 43 | NOASSERTION | 2023-09-04T23:07:30 | 2013-11-27T05:27:58 | R | UTF-8 | R | false | false | 1,239 | r | default.R | structure(list(participant_id = c(1, 2), redcap_survey_identifier = c(NA,
NA), prescreening_survey_timestamp = structure(c(1520351563,
1520351595), class = c("POSIXct", "POSIXt"), tzone = "UTC"),
dob = structure(c(17596, 17595), class = "Date"), email = c("aaa@bbb.com",
"ccc@ddd.com"), has_diabetes = c(1, 0... |
6a1cbca04a6df4faf6a542fb291b2dddd02886ef | a588dd1a34555dd71c898c82fbc7016dcc9cbdb3 | /DepressionModels/R/main.R | 364ee20d4694473870676f310aaf9c8ca8149283 | [] | no_license | NEONKID/StudyProtocolSandbox | 5e9b0d66d88a610a3c5cacb6809c900a36bc35c3 | c26bd337da32c6eca3e5179c78ac5c8f91675c0f | refs/heads/master | 2020-03-23T14:02:11.887983 | 2018-10-19T05:33:13 | 2018-10-19T05:33:13 | 141,651,747 | 0 | 1 | null | 2018-07-20T02:10:06 | 2018-07-20T02:10:06 | null | UTF-8 | R | false | false | 1,018 | r | main.R |
main <- function(){
library(DatabaseConnector)
library(PatientLevelPrediction)
library(DepressionModels)
options('fftempdir' = 's:/fftemp')
connectionDetails <- createConnectionDetails(dbms = "pdw",
server = Sys.getenv('server'),
... |
6c5d087c43ab6bc4fcd7e2e697d2afd2d3168e24 | dfc54f1755f9eea3037f93b40a9aec8eeed57783 | /workout2/saving-investment-simulation/app.R | 1635c6a198100bd465a7d1371dd782c40c67c0a5 | [] | no_license | stat133-sp19/hw-stat133-mingyueyang | eea107ce497f1847a98663b14e9610643072d042 | 09dc2477cc3ec20e2f43f4e05464dd0ed374be9d | refs/heads/master | 2020-04-28T08:04:20.557614 | 2019-05-03T23:42:20 | 2019-05-03T23:42:20 | 175,114,010 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,837 | r | app.R | #
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(ggplot2)
library(dplyr)
# Define UI for application
ui <- fluidPage(
# Application ti... |
0bc9d714eedc0aea2ecb3a9991bc0e9fe1cade1a | e1f9dbb834bc550b243e325f7b8eb639d3d33c56 | /man/fetchFX.Rd | 57a3174f9b6045f68b63bd0ec82e94de2b8a78be | [] | no_license | enricoschumann/pacificFX | 55a543908e7732e965880ecb2271112ffe5b0423 | c26b1b607c0c15016867648b62e18f0c7ac85f2b | refs/heads/master | 2021-05-04T11:47:09.881858 | 2019-02-24T07:18:08 | 2019-02-24T07:18:08 | 52,907,420 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,019 | rd | fetchFX.Rd | \name{fetchFX}
\alias{fetchFX}
\title{
Download historical FX data
}
\description{
Download historical FX data from the PACIFIC Exchange Rate
Service, run by Werner Antweiler at Sauder School of Business,
University of British Columbia. Visit the homepage
\url{http://fx.sauder.ubc.ca/} to learn more.
}
\usage... |
d8e63a3bc5d52c93f4ad8764940d5f1b728b8928 | 9aafde089eb3d8bba05aec912e61fbd9fb84bd49 | /codeml_files/newick_trees_processed/8641_1/rinput.R | 169d7a3bb9878b007c8e1c819510bf865be02e2d | [] | no_license | DaniBoo/cyanobacteria_project | 6a816bb0ccf285842b61bfd3612c176f5877a1fb | be08ff723284b0c38f9c758d3e250c664bbfbf3b | refs/heads/master | 2021-01-25T05:28:00.686474 | 2013-03-23T15:09:39 | 2013-03-23T15:09:39 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 135 | r | rinput.R | library(ape)
testtree <- read.tree("8641_1.txt")
unrooted_tr <- unroot(testtree)
write.tree(unrooted_tr, file="8641_1_unrooted.txt") |
b3ef58380f211a423095bce5ed6695fe216c6c16 | 30d2ed023fed988d04dbb83e66edba3df96dad74 | /dashboard/dash_header.R | 89ac8a985f95898a663d45cda3a37618750fd537 | [
"MIT"
] | permissive | arestrom/Chehalis | 7949a449a0e4ec603b98db72b9fbdefd0c39529a | c4d8bfd5c56c2b0b4b58eee3af7eb1a6b47b2695 | refs/heads/master | 2023-05-31T05:58:51.247660 | 2021-06-29T17:26:19 | 2021-06-29T17:26:19 | 295,434,189 | 0 | 0 | MIT | 2021-05-26T22:11:54 | 2020-09-14T14:03:02 | HTML | UTF-8 | R | false | false | 325 | r | dash_header.R | #=============================================================
# ShinyDashboardPlus header function
#=============================================================
dash_header = dashboardHeader(
fixed = TRUE,
title = tagList(
span(class = "logo-lg", "Chehalis Basin data"),
img(src = "ShinyDashboardPlus.svg"... |
f98a03cad70e86f15e1c4a7ee23756a92118a014 | 359cbcaf78f3d70062610f13e01ff49b7bf202de | /[R] lab13.R | cdf717dff164bc5722aa5852ad41ae8561686a3d | [] | no_license | haoingg/analysis | 8bb4b776b8fe95cdc5dd0acacc2a08d752b2584a | a1be341a77ba9ee859816d2b5d9cdb8c966f5c92 | refs/heads/master | 2023-06-02T06:09:02.956848 | 2021-06-25T14:07:53 | 2021-06-25T14:07:53 | 355,138,994 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 885 | r | [R] lab13.R | library(wordcloud2)
library(KoNLP)
data <- readLines("output/yes24.txt", encoding='UTF-8'); data
txt <- extractNoun(data); txt
#undata <- gsub("[[:punct:]]","",txt)
undata <- unlist(txt)
undata2 <- gsub("^[가-힣]","", txt)
text <- Filter(function(x){nchar(x) >= 2}, undata2)
#text <- Filter(function(x){nchar(x) >= 2|ncha... |
572f2ffcc71b1ea11189593df7114aad38d903ba | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/phrasemachine/examples/coarsen_POS_tags.Rd.R | 27925b78532e3fb84b73e1f56d0d3be81fc9c9df | [] | 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 | 196 | r | coarsen_POS_tags.Rd.R | library(phrasemachine)
### Name: coarsen_POS_tags
### Title: Coarsen POS tags
### Aliases: coarsen_POS_tags
### ** Examples
pos_tags <- c("VB", "JJ", "NN", "NN")
coarsen_POS_tags(pos_tags)
|
14f2af86530272e58004807e02494e98acc84150 | eb5d6c88a8ca82b8d78fc55da93734cbd09f231b | /man/splitIntoStatements.Rd | ab11673ba0a2753d739a1ae6cda4ec94046cc7a9 | [] | no_license | uhjish/sasMap | 79b9675e648c9dbe93423552a7d8d2d2fba0f3e3 | 769f28467fad3d0c4b3d51c6dde7389366d2b494 | refs/heads/master | 2021-01-19T20:36:50.691431 | 2017-08-20T21:18:00 | 2017-08-20T21:18:00 | 101,232,842 | 1 | 0 | null | 2017-08-23T23:19:06 | 2017-08-23T23:19:06 | null | UTF-8 | R | false | true | 492 | rd | splitIntoStatements.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utility_functions.R
\name{splitIntoStatements}
\alias{splitIntoStatements}
\title{Split SAS code into statements}
\usage{
splitIntoStatements(sasCode)
}
\arguments{
\item{sasCode}{Character string containing SAS code}
}
\description{
Split SA... |
782722fc52b58e1f09b168c038722892fd59c7d8 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/Matrix/examples/all-methods.Rd.R | 0d28db0dfdbaa84cdd2d1abdcb0528586000d296 | [] | 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 | 984 | r | all-methods.Rd.R | library(Matrix)
### Name: all-methods
### Title: "Matrix" Methods for Functions all() and any()
### Aliases: all-methods all,Matrix-method any,Matrix-method
### all,ldenseMatrix-method all,lsparseMatrix-method all,lsyMatrix-method
### any,lMatrix-method
### Keywords: methods
### ** Examples
M <- Matrix(1:12 +0,... |
70cff931ebf6fa812cdab8ea87c36d057082d985 | 6a28ba69be875841ddc9e71ca6af5956110efcb2 | /Introduction_To_Mathematical_Statistics_by_Robert_V_Hogg_Joseph_W_Mckean_Allen_T_Craig/CH4/EX4.10.1/Ex4_10_1.R | 73811731069338fcb7d0114c9dadca18212753b5 | [] | 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 | 121 | r | Ex4_10_1.R | #Page no 287
f<-function(v)
{
(30*(v^4))*(1-v)
}
i<-integrate(f,lower=0,upper=0.8)
ans<-1-i$value
round(ans,2) |
690ffb7b1abd3ebc3042f5f2459202e6ee85f4af | c08e6b516a3d341d1fdb893448922082dc3626cf | /R/dimsum__filter_reads.R | d60c5a6279db04143d0f96507017fbcb247cef50 | [
"MIT"
] | permissive | lehner-lab/DiMSum | eda57459bbb450ae52f15adc95d088747d010251 | ca1e50449f1d39712e350f38836dc3598ce8e712 | refs/heads/master | 2023-08-10T17:20:39.324026 | 2023-07-20T15:29:47 | 2023-07-20T15:29:47 | 58,115,412 | 18 | 5 | null | null | null | null | UTF-8 | R | false | false | 5,672 | r | dimsum__filter_reads.R |
#' dimsum__filter_reads
#'
#' Concatenate reads (with or without reverse complementing second read in pair).
#'
#' @param input_FASTQ Path to input FASTQ file (required)
#' @param input_REPORT Path to input report file (required)
#' @param output_FASTQ Path to output FASTQ file (required)
#' @param output_REPORT Path ... |
3721a13341ebe9786a03ae1be84f3b8ad512bd51 | 1903367ccf3ffcf2dc3680fabfa58a99de58cb5e | /R/foci.R | d3e9aa2440b7dabd270ad095c4ffd9ad175b0d5b | [] | no_license | cran/FOCI | f97477ce4e6bd02e7468d6d5aa3c5af31c95f505 | 8ebce7c9ce307796724fbdf020e43abf7fd75b81 | refs/heads/master | 2021-07-12T12:02:38.917189 | 2021-03-18T22:00:07 | 2021-03-18T22:00:07 | 236,599,263 | 4 | 1 | null | null | null | null | UTF-8 | R | false | false | 12,556 | r | foci.R | ####################################################################
# MAIN FUNCTIONS:
# foci_main: the core function for implementing the foci algorithm
# foci: Performs feature ordering by conditional independence
####################################################################
# foci_main ---------------------... |
c9aad05e2602d0a5038f58a9011f798ec75701f2 | 512251113212381e4704309f9b5f386118125bc6 | /man/toolCodeLabels.Rd | 63efd3d02dad5d0535ba6901e2f10cdba090f99e | [] | no_license | johanneskoch94/madrat | 74f07ee693d53baa5e53772fc41829438bdf1862 | 2a321caad22c2b9b472d38073bc664ae2991571f | refs/heads/master | 2023-08-09T11:07:47.429880 | 2021-09-03T13:04:32 | 2021-09-03T13:04:32 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,001 | rd | toolCodeLabels.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/toolCodeLabels.R
\name{toolCodeLabels}
\alias{toolCodeLabels}
\title{Tool: CodeLabels}
\usage{
toolCodeLabels(get = NULL, add = NULL)
}
\arguments{
\item{get}{A vector of hash codes which should be replaced}
\item{add}{Additional entries tha... |
279481e695baeadb59d6ad855f90de27107990dd | 636ef7dfc05c678b24fda5aa9fea3323c457354c | /R/zzz.R | 766862ddd85463c58f65d737065377ad46660d31 | [] | no_license | bschulth/jsTreeRExample | ea1921ae9f5764b70837558eef1db1b70511eef0 | cf676f09717f25d990cdbc05fc9e75883a682659 | refs/heads/master | 2023-08-03T01:04:40.872464 | 2021-09-18T19:49:58 | 2021-09-18T19:49:58 | 407,584,851 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 411 | r | zzz.R | #++++++++++++++++++++++++++++++++++++++++++++++++++++++
# Before package sealing
#++++++++++++++++++++++++++++++++++++++++++++++++++++++
.onLoad <- function(libname, pkgname) {
options(keep.source = TRUE)
invisible()
}
#++++++++++++++++++++++++++++++++++++++++++++++++++++++
# After package sealing
#+++++++++... |
62859a8cdd536305ca854d5d27254f9359f0d45f | cbc7f6ba280cba7cd297520c0eb7916a815045e2 | /cachematrix.R | 9509cf4d746263ed3dbdca12f1e65451ff7fc22e | [] | no_license | atorrents/ProgrammingAssignment2 | dd14d61e3b349c24029f7a2ccb934691ee01f1b0 | 22b1c048c9a5c766533a1e02c1d030519bca2f35 | refs/heads/master | 2021-01-18T04:14:36.166369 | 2014-07-16T14:40:54 | 2014-07-16T14:40:54 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,652 | r | cachematrix.R | ## Time-saving system, caching the inverse of a matrix
## when we need calculate it several times
## function: makeCacheMatrix
## (uses special operator <<- which stores values in "parent" environment)
## Usage:
## a<-makeCacheMatrix(matrix <default NULL>) >> creates cache matrix a
## This matrix will cache its inver... |
77af801303ed5b7d55597280c436fd10a4ab2225 | 57c9c8efb9dd8e88d11e0a6b755f862aeb445eef | /human/sveval/repeatmasked/eval.R | 227d208013202ed176bc12e8eb7e3b962488299a | [
"MIT"
] | permissive | quanrd/sv-genotyping-paper | ce8471699f2e3f0ad874ebdaf259bc8e37428c0e | 627d6049fef1fbb26a0c63c96301dff293e0c58d | refs/heads/master | 2022-03-11T22:02:20.899651 | 2019-11-25T23:02:08 | 2019-11-25T23:02:08 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,227 | r | eval.R | library(sveval)
library(VariantAnnotation)
library(ggplot2)
truth.vcf = readSVvcf('hgsvc-truth-baseline.norm.rmsk.vcf.gz', vcf.object=TRUE)
calls.vcf = readSVvcf('hgsvc-vg-HG00514.norm.rmsk.vcf.gz', vcf.object=TRUE)
min.cov = .8
truth.reps = ifelse(info(truth.vcf)$RMSKCOV>min.cov, info(truth.vcf)$RMSKCLASS, NA)
truth... |
b4e57a4b014f401a8ce2adab5da25dd033e746ab | 8ea89ec7e70995d44aee36a0698a20e50fa91d7d | /examples/sqlite/update_samples.R | 77843cdc2f13e1afd0265dfe151e56c8c6c8976d | [
"MIT"
] | permissive | DrRoad/shiny-chart-builder | 6e353b0ee12772e93af85a7b295a7784700bc5e3 | e5072ab8bfcff1a897e6aac448ce00de0b4d58aa | refs/heads/master | 2020-06-05T11:16:11.780338 | 2017-11-07T03:43:10 | 2017-11-07T03:43:10 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,557 | r | update_samples.R | # Make sure your working directory is that of the project, not "example".
source('example/config.R')
allTables = queryDb("SELECT name tablename FROM sqlite_master WHERE type='table'")
getDef = function(table)
{
t=queryDb(paste0("pragma table_info(", table, ")"))
t$type = case_when(
t$type == "INTEGER" ~ "int... |
e064a2435e105b6936b60a2c3cc6d2e7bae3750f | 29585dff702209dd446c0ab52ceea046c58e384e | /CovSelHigh/R/cov.sel.high.R | a7df087fa20621a9c1ad6d1b6f3790e8704d074f | [] | no_license | ingted/R-Examples | 825440ce468ce608c4d73e2af4c0a0213b81c0fe | d0917dbaf698cb8bc0789db0c3ab07453016eab9 | refs/heads/master | 2020-04-14T12:29:22.336088 | 2016-07-21T14:01:14 | 2016-07-21T14:01:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 61,311 | r | cov.sel.high.R | cov.sel.high<-function(T=NULL, Y=NULL, X=NULL,type=c("mmpc","mmhc","rf","lasso"), betahat=TRUE, parallel=FALSE, Simulate=TRUE, N=NULL, Setting=1, rep=1, Models=c("Linear", "Nonlinear", "Binary"),...){
Simulate<<-substitute(Simulate)
N<<-substitute(N)
Setting<<-substitute(Setting)
Rep<<-substitute(rep)
Models... |
3f9a5f865cc3e5002d901e47e406e9abe48d9e35 | 1dcd515a6742140b05c00b098115c7909f6ced42 | /summary_data.R | 2b2a9a10cc80020c393a670e780ce9de38e81a3b | [] | no_license | hearyt/FC-manuscript | 549912690723c04a8fb6d6142a8b70b31a2884d1 | 7df739df232121cca805f58d08ec4560a7fc53c1 | refs/heads/master | 2021-05-15T16:07:50.722710 | 2017-11-03T19:06:28 | 2017-11-03T19:06:28 | 107,435,293 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,575 | r | summary_data.R |
summary_data <- function(lv, d1, k, k.parent, k.den, lab.y, binwidth, caption.fig, caption.tab)
{
#############
## data QA ##
#############
# sum of all children nodes' numbers of events (numerator)
d1$sum = apply(d1[k:(k+length(lv)-1)], MARGIN = 1, FUN=sum)
## percentage out of parent node
... |
8c7fabc440b1f5e53dbfaa612065e7e1d73caa74 | f0b675fe8fdab8d263ccd0faf9d02962697c2f51 | /R/poolData.R | 255379a2aa880b14d197e4d7cb94530a3348cca0 | [] | no_license | kemacdonald/iChartAnalyzeR | bef94793c8f175d335c14fd2d6155ccb4c925a36 | a2a1c352ee692a52d8c7a50e4a79964934c44bb5 | refs/heads/master | 2020-03-21T04:07:36.997658 | 2018-09-18T17:47:07 | 2018-09-18T17:47:07 | 138,092,029 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,503 | r | poolData.R | #' Pool Data
#'
#' This function aggregates iChart RT and Accuracy for each trial, participant, and condition,
#' returning this information in a data frame.
#'
#' @description \code{poolData()} computes the mean accuracy or RT for each each participant and condition.
#' @param iChart A data frame in iChart format with... |
510845b019af382b6ac903a168b7fb2465323847 | 18cd6280d38d276d723f766c57f7e7fb1a3da3f5 | /cachematrix.R | dde85648edb644ce3059bf8d1c40c628f4ad06e2 | [] | no_license | morenz75/ProgrammingAssignment2 | 29802f405bac70c0a56a1db8f906dcf45449db0a | c4a4185a63b3771c1e244a75264ae2ad6539d302 | refs/heads/master | 2020-12-30T22:10:03.437043 | 2015-04-16T14:44:25 | 2015-04-16T14:44:25 | 33,993,836 | 0 | 0 | null | 2015-04-15T12:57:10 | 2015-04-15T12:57:10 | null | UTF-8 | R | false | false | 1,883 | r | cachematrix.R | ## Put comments here that give an overall description of what your
## functions do
# This function get a matrix (supposed to be reversible) and return it's reversed ones
# The reversed matrix is calculated just one time, so if we call cacheSolve it take
# the cached version of the reversed matric if exists, othewise ... |
6858ce4f3d5733dc0498d08f76048346108e4017 | 46b4592d82aac98165d6d65225cefa42714be853 | /inspkg.r | 7cc317056eed4bec7aec57eec4db954ec20cee16 | [] | no_license | nhchauvnu/rpkg | be852c3fd0eb841efdc5dffa19b1a218150c4a57 | 8c3519ebc95a6e87c113aa360ff07c8c8ee529fa | refs/heads/master | 2022-02-17T12:07:34.609758 | 2022-02-04T10:48:43 | 2022-02-04T10:48:43 | 32,579,295 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 962 | r | inspkg.r | file = paste('wget -O -', 'https://raw.githubusercontent.com/nhchauvnu/rpkg/master/rpkg.csv')
pkg = as.character(read.csv(pipe(file))$pkg)
chkpkg = function(pkg) {
pkglist = installed.packages()[,1]
m = sum(pkglist == pkg)
if (m <= 0) return(FALSE)
else return(TRUE)
}
printstat = function(pkg) {
if (chkpkg(pkg))... |
651f51296862825add8ddc95ac77dfc23a72d3bc | 4295a487ac3bca6a1493001f5090f5c2c4a5297e | /man/print.JMR.Rd | f5e75a33546009d09503d4344cdb125fefd99507 | [] | no_license | sa4khan/JMR | f8c732155830558ddbf7d3d00a1a0f3ea6d5d56c | fd801ddf778f30054b6cab0de5bc09964dfc14a3 | refs/heads/main | 2023-06-26T17:25:39.893637 | 2021-07-13T01:44:56 | 2021-07-13T01:44:56 | 385,138,057 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 433 | rd | print.JMR.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/JMRprint.R
\name{print.JMR}
\alias{print.JMR}
\title{Prints JMR objects}
\usage{
\method{print}{JMR}(x, digits = max(options()$digits - 4, 3))
}
\arguments{
\item{x}{A \code{JMR} object}
\item{digits}{minimal number of significant digits}
}
... |
c2f2ee0dd982ff14d9153c13cfa0df2f5a067a5a | 223893fbf2d8b796dfcc9593ccaca4195d86b45d | /cachematrix.R | ef25ca81fef7ef33e1b364b64d9aa7b1a20df35d | [] | no_license | dscourse1/ProgrammingAssignment2 | 8c922d3375df06496439e59718c65c0f6d09fbf5 | bf9b3a4709201edb7af30272492ab921192d411a | refs/heads/master | 2020-12-27T05:30:58.643336 | 2015-01-25T07:36:41 | 2015-01-25T07:36:41 | 29,805,590 | 0 | 0 | null | 2015-01-25T06:42:52 | 2015-01-25T06:42:50 | null | UTF-8 | R | false | false | 1,561 | r | cachematrix.R | ## Functions to support caching of the inverse of a matrix
## usage:
## > x <- makeCacheMatrix(matrix(rnorm(16), 4, 4))
## > cacheSolve(x)
## [,1] [,2] [,3] [,4]
## [1,] -0.5217698 0.59491642 -0.3728793 -0.09381126
## [2,] 1.5125709 -0.58157656 0.4206847 -0.32677740
## [3,] 0.1860804... |
2f887ebd4826b55734d851191e82fd1983012dc9 | 77b52dc4be6980a7066a435d53a18ecc6574be77 | /One Predictor Models/R_estimates.R | 110a7b4f179eba93bed1fd6d6b7627cd1aad78e5 | [] | no_license | AgneseG/RatioImputationImprovements | 32c0e3a505d9334b02567b586a6b02c4c565ec7e | 9cd348d79547b67a2296eaf175caaf3f10a34d87 | refs/heads/master | 2020-07-22T22:37:26.095907 | 2019-09-16T18:08:21 | 2019-09-16T18:08:21 | 207,353,383 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,081 | r | R_estimates.R | # --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
### In this file, the ratio R has been estimated for the wls, Huber and Tukey estimators.
#### Final estimates... |
6b021c76b6281a7ab665521b9a0ee69bd5ff5b2f | d4bbec7817b1704c40de6aca499625cf9fa2cb04 | /src/lib/distributions/chi-2/__test__/fixture-generation/dnchisq2.R | a2af860b9b73c25eeb663cdd760e387b110b72c5 | [
"MIT"
] | permissive | R-js/libRmath.js | ac9f21c0a255271814bdc161b378aa07d14b2736 | 9462e581da4968938bf4bcea2c716eb372016450 | refs/heads/main | 2023-07-24T15:00:08.372576 | 2023-07-16T16:59:32 | 2023-07-16T16:59:32 | 79,675,609 | 108 | 15 | MIT | 2023-02-08T15:23:17 | 2017-01-21T22:01:44 | TypeScript | UTF-8 | R | false | false | 2,472 | r | dnchisq2.R | #> x=seq(0,40,0.5);
#> y=dchisq(x,13,ncp=8, log=T)
#> plot(x,y, type='l')
#> data.frame(x,y)
# x y
1 0.0 -Inf
2 0.5 -18.0780230497580163
3 1.0 -14.3663511842686908
4 1.5 -12.2396822876410578
5 2.0 -10.7634009342061265
6 2.5 -9.6445091114802803
7 3.0 -8.7524278409... |
d15429d85c5029265625d3e5fabe303aea685718 | f23496883cd9ee0267027e74946647fc809735d5 | /simulated/velezmalaga_plots.R | 053adec4ce8386a8e6c4bfc1fa0dfca47ac4f6fe | [] | no_license | davgutavi/IoT_Smart_Agent | 0e847b0f1397c7d38342a97c2b443642d20402d5 | 788a3fcad141e1c4dc4d793ae9ea0a88caf2c5c4 | refs/heads/master | 2021-04-03T08:37:52.786031 | 2020-01-20T13:06:27 | 2020-01-20T13:06:27 | 124,416,104 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 10,832 | r | velezmalaga_plots.R | source("simulated/paths.R")
require(ggplot2)
# Presure ----
velezmalaga.pressure <- read.csv(path.velezmalaga.pressure)
velezmalaga.pressure.01 <- velezmalaga.pressure[velezmalaga.pressure$entity_id=="weatherobserved-velezmalaga-01",]
velezmalaga.pressure.02 <- velezmalaga.pressure[velezmalaga.pressure$entity_id=="we... |
4047410ed4b74d60d17b841d106b96ee07f294c8 | 9463229d7d9cc5902971aed9c9c4efe2f4083c50 | /R/vis_functions.R | 93c3badc6f9d00744b1c1c379c854774d3f66bac | [] | no_license | sapfluxnet/sapfluxnetQC1 | df66fb4c8282c14aa8921e668f671928c73e300a | c66115798d0c0814f399b1df6505f146594b6bdf | refs/heads/master | 2021-05-01T12:53:11.380754 | 2019-03-01T09:15:47 | 2019-03-01T09:15:47 | 52,454,181 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 23,575 | r | vis_functions.R | ################################################################################
# VISUALIZATION FUNCTIONS #
# #
# Functions to visualize the data ... |
c95adf490093ceb91aa061b7f67c2a7c9e003d38 | a09eaebce8c5e5aca5b25e18072ab9092b120680 | /main/4_model_loglinear.R | 05e7b1ccdb8ccf11d788824ba185af07973ff9ef | [] | no_license | byyangyby/ct_rt_hk | ad72afda8c534cb85d2b3694ebbcb37578139704 | 52f6101f754e66d951e3a0d22d8f50223f6a3ab7 | refs/heads/main | 2023-07-12T20:33:35.650050 | 2021-08-23T03:29:50 | 2021-08-23T03:29:50 | 398,963,437 | 0 | 0 | null | 2021-08-23T03:36:03 | 2021-08-23T03:36:02 | null | UTF-8 | R | false | false | 5,346 | r | 4_model_loglinear.R | #------------
# log-linear
# Rt and Ct
# also include reverse validation
#------------
######################################################
## data_daily_all: daily case counts/sample counts, incidence-based Rt;
## daily Ct mean, median and skewness (imputed) from "1_merge_data"
## co... |
3399fab5b28237eb279bcc6541bdb80796d8d2e9 | c6ebbbfb3250deb51005c9d7a91a5b1e72407d20 | /ui.R | 6dede83ed77f71799303b7fb4f080387d54c1129 | [] | no_license | M-A-AliKhan/Main | 57d09d8c67b05c59c4954b1b0094ce0aa37c8f3a | 07f47c55c8918fbb4c0f45011f9953ef4b66be4e | refs/heads/master | 2021-01-10T17:00:24.531120 | 2015-05-24T14:23:31 | 2015-05-24T14:23:31 | 36,175,010 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,183 | r | ui.R | # Load shiny library
library(shiny)
# All UI elements must be inside shinyUI()
shinyUI(
# Set up a page with a left-hand sidebar menu.
pageWithSidebar(
# The header/title of the page.
headerPanel("Dynamic Plotting"),
# User inputs go in a sidebar on the left.
side... |
3a3bd05e584b0547de031823396d1b008e040c97 | 79c3864f9edb99e373243fe2fbf14a8b6933a7f4 | /R/get_multiple_LVs.R | 1a16dd93c1eb9267c5bbe8e314f7f62c29301556 | [
"MIT"
] | permissive | acsala/sRDA | b7f33047b25cf5a81f702ae7a4936115bff4caa1 | e6b3635d2bc79bd736825ecc40c3a1110bae9cd5 | refs/heads/master | 2022-08-12T03:27:13.835323 | 2022-07-27T08:53:04 | 2022-07-27T08:53:04 | 124,358,659 | 4 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,145 | r | get_multiple_LVs.R | get_multiple_LVs <- function(X,
Y,
penalization,
lambda,
nonzero,
nr_latent=1,
stop_criterium = 1 * 10^-5,
... |
19851133fb4f9ad4230aa1a7b7b4e1c8626c4e16 | 0539c05542edb96da66aab6943e785e9d81fe980 | /plot4.R | 517519f71d92ea01eff9013a1a09736be594a927 | [] | no_license | metustat/ExData_Plotting1 | f8fea02a102906be7845f160b323830ca1065d9a | ea36227fd333d3292fdf857ad5a1b72304851b83 | refs/heads/master | 2020-04-05T23:27:44.535844 | 2015-08-07T20:06:03 | 2015-08-07T20:06:03 | 39,706,154 | 0 | 0 | null | 2015-07-25T23:19:31 | 2015-07-25T23:19:31 | null | UTF-8 | R | false | false | 1,526 | r | plot4.R | fileUrl<-"https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(fileUrl,destfile="data.zip")
unzip("data.zip",list=TRUE)
data<-read.csv2(unz("data.zip","household_power_consumption.txt"),
header=TRUE,colClasses=c("character"))
options(warn=-1)
for(i in 3:9... |
55c526dcf4e6bd67c99a2f4ac21b2835110349ba | c287ac86f02fe8b3fc5ecc97fe761a636ee2f72c | /man/rbinorm.Rd | 43d501bb73fd76c372f0e37dc5882a092c061745 | [] | no_license | cran/FamilyRank | 88b9d194faacf337f0a0f2acfd8c6c2fa5387e82 | 0c31311610f1cfa4e7bdf1e41dda814bf0ccd772 | refs/heads/master | 2023-03-03T03:25:58.937043 | 2021-02-05T07:50:08 | 2021-02-05T07:50:08 | 336,239,780 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 962 | rd | rbinorm.Rd | \name{rbinorm}
\alias{rbinorm}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Bimodal Normal Distribution}
\description{Simulates random data from a bimodal Gaussian distribution.}
\usage{
rbinorm(n, mean1, mean2, sd1, sd2, prop)
}
%- maybe also 'usage' for other objects documented here.
\argumen... |
673090c7649058e71d72ae6164e0c609c798aa9e | efe3bdc6afd1f111ece86b830fc92cc4bec8910e | /man/contact_df_countries.Rd | bb1525fd9fac7f9c032bfa818d93a1210d679107 | [
"MIT"
] | permissive | Bisaloo/contactdata | cd2b35db31ae2d32b52721bc13e01cc80a5e4484 | 444ba7569703863092ed488f8f4b572a6453c5e6 | refs/heads/main | 2023-04-11T15:34:34.543076 | 2023-03-22T11:19:38 | 2023-03-22T11:19:48 | 293,047,665 | 6 | 2 | NOASSERTION | 2023-09-05T11:32:09 | 2020-09-05T09:52:13 | R | UTF-8 | R | false | true | 1,477 | rd | contact_df_countries.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/contact_countries.R
\name{contact_df_countries}
\alias{contact_df_countries}
\title{Get a data.frame (in long format) of contact data for multiple countries}
\usage{
contact_df_countries(countries, ...)
}
\arguments{
\item{countries}{A charac... |
dd5ecc8dce421807b4a4c7528618b117cc1d238a | 43b17584478c0360d0fdced151db43c35728837a | /man/set_gitlab_connection.Rd | fc79babb58778a4558fc473061d6d53239a1de67 | [] | no_license | cran/gitlabr | 51357cc4c136b4d5125a1d39aec63ea62ef509d1 | b8d64273024933804044ca8eeab18930a4611c55 | refs/heads/master | 2022-10-03T07:18:40.338952 | 2022-09-13T10:00:02 | 2022-09-13T10:00:02 | 48,080,948 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 990 | rd | set_gitlab_connection.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/global_env.R
\name{set_gitlab_connection}
\alias{set_gitlab_connection}
\alias{get_gitlab_connection}
\alias{unset_gitlab_connection}
\title{Get/set a GitLab connection for all calls}
\usage{
set_gitlab_connection(gitlab_con = NULL, ...)
get... |
19b2f5e4cb2ec6ec474b6ba70a24a2464a5411e4 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/geosapi/examples/GSOracleNGDataStore.Rd.R | 8b5b776aefe6d792e8c71d1ad329189e824bfa63 | [] | no_license | surayaaramli/typeRrh | d257ac8905c49123f4ccd4e377ee3dfc84d1636c | 66e6996f31961bc8b9aafe1a6a6098327b66bf71 | refs/heads/master | 2023-05-05T04:05:31.617869 | 2019-04-25T22:10:06 | 2019-04-25T22:10:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 283 | r | GSOracleNGDataStore.Rd.R | library(geosapi)
### Name: GSOracleNGDataStore
### Title: Geoserver REST API OracleNGDataStore
### Aliases: GSOracleNGDataStore
### Keywords: DataStore OracleNG api geoserver rest
### ** Examples
GSOracleNGDataStore$new(dataStore="ds", description = "des", enabled = TRUE)
|
207b16f0721a41f3d03f768bc77d18603934b086 | 2bd293d9eff164a31e5ca98900a3b623aced5815 | /man/drawbipl.catPCA.Rd | e3cbfdaea80a3bb115093d1b90abd36a5e5a24c0 | [] | no_license | carelvdmerwe/UBbipl3 | 213a17f60e7cd1796f51ce2a2f5fc097b57e722c | ea5bbe4767d42d92d949e42b1db199fc8d5e12f0 | refs/heads/master | 2020-06-07T04:44:22.514152 | 2019-06-20T13:39:36 | 2019-06-20T13:39:36 | 192,926,846 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 128 | rd | drawbipl.catPCA.Rd | \name{drawbipl.catPCA}
\alias{drawbipl.catPCA}
\title{
DRAW CATEGORICAL PCA BIPLOTS
}
\description{
See Understanding Biplots.
} |
0e986de1becbcb737312eaf8755f9ebb2a8d8c70 | 202fb2f3a908b0c002ef6859275a617ffa6a51e8 | /man/multiplicativeSeasonalityDecomposition.Rd | 9f02405b30b968bcd1771c80d0966e39aa0ddee4 | [] | no_license | jdestefani/MM4Benchmark | ad68d68a000dc879be2bcb91acb0bf4aaa48cc9f | bb8f185ce984121b084d109912e7df1566d7fb26 | refs/heads/master | 2023-09-04T17:58:34.312342 | 2021-11-20T21:30:09 | 2021-11-20T21:30:09 | 364,299,203 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 745 | rd | multiplicativeSeasonalityDecomposition.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/benchmarks.R
\name{multiplicativeSeasonalityDecomposition}
\alias{multiplicativeSeasonalityDecomposition}
\title{multiplicativeSeasonalityDecomposition}
\usage{
multiplicativeSeasonalityDecomposition(input, fh)
}
\arguments{
\item{input}{\ite... |
642947d1b807d4902d3b3bc6db02da9b2eb66a2a | 915dd8fb8c341c90288f84fd19a9d72ad4f11b9c | /chemenhance.R | f7b2f228b0a30943ab2915542366c805942ef0d9 | [] | no_license | martwine/Transfer-velocity-core-scheme | b8db0c3889d0d19738546b18148a3d7385768046 | e0786e1437ef90845294123552ca188eb621d19a | refs/heads/master | 2016-09-06T07:49:27.708907 | 2012-07-03T08:07:40 | 2012-07-03T08:07:40 | 1,215,413 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,233 | r | chemenhance.R | source("K_calcs_Johnson_OS.R")
# Chemical enhancement calculations based on Hoover and Berkshire (1969) equation
#############################################
#Calculating chemical enhancement to kw
###############################################
# get mass boundarly layer dpeth from windspeed for given compound
... |
06e0e62c2f239581a160a5923d7283818a8fbd62 | ca25692e5f1e3c1f63c59e37fd92ffcdc6c78412 | /code/12_extract_samples_calc_residuals.R | b4995e042ee5a627e1d40e64877a7522aa327dac | [] | no_license | mkiang/decomposing_inequality | 3a06f8d86c1eddc161e0c83bbfaa092cde7285f8 | b3431e499572aeb2b11bfd2f7a2ea82d84ecfbb1 | refs/heads/master | 2020-09-06T12:19:47.116124 | 2019-11-09T06:40:55 | 2019-11-09T06:40:55 | 220,422,411 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,405 | r | 12_extract_samples_calc_residuals.R | ## Imports ----
library(rstan)
library(tidyverse)
library(matrixStats)
source('./code/helpers/99_helper_functions.R')
## Define the level of significance ----
sig_limit <- .8
## Mapping data ----
fips_idx_map <- readRDS('./data_working/fips_to_dummy_mappings.RDS')
## Get model fits ----
## Note: I named model 1 mode... |
a0102f39023ec233699522fa7ec639a9a60d7f61 | 6704f3fb2a8fe3b4ccd951c902cf0e0d84bb59ca | /nosocomialtransmission_runfile.R | 11536b86b662f0b8405baf695d0ad7edb3e468f5 | [] | no_license | tm-pham/covid-19_nosocomialtransmission | f5d04f987530d556c33a37eed7b98b017271eb7d | 67878b9feaf487404760dffac817025e7f4d05a8 | refs/heads/master | 2022-12-05T07:42:01.994047 | 2020-08-24T06:56:48 | 2020-08-24T06:56:48 | 265,420,009 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,307 | r | nosocomialtransmission_runfile.R | # =============================================================================#
# NOSOCOMIAL TRANSMISSION
# Run file for STAN code
# =============================================================================#
library(rstan)
setwd("/Users/tm-pham/PhD/covid-19/nosocomialtransmission/stochasticepidemicmodel/stan")
sim... |
a6dcea3a1d50e2499085176d1fb8191a461c2d6a | 104c538bdf45af6b466b2dd3a7f64f4541d1d711 | /man/readDB.Rd | be2c4f22cc3e0238200ab22bb011004f2d149e9a | [] | no_license | betonr/rPostgis | 6b819d444a8e78ac1d58d7cda3523bd2c6d44ff4 | 5f4ce28ba35da810d9eaa24a0030360b409bed4e | refs/heads/master | 2021-01-20T02:12:51.342364 | 2017-08-25T11:24:08 | 2017-08-25T11:24:08 | 89,390,184 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 546 | rd | readDB.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ReadDB.R
\name{readDB}
\alias{readDB}
\title{readDB}
\usage{
readDB(objectInfo, date, type, uf)
}
\arguments{
\item{objectInfo}{(InfoDB) - Object with informations for connections}
\item{date}{(character) - amount of previous days (Y-m-d)}
... |
3b6847b579f2dc6c6ae36b626c9a9d32e9dec100 | 4e35775e2a3b6903b68ca5ae2ce0ecbd25b1b5a2 | /tests/testthat/test_draw_posterior.R | 4fa149669575a50aff94ac4b3dbcf05a7bc5bc9d | [
"MIT"
] | permissive | FrankLef/eflRethinking | 93ab747e7ebe93ec4ca3fe5e5a80e6952a45d04e | d9b2a868923134b3e549c96982f1b00092b0c3b2 | refs/heads/main | 2023-08-07T12:19:05.414807 | 2021-10-08T18:56:57 | 2021-10-08T18:56:57 | 410,892,718 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 848 | r | test_draw_posterior.R | # declarations ------------------------------------------------------------
library(posterior, quietly = TRUE)
# the inla objects used
m04m07ctr <- readRDS(test_path("testdata", "fits", "m04m07ctr.rds"))
# tests -------------------------------------------------------------------
test_that("verify the inla model ob... |
94f8875c42558712853e1832bcb2c930df185b7a | d859174ad3cb31ab87088437cd1f0411a9d7449b | /scripts/setup_switchr_environment.R | bcb4f47f2bfe140a978821d0617d7b8c8988f8d9 | [] | no_license | bhagwataditya/autonomics0 | 97c73d0a809aea5b4c9ef2bf3f886614eceb7a3c | c7ca7b69161e5181409c6b1ebcbeede4afde9974 | refs/heads/master | 2023-02-24T21:33:02.717621 | 2021-01-29T16:30:54 | 2021-01-29T16:30:54 | 133,491,102 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,816 | r | setup_switchr_environment.R | # Setup 'switchr' infrastructure ------------------------------------------
switchr::switchTo("autonomics")
# Install/update gitted infrastructure ------------------------------------
# Deal with prerequisites
packages_prerequisite <- c(
'magrittr',
'stringi')
packages_to_install <- setdiff(
packages_prerequ... |
a9885b0697fa9ec3d7e2d28990ffc4a91f6c3e00 | 1708c822fe65b55f5b5680536ab9cd2fda511a27 | /11-IST719-InformationVisualization/Assignments/ThulasiRamRuppaKrishnan_LabWeek8.R | fbe7b2d40fd3f50bcc73fbcfe4b52722479e859b | [] | no_license | truppakr/AppliedDataScience | bec73a851d2c46f00468c88f0e99db46e55aadf5 | f70faf5c585e064cb54e03f236b731238cf2dfca | refs/heads/master | 2022-09-15T18:15:28.788511 | 2020-05-31T22:38:46 | 2020-05-31T22:38:46 | 267,444,552 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,046 | r | ThulasiRamRuppaKrishnan_LabWeek8.R | ###########################################################################
#
# Author : Ram Krishnan
# Purpose: Week 8
# "Class Social Network Data (structure and Cleaning)"
# uses LINKS-421-719Networks.csv
# Nodes-421-719Network.csv
#########################################################################... |
13f4cf4312f5c57a41d8501dee06ba47b660fc30 | f3ca0a4a2391f3e226b14b54f367a9797fe2d275 | /man/a_in_mem_asset.Rd | 3e41c6a2320a92feab94cf42d57f6e2d8a3ccc1d | [
"MIT"
] | permissive | Rukshani/r2vr | a8b9903f5876f9d679824b27e3376a514695a26c | 8d5e9630eb7538121f01951045e174ec235b043c | refs/heads/master | 2023-07-10T12:43:30.438378 | 2021-03-28T07:22:43 | 2021-03-28T07:22:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,544 | rd | a_in_mem_asset.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/in_mem_asset.R
\name{a_in_mem_asset}
\alias{a_in_mem_asset}
\title{a_in_mem_asset()}
\usage{
a_in_mem_asset(.data, src, .parts = NULL, ...)
}
\arguments{
\item{.data}{a string containing file content or a list of such strings.}
\item{src}{a ... |
b55943068522360e5e8e410ae14e5c8c55150830 | f4296a6ce342a35f15b51b0555ea000e10414391 | /05 Analysis Function Calculate Predicted Building.R | 01dee41d859b1b9bb73e2d875469652a31459738 | [] | no_license | ReneVanDijkBDH/Ubiqum_wifi | 23ab924ccd9c8b88dc7dec57144c76de52b6369c | 6c6419bc56d809c5aadece96f67841a952d8b12f | refs/heads/master | 2022-02-22T03:46:24.335269 | 2019-10-23T14:59:08 | 2019-10-23T14:59:08 | 212,550,364 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,702 | r | 05 Analysis Function Calculate Predicted Building.R | #########################################################################
## Author: René van Dijk
## Creation: 10-10-2019
## Purpose: calculates the expected building based on predicted Longitude & latitude:
## 1) Add predicted Longitude and Latitude to testing set
## 2) Calculate errors co... |
0b4a5ed801a2bff3c1ca3bfc87ab60fa1925283b | 604f064ac46806c8aaba71afc42fc6f8f6d2a1e0 | /tests/testthat/test-getLocations.R | 873d4b073d1897b2f61641314578e6ed792ea185 | [
"MIT"
] | permissive | johndharrison/webpagetestr | d2278dcf271dbe7f800e95569829fff045689d43 | 48ba992bfa4ebf3edf6b8767160c1a2e92f65595 | refs/heads/master | 2021-01-13T10:26:49.749120 | 2016-11-08T16:34:32 | 2016-11-08T16:34:32 | 72,283,586 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 938 | r | test-getLocations.R | context("getLocations")
test_that("canGetLocations", {
WPT <- server()
locs <- getLocations(WPT)
expect_s3_class(locs, "locations")
})
test_that("errorOnInvalidRequestIdGetLocations", {
WPT <- server()
expect_error(getLocations(WPT, 1), "requestId is not a string or null")
})
test_that("canGetErrorFromGe... |
f0e66f008ae6345948398b0a8af2e721aa41fce5 | 705255987191f8df33b8c2a007374f8492634d03 | /examples/Rules-class-NextBestMinDist.R | cf61db54aa62fd25bc103dbfb6b8681a393e80a0 | [] | no_license | Roche/crmPack | be9fcd9d223194f8f0e211616c8b986c79245062 | 3d897fcbfa5c3bb8381da4e94eb5e4fbd7f573a4 | refs/heads/main | 2023-09-05T09:59:03.781661 | 2023-08-30T09:47:20 | 2023-08-30T09:47:20 | 140,841,087 | 24 | 9 | null | 2023-09-14T16:04:51 | 2018-07-13T11:51:52 | HTML | UTF-8 | R | false | false | 176 | r | Rules-class-NextBestMinDist.R | # In the example below, the MTD is defined as the dose with the toxicity rate
# with minimal distance to the target of 30%.
next_best_min_dist <- NextBestMinDist(target = 0.3)
|
2305596394bd887bfce2b70499d64d51bc1ebf31 | 48f83c8d49a4abe93213daf2068f27180633a9d3 | /tests/testthat/test-predict_asymmetry.R | c631dc91eaea8949dfc5ab863566b4632e467d7b | [] | no_license | LCBC-UiO/BayesianLaterality | 71a051964d1f93cdd4f821fc3188b76e400c3cf7 | 4ed929c363995a7b68240db199d823e88fdf852b | refs/heads/master | 2023-07-03T09:34:41.426732 | 2021-08-08T20:06:05 | 2021-08-08T20:06:05 | 171,873,953 | 0 | 0 | null | 2021-08-08T20:06:05 | 2019-02-21T13:10:52 | R | UTF-8 | R | false | false | 210 | r | test-predict_asymmetry.R |
data <- dplyr::tibble(
listening = c(-20),
handedness = "left",
stringsAsFactors = FALSE
)
df <- predict_dominance(data)
expect_equal(
df$probability,
c(0.476309298919027, 0.523690701080972, 0)
)
|
184300e0084455882208d221a975281e4c2a4ff9 | b1d7cd1c5f99d510c03ef8f792f5e59a86e82292 | /instalaPaquetes.R | 790b1fae15236663a07e9ad9904ae4bfe1209363 | [] | no_license | diegoosorio/iData | 9322f7b88bec3e85b96a2161d9ce8f5cdd9810ee | ee3f56a5f1fc82d4142cd0cc33f7f5fc0d0ad748 | refs/heads/master | 2020-04-05T14:30:25.641130 | 2018-11-15T01:36:12 | 2018-11-15T01:36:12 | 156,932,534 | 0 | 0 | null | null | null | null | WINDOWS-1250 | R | false | false | 1,663 | r | instalaPaquetes.R | # -----------------------------------------------------------------
# Instalación de paquetes necesarios para el curso
# -----------------------------------------------------------------
# Función para verificar si un paquete está instalado o no
is.installed <- function(paquete) is.element(
paquete, installed.... |
63ecb4378db05f0652e6674c5c01c83033f5755a | 7aa1bc3dedd865bf833294c63e578d72392f7cc8 | /deaPDF.R | ca61087aed404a018d010b5226eec879bb42c89b | [] | no_license | SophiaLC/KSSP_Data_Quality | 8724a1544b285c4aceeb510f829aadc1d5957499 | cd9ec42d5167a49449b457d2f6858e02faeb144c | refs/heads/master | 2020-03-22T09:51:36.959338 | 2018-09-13T19:30:54 | 2018-09-13T19:30:54 | 139,865,192 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 26,128 | r | deaPDF.R | #### prep ####
setwd("~/mhwii/misc")
library(tabulizer)
library(dplyr)
library(tidyr)
library(magrittr)
library(stringr)
#### notes ####
# not including state totals, because that is at a different level of analysis than zip
# the different matrices on different pages get read in differently, so I had to change the co... |
6ab8c0aa1ed965d776f44f290eafe9453fb3d30c | c5fe243e1c7f01c6217cc15f7f64a955f6561624 | /R/ph2.r | 719380abee69bb0780f89883fd99fdfb7b4913a9 | [] | no_license | cran/probhat | 79c1ff28e9867565d80f2744e3a84f49aeba5dc6 | ae21b43b0de331247713e4294acad3aa99c4fdb5 | refs/heads/master | 2021-06-09T16:27:06.236867 | 2021-05-12T08:40:02 | 2021-05-12T08:40:02 | 174,553,921 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 932 | r | ph2.r | #probhat: Multivariate Generalized Kernel Smoothing and Related Statistical Methods
#Copyright (C), Abby Spurdle, 2019 to 2021
#This program is distributed without any warranty.
#This program is free software.
#You can modify it and/or redistribute it, under the terms of:
#The GNU General Public License, versi... |
d930a99c4ff3a1ff54328b8a7e1106c2168f94ac | 9f438e0f499907ee53f4f77d13639af1729a0687 | /plot3.R | e4cceb3f9e5484bbaa4cd1926980f4bf7064c69c | [] | no_license | ankit76ja/ExData_Plotting1 | c2b948fa8959ca3e994192a94f0b5dc4b9e0f647 | b644b4f0be7c68086931d10e2a9eccbfaa75199a | refs/heads/master | 2021-08-10T17:44:30.153899 | 2017-11-12T21:01:48 | 2017-11-12T21:01:48 | 110,467,205 | 0 | 0 | null | 2017-11-12T20:37:19 | 2017-11-12T20:37:19 | null | UTF-8 | R | false | false | 477 | r | plot3.R | source("read_data.r")
power_data<-read_data()
png("plot3.png",height = 480,width = 480,units = "px")
plot(power_data$Time, power_data$Sub_metering_1, type = "l", xlab = "", ylab = "Energy sub metering")
lines(power_data$Time,power_data$Sub_metering_2,col="red")
lines(power_data$Time,power_data$Sub_metering_3,col="blue... |
9d6d6cb80a9889b54dd0ff16a91c93e0bc2a9dbe | 9271179ea2cac166e527234f9013aa3ef195913b | /data-raw/get_fbi_datsa.R | e447db7b9183f2df907985ee7ded887cda7fa4ac | [] | no_license | mikkelkrogsholm/murderdata | 0eb25bd680dedaac1002e04ba23ef4d5fb5ba29c | 86b3842fd647b1e395bb6784b2f87f63e95ebf36 | refs/heads/master | 2021-05-06T07:53:54.688980 | 2017-12-18T16:05:31 | 2017-12-18T16:05:31 | 113,975,913 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 382 | r | get_fbi_datsa.R |
url <- "https://www.dropbox.com/s/xzulxmnzm3mf6bm/SHR.zip?dl=1"
filename <- "data-raw/fbi/fbi_sup.zip"
utils::download.file(url, filename)
unzip(filename, exdir = "data-raw/fbi/fbi_sup")
url <- "https://www.dropbox.com/s/mdonovdamlppf80/ReturnA.zip?dl=1"
filename <- "data-raw/fbi/fbi_all.zip"
utils::download.file(ur... |
27e4c09f32aaa7413fa98a34ff34b771a05c3e51 | 09f489b818406f56e28f544d566121e5a2c1be2c | /init.R | 19f494731ec9ce32807f14fcd8e675669fc85fce | [] | no_license | Martien1973/rAHNextract | e477e998509912c217061902548a3c0e9aadf332 | 696d66ec58d5e15eb076623ccd2bac7bd5d46285 | refs/heads/master | 2021-01-04T10:21:28.198351 | 2020-02-14T08:22:17 | 2020-02-14T08:22:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 121 | r | init.R | my_init <- function(){
library(raster)
library(rgdal)
library(sp)
library(sf)
library(data.table)
}
my_init()
|
672f524843b837654ff277f6779793d3650c0607 | c2497a475ceb8fead3eea2432876d0e6ca6c1e9f | /AgeMixing/plotGroupMixingPairs.R | af7dc1b68f96299d9db5fb546705635f0f4c7750 | [] | no_license | nicfel/FluBaselPhylo | bb64f70f70ef6ada41f5b55aec5fbbbb50302b9d | 10bf47725bab230324037f1f814f1d98ea1cf699 | refs/heads/master | 2022-02-12T00:27:06.621190 | 2019-08-14T08:36:14 | 2019-08-14T08:36:14 | 192,312,417 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,007 | r | plotGroupMixingPairs.R | ######################################################
######################################################
# Here the inferred mean coalescent and migration
# rate ratios are plotted
######################################################
######################################################
library(ggplot2)
# clea... |
bf2f363f8b10aa2b708e5dec9041c1b275ae9ad6 | 0768cca65ac0cbda2096577e7156090ebf73dd08 | /KNN.R | ae3ca3749bc7f10355113aa140e652855f18d9f9 | [] | no_license | bilsko/ML | 0281616da5d8dc1a5a76ff454eb4b8123a6d545f | 5cab16e2a25a14dfea8c077d526acd426912a60c | refs/heads/master | 2020-04-14T22:46:09.088344 | 2019-01-05T03:13:25 | 2019-01-05T03:13:25 | 164,177,112 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 798 | r | KNN.R | library(ISLR)
purchase<- Caravan[,86]
standardized.Caravan <- scale(Caravan[,-86])
test.index<- 1:1000
test.data<- standardized.Caravan[test.index,]
test.purchase<- purchase[test.index]
train.data <- standardized.Caravan[-test.index,]
train.purchase<-purchase[-test.index]
#KNN model
library(class)
set.s... |
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