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values | filename stringlengths 1 141 | content stringlengths 7 9.18M |
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90dfb52d559076b6d148e4da721161d8c2188f1f | 4cb5426e8432d4af8f6997c420520ffb29cefd3e | /P6.R | 047efecbcdd36924cd64e63fa1eee9bf0829aea5 | [
"CC0-1.0"
] | permissive | boyland-pf/MorpheusData | 8e00e43573fc6a05ef37f4bfe82eee03bef8bc6f | 10dfe4cd91ace1b26e93235bf9644b931233c497 | refs/heads/master | 2021-10-23T03:47:35.315995 | 2019-03-14T21:30:03 | 2019-03-14T21:30:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,274 | r | P6.R | # making table data sets
library(dplyr)
library(tidyr)
library(MorpheusData)
#############benchmark 1
dat <- read.table(text=
"GeneID D.1 T.1 D.8 T.8
A2M 8876.5 510.5 4318.3 8957.7 4092.4
ABL1 2120.8 480.3 1694.6 2471 1784.1
ACP1 1266.6 213.8 1337.9 831.5 814.1
", header=T)
write.csv(dat, "data-r... |
28deabd1d0cb7b2fbf60669961eda591d9f8080e | 04f6c2eb3c2dca28f79094b05297aa1a182d4695 | /01-data_cleaning-post-strat1.R | a2d473bc02c4d79ccd2f751c87ae2f0f30c4ede6 | [
"MIT"
] | permissive | jingwennnn/Prediction-of-2020-United-States-Presidential-Election-Result | a7deb28efc7a5e0e486bf28df62394281f8250d8 | e67164a478b9332b5cb232cc46e4919520bffe3f | refs/heads/main | 2023-01-05T02:41:46.372103 | 2020-11-03T04:08:02 | 2020-11-03T04:08:02 | 309,485,797 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,186 | r | 01-data_cleaning-post-strat1.R | #### Preamble ####
# Purpose: Prepare and clean the survey data downloaded from https://usa.ipums.org/usa/index.shtml
# Author: Yuchen Cong, Jingwen Deng, Ruoxi Guan, Yuwei Sun
# Date: 2 November 2020
# Contact: jingwen.deng@mail.utoronto.ca
# License: MIT
#### Workspace setup ####
library(haven)
library(tidyverse)
# ... |
feac75c5a62db13de8a9580992dd4a1fcb5a27e3 | 0b8c23f9e629e3063eeaccf12d74f0c1423ebb1a | /man/GradientDescent.Rd | 98ceff4afd6b4a7663fcfe83b1235914f4bd5d3c | [] | no_license | sh0829kk/R-package-imbedding-Newton-Nestrov-Gradient | 53830dde2f036ba512f6bb940dc5a5062f53e2a5 | 15b690df77832c7d1d9ccd4aa8d19e3cd8f2f73a | refs/heads/master | 2023-08-10T16:48:05.995506 | 2021-01-25T18:14:37 | 2021-01-25T18:14:37 | 331,316,612 | 3 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,156 | rd | GradientDescent.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GradientDescent.R
\name{GradientDescent}
\alias{GradientDescent}
\title{GradientDescent}
\usage{
GradientDescent(
beta,
X,
y,
maxLength = 10000,
learningRate = 0.001,
sigma = 0.001,
regulation = 0,
lamda = 0.5
)
}
\arguments{
... |
3d37c7ef5b5c1b5c0833f4869ee721b529545218 | fc54f6fcc80d7f63b3cde85346408814e19a1f3a | /R/solver.mst.R | 315148d95416b46ea4e5a7661121678e3df33777 | [] | no_license | MartinWolke/salesperson | 888422ffb435171b96cda19da003e41861dfd46b | 7ec9e0075dc3cb74e5ed3fb5344c00c8fa1abe41 | refs/heads/master | 2021-01-17T05:43:28.267481 | 2015-11-26T15:30:26 | 2015-11-26T15:30:26 | 38,509,913 | 0 | 0 | null | 2015-07-03T20:43:51 | 2015-07-03T20:43:50 | R | UTF-8 | R | false | false | 468 | r | solver.mst.R | #' @export
makeTSPSolver.mst = function() {
makeTSPSolverInternal(
cl = "mst",
short.name = "MST",
name = "MST (minimum spanning tree) heuristic",
properties = c("euclidean", "external", "requires.tsplib", "deterministic"),
par.set = makeParamSet()
)
}
#' @export
# @interface see runTSPSolver
r... |
6b70c63dd8836ad69bfd5b9a7f7200b004f2444d | a2513ff9dc0be7fb01034bd50207199fd5d25d8c | /inputs/caribou_ranges.R | 429cecd0ee736bd3717c367b25021e6155153ec6 | [] | no_license | fRI-Research/LandWeb | fd4003a50e77670a35fbdac874f1e7601463e11c | 4640c2dcd92324c9d5dde4ea414eca26427aa9c4 | refs/heads/master | 2020-09-11T05:37:34.543009 | 2019-11-15T15:32:49 | 2019-11-15T15:32:49 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,310 | r | caribou_ranges.R | ### LandWeb was previosuly only using Boreal Caribou Ranges for results
### This adds Mountain Caribou Ranges for AB and BC, as requested by several partners
library(magrittr)
library(map)
library(stringr)
ml <- mapAdd(layerName = "Boreal Caribou Ranges",
useSAcrs = TRUE, poly = TRUE, overwrite = TRUE,
... |
1cfbf3dcc9d46a64c73aad2d6a2c8aab221cc782 | d161a144cca6f876557c5f716d43e4fc40fe0eb9 | /R/MCMC_functions.R | f82608884f77e5b48cea973fdd6e26309bc7306b | [] | no_license | SimoneTiberi/BANDITS | d57c02cf85ec56c87900265ed3264d106480640d | 3c42091edf5533197695b2d8bf2a1e22d7cc754d | refs/heads/master | 2022-06-19T01:23:45.396288 | 2022-05-20T14:56:55 | 2022-05-20T14:56:55 | 178,011,248 | 19 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,678 | r | MCMC_functions.R | ##############################################################################################################################
# General MCMC functions:
##############################################################################################################################
# initialize pi new (matrix) object
crea... |
9efcee796ba34d00f7eab27107e89cff4c77dc8b | 7898b2dfe59e4dda0456d68f015ae22448159520 | /plot3.R | 630b62afe0eb4ba6ef42069986e9e09362866515 | [] | no_license | creato-zoom/ExData_Plotting1 | 359c103ac1921249f4233c84933daa4521b0b04a | 69ddbc5119aee35eeb20e934a83538bd3dd6de77 | refs/heads/master | 2021-01-16T18:14:10.509777 | 2015-10-10T20:48:14 | 2015-10-10T20:48:14 | 43,940,631 | 0 | 0 | null | 2015-10-09T07:45:57 | 2015-10-09T07:45:57 | null | UTF-8 | R | false | false | 1,360 | r | plot3.R | plot3 <- function()
{
if(!file.exists("household_power_consumption.txt")){
message("File household_power_consumption.txt does not exist in working directory.")
message("Please add household_power_consumption.txt to working directory and try again")
return()
}
#Data Setup
powerData <- read.csv2(file... |
8cb8a8f7f292158350789f003df184aa30316920 | 828ab27d1bf27f9ba5f18542af72a8e3de1ef567 | /plot3.R | d9681be1cacd38cc1cb97679dfb296cc38e77a19 | [] | no_license | ntquyen/ExData_Plotting1 | 930b44b3d532e275826c240f9ac47b083aba6e41 | 464f0e07783e261744eacb4bcda4eb2187d46e45 | refs/heads/master | 2020-12-25T04:01:17.772883 | 2015-06-11T01:00:33 | 2015-06-11T01:00:33 | 31,745,264 | 0 | 0 | null | 2015-03-06T00:57:01 | 2015-03-06T00:57:01 | null | UTF-8 | R | false | false | 91 | r | plot3.R | # source("download_data.R")
png("plot3.png")
source("plotting.R")
plot3(subData)
dev.off() |
dbc2719f8e99db04cb6ff2b10602636beaec1ac4 | 0a906cf8b1b7da2aea87de958e3662870df49727 | /borrowr/inst/testfiles/matchesToCor/libFuzzer_matchesToCor/matchesToCor_valgrind_files/1609957931-test.R | cdd9cd36e842387de9b4574fe29f2d8778eef664 | [] | no_license | akhikolla/updated-only-Issues | a85c887f0e1aae8a8dc358717d55b21678d04660 | 7d74489dfc7ddfec3955ae7891f15e920cad2e0c | refs/heads/master | 2023-04-13T08:22:15.699449 | 2021-04-21T16:25:35 | 2021-04-21T16:25:35 | 360,232,775 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,315 | r | 1609957931-test.R | testlist <- list(x = structure(c(2.12199581912701e-314, 4.94065645841247e-324, 4.94065645841247e-324, 4.94065645841247e-324, 4.94065645841247e-324, 4.94065645841247e-324, 4.62895107548006e-299, 2.46679008847656e-308, 4.52353163074667e-310, 6.21470200082845e+228, 2.02822087723472e-110, 7.2846496044813e+199, 2.347291... |
4f2dcd4e332dedc0dca8f06a8faa46d01ec87340 | 7afe5683bcecc755ab598a9d21400dd35e33bd50 | /resources/make.assocplot.R | 857f84232f58344b0142a0c0b89737f4f2100a31 | [] | no_license | AnalysisCommons/assocplot | 9d03a3010923445b221b1ad624e51822a67718a8 | 376e88a6ff21492b3b4c19fd0d973b99ad61f1f3 | refs/heads/master | 2020-06-27T10:13:09.928600 | 2017-06-15T20:35:18 | 2017-06-15T20:35:18 | 94,249,200 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,187 | r | make.assocplot.R | # Script generalized from 'make.plot_P.value_forManning.R' script written by Jaeyoung Hong
LOCALTEST <- FALSE
if (LOCALTEST) {
## Load libraries and source files
library(data.table)
setwd("/home/mbrown/DNAnexus/assocplot/resources/")
source("modified.assocplot_P.value.R")
## Setup paths
da... |
385bf7d3c6aed41ceba01e7d1c27159b859a3603 | 0f9f7c99088cf725acd5cf435840044ab2b12e03 | /src/engine_all_dataset.R | 9bb8070613677ae2ccce024b93d684f1bd52832e | [
"MIT"
] | permissive | hiplot/gmiec-shiny | 64d20b21d8be64517cd1b701968ac9002cea4cf9 | 9c88d89c7b8223ef4b56e7597659c06999e77e2a | refs/heads/master | 2023-03-09T18:02:03.778476 | 2021-02-28T14:24:59 | 2021-02-28T14:24:59 | 343,124,446 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,398 | r | engine_all_dataset.R |
engine_all_dataset<-function(input_for_klar2,dfPatientForAnalysis_GAC,clusters){
print("Step 6: Run klaR")
print(dim(input_for_klar2[,-1]))
print(dim(unique(input_for_klar2[,-1])))
resKLAR = kmodes(input_for_klar2[,-1], clusters)
ifkl<-cbind(clusters=resKLAR$cluster,input_for_klar2)
... |
3b9ce5fd17140646a7fd8b98c4d90dfe1d1780e8 | 061a7c01302d3d865869e45448b9c6d10bb02b87 | /man/assign_label_cex.Rd | f69d8c8bc608eb4e245e83406932c5de3a5df3ac | [] | no_license | naikai/sake | 4da891e257ff551adbfc7e01c7dcbc8627ed5e8f | 68b8c688c2eaf985de96d020deaaa7af319079f4 | refs/heads/master | 2023-02-19T22:41:38.865443 | 2023-02-08T18:47:21 | 2023-02-08T18:47:21 | 60,200,366 | 29 | 14 | null | 2021-03-18T23:37:38 | 2016-06-01T18:14:57 | R | UTF-8 | R | false | true | 407 | rd | assign_label_cex.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plot_utils.R
\name{assign_label_cex}
\alias{assign_label_cex}
\title{Adjust label cex based on its number}
\usage{
assign_label_cex(n.samples)
}
\arguments{
\item{love}{Do you love cats? Defaults to TRUE.}
}
\description{
This function allows... |
320088858bb1510d053b0a1d071c711c96c6629f | f5d2dd91994929a25bd36dc78b246bee85202adf | /R/RcppExports.R | 732344bd320d15798e3cdeab8526c1c0a4372fb5 | [] | no_license | environmentalinformatics-marburg/Reot | 1350feb80c342aa6c94172d68c58d5e55ae8ad1c | 1a3e09b08e960b80b236d571d3c637b8e29272fd | refs/heads/master | 2020-04-24T22:32:13.185940 | 2014-08-25T09:29:07 | 2014-08-25T09:29:07 | 11,943,730 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 783 | r | RcppExports.R | # This file was generated by Rcpp::compileAttributes
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
corC <- function(x, y) {
.Call('Reot_corC', PACKAGE = 'Reot', x, y)
}
lmC <- function(x, y) {
.Call('Reot_lmC', PACKAGE = 'Reot', x, y)
}
predRsquaredSum <- function(pred_vals, resp_vals, standardised... |
61b5b3b10fd0b672d8bd9e4efdefb48a206fe522 | 8707c19f9ba5faafa304dde5b00fab2ab345dd2e | /plot2.R | fb0b019f3bb0632a4107d045e3400f6ad9aeae4a | [] | no_license | LiuyinC/ExData_Plotting1 | e0a314896385b60e7f40eef319f977ca721ecab9 | 39a787f831e797e1636a067a8b0b0c14667ff3d4 | refs/heads/master | 2021-01-18T02:10:46.093926 | 2014-06-02T19:45:22 | 2014-06-02T19:45:22 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 467 | r | plot2.R | powerData <- read.table("./data/household_power_consumption.txt", header = TRUE, sep = ";", na.strings = "?")
plotdata <- subset(powerData, Date == "2/2/2007" | Date == "1/2/2007")
TimeDataCha <- paste(plotdata[["Date"]], plotdata[["Time"]], sep=" ")
TimeData <- strptime(TimeDataCha, format = "%d/%m/%Y %H:%M:%S")
png(f... |
63b36c615a05a9bcbc9c2009da65c7b37a703c5b | 5331c39119c2e02eb2d91016f2201be33609c9b4 | /extras/plot-aucs.R | aff7d3959f2d51bdf8aa0c07be0f7f1bd93c73f2 | [
"MIT"
] | permissive | project-aero/measles-ews | 034957e3247b19419181aacf54cbb0cf520aa763 | a67845c1b056299cd2896263f584b55aba6bf24b | refs/heads/master | 2023-04-14T01:36:24.801773 | 2021-11-23T13:07:11 | 2021-11-23T13:07:11 | 136,212,776 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,772 | r | plot-aucs.R | # plot-aucs.R
# Script to plot the AUC results from emergence and endemic simulation
# tests of EWS.
#
# Author:
# Andrew Tredennick (atredenn@gmail.com)
# Load libraries ----------------------------------------------------------
library(tidyverse)
library(viridis)
# Load results ------------------------------... |
575c82a84260f1321962a6ae4a6603824d402767 | 6b28896f46eabbddaf8f14cd08554cfeab591263 | /R/fem.main.R | 591b40060c6e0c12e6649ee86a5f5c032e9c60a5 | [] | no_license | cran/FisherEM | 3b565591d45e456884b8296af38047421f8ade93 | 4ff2e8e609a42942801b74290158e79e3c18c751 | refs/heads/master | 2021-06-02T08:28:58.187744 | 2020-09-28T13:10:02 | 2020-09-28T13:10:02 | 17,679,260 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,748 | r | fem.main.R | fem.main <- function(Y,K,init,nstart,maxit,eps,Tinit,model,kernel='',method){
# Initialization
colnames = colnames(Y)
Y = as.matrix(Y)
n = nrow(Y)
p = ncol(Y)
d = min((K-1),(p-1))
# Compute S
m = colMeans(Y)
XX = as.matrix(Y - t(m*t(matrix(1,n,p))))
S = t(XX) %*% XX /n
# New objects
Lobs =... |
d4ff529833bf6c764de41396a15e10b5fbf1c509 | fe612f81a3118bf3ebef644bae3281bd1c156442 | /man/h2o.removeAll.Rd | 3bf89913be2dd243bc31559531a13e2adf6e3b92 | [] | no_license | cran/h2o | da1ba0dff5708b7490b4e97552614815f8d0d95e | c54f9b40693ae75577357075bb88f6f1f45c59be | refs/heads/master | 2023-08-18T18:28:26.236789 | 2023-08-09T05:00:02 | 2023-08-09T06:32:17 | 20,941,952 | 3 | 3 | null | null | null | null | UTF-8 | R | false | true | 1,141 | rd | h2o.removeAll.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/kvstore.R
\name{h2o.removeAll}
\alias{h2o.removeAll}
\title{Remove All Objects on the H2O Cluster}
\usage{
h2o.removeAll(timeout_secs = 0, retained_elements = c())
}
\arguments{
\item{timeout_secs}{Timeout in seconds. Default is no timeout.}
... |
bfc39c11504a111f9a4d0da5dc7d31258f02fbfe | b12382e16a602599d0725b5446bb6e5680da3e66 | /R/Newton-Raphson/NLS_NR/Functions/expitm1.R | 057531f490db4f1a0104c8aff84bf0489afa50a7 | [] | no_license | hhnguyen2/Summer-2016 | edd9de12fff00d5af3c058c30a7d07e71ba4289b | bccd6810ce3c49f8a0925b1954cff7643eb9648c | refs/heads/master | 2021-01-20T17:20:31.080061 | 2016-08-04T20:11:56 | 2016-08-04T20:11:56 | 60,541,681 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 131 | r | expitm1.R | # expitm1: evaluate (exp(x)-1)/(exp(x)+1) = 1 - 2/(exp(x)+1)
# Read: "expit minus one"
expitm1 <- function(x){
1 - 2/{exp(x)+1}
} |
f7f256d189751fdef1678e14866a35962351c0d9 | 596338eae0a9ad8879e01ace95ab52027c8795cc | /toRun.R | f4b1463c719031d9755b0c2a3ddb20b1c4644100 | [] | no_license | databio/Methylation_Age_Prediction | ddb92f93d90348e505f98e45d380725e176318a9 | b369c15e0bb72e2ff02105130a7466303cf4e0bc | refs/heads/master | 2020-05-02T20:57:52.790718 | 2019-04-25T13:53:04 | 2019-04-25T13:53:04 | 178,206,628 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 876 | r | toRun.R | ##Install dependencies, commented incase dependencies are already present.
#source("https://bioconductor.org/biocLite.R")
# install.packages("knitr", repos='http://cran.us.r-project.org')
# install.packages("rmarkdown", repos='http://cran.us.r-project.org')
#biocLite("preprocessCore")
#install.packages("installr")
#... |
e255a6f164a38409871b12875de6be11bef0d495 | c746b5f40c118fb4f41a2d7cb88024738476d40f | /Data_Generation/Results/combine_adaelnet75_500.R | 56773119bc84dc3b6886c63fa540a692bab49c4b | [] | no_license | multach87/Dissertation | 5548375dac9059d5d582a3775adf83b5bc6c0be7 | d20b4c6d3087fd878a1af9bc6e8543d2b94925df | refs/heads/master | 2023-06-25T20:09:25.902225 | 2021-07-23T18:51:07 | 2021-07-23T18:51:07 | 281,465,959 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,423 | r | combine_adaelnet75_500.R | #load data
half.data <- readRDS("/Users/Matt Multach/Desktop/Dissertation/Dissertation_Git/Data_Generation/Data_Storage/500_data_10052020.RData")
adaelnet75.final <- readRDS("/Users/Matt Multach/Dropbox/USC_Grad2/Courses/Dissertation/Dissertation_Git/Data_Storage/MainResults_Storage/adaelnet75_resultmain_500.RData")
#... |
cc6afafb1012b2b92df37cdb76f36d4e79369649 | 0ae69401a429092c5a35afe32878e49791e2d782 | /trinker-lexicon-4c5e22b/man/profanity_banned.Rd | 6ed7cdf0467e0d412a99db83d7dd2b1a18a50585 | [] | no_license | pratyushaj/abusive-language-online | 8e9156d6296726f726f51bead5b429af7257176c | 4fc4afb1d524c8125e34f12b4abb09f81dacd50d | refs/heads/master | 2020-05-09T20:37:29.914920 | 2019-06-10T19:06:30 | 2019-06-10T19:06:30 | 181,413,619 | 3 | 0 | null | 2019-06-05T17:13:22 | 2019-04-15T04:45:06 | Jupyter Notebook | UTF-8 | R | false | true | 838 | rd | profanity_banned.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/profanity_banned.R
\docType{data}
\name{profanity_banned}
\alias{profanity_banned}
\title{bannedwordlist.com's List of Profane Words}
\format{A character vector with 77 elements}
\usage{
data(profanity_banned)
}
\description{
A dataset contai... |
cb44cedaf0e205281b99c3c9b416494c6d99b5a6 | 7815bb69f7e5d07aec5d853be6d705bee6c444a6 | /Assignment3/best.R | 040724ef3a9d79f8cdbd8b130e439cd3b9c8bf2a | [] | no_license | fiamen/RProgramming | 082c7cde4f9c6367ac2df6ef0a3ebf7bdbf46883 | 0ecc60edc099325a73812b1ca57558f96980f3c4 | refs/heads/master | 2021-01-18T18:25:51.464176 | 2014-11-17T02:10:01 | 2014-11-17T02:10:01 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,281 | r | best.R |
best <- function(state, outcome) {
## Read outcome data with measures of outcomes of care
Outcome <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
## Check that state is valid
st<-unique(Outcome$State)
styes<-which(st==state)
i... |
f0e615083df4fe144dc800c1e1251518699b1d11 | 2eae755d5619934c814a2aec3e8ff01a69ee727f | /07/ReactionTimeGibbs.R | 4b97b31f04662162ed73e151ff76235b7b6de509 | [] | no_license | tjwhalenUVA/664-Homework | 8535877e0f2400ae3544888d52a5f052f2f8144d | 2cb524132d0906d89a65aec3f5d5562d889d6e5c | refs/heads/master | 2021-05-02T00:34:02.722399 | 2018-06-08T17:30:24 | 2018-06-08T17:30:24 | 120,946,506 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,476 | r | ReactionTimeGibbs.R | # Reaction time example from Unit 5 and 6
# Reaction time data (log reaction times) for first non-schizophrenic subject
reaction.times=c(5.743, 5.606, 5.858, 5.656, 5.591, 5.793, 5.697, 5.875, 5.677, 5.73,
5.69, 5.919, 5.981, 5.996, 5.635, 5.799, 5.537, 5.642, 5.858, 5.793,
5.805, 5... |
8df7a69d6345cda5dcb7446dbaaf15b668295864 | 52e900e1cd7820ee4f9d298c7b1eee2fb975461e | /plot1.R | a802e4a55bec2699dc7893fc2c3d7afa6663223c | [] | no_license | cscarvalho/ExData_Plotting1 | 38a1aab0806d699e2c2237a914af8b7fcc1a5dd8 | 1bd81811e5089001d5c258775ae5612831bc2a88 | refs/heads/master | 2021-01-18T06:44:07.817790 | 2015-12-13T21:32:37 | 2015-12-13T21:32:37 | 47,933,561 | 0 | 0 | null | 2015-12-13T19:41:27 | 2015-12-13T19:41:27 | null | UTF-8 | R | false | false | 355 | r | plot1.R | ##plot1.R
datafile="household_power_consumption.txt"
data=read.table(datafile,sep=";",header=TRUE,stringsAsFactors=FALSE,dec=".")
#head(data)
subdata=data[data$Date %in% c("1/2/2007","2/2/2007"),]
x=as.numeric(subdata$Global_active_power)
png(file="plot1.png")
hist(x,main="Global Active Power",xlab="Global Active Powe... |
6a66a10604576d0d43ae867e6184e4ff67080ad7 | 4e929f4a92a2533e713b87adb06f773748814126 | /R/RProjects/HITHATStats/R/dl20.R | 4bdc1ee222259f873a4720b6522e21ee600aa953 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | jlthomps/EflowStats | f4fe56f17cb675bcc1d618bc838003c2f2e9f81b | 016c9cb65a2f13a041af3eb87debb4f83793238a | refs/heads/master | 2021-01-01T05:33:44.189671 | 2013-12-04T23:30:21 | 2013-12-04T23:30:21 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 895 | r | dl20.R | #' Function to return the DL20 hydrologic indicator statistic for a given data frame
#'
#' This function accepts a data frame that contains a column named "discharge" and
#' calculates the number of zero-flow months for the entire record
#'
#' @param qfiletempf data frame containing a "discharge" column containing d... |
4831f85c47595d545121b7ff5a590908d66a8b71 | a40171fbebb7daff29f1c0ea023e5bf17f025365 | /R/Query.R | f8c65a6e9ff64b364b3c062e84e2fef31fd89d1a | [] | no_license | SimonPBR/reviewR_prep | d4e7d7abb79f03aa1481c8247e65b98f485ccf25 | fc3e007c0832e702cb942bd98fad44f23d49f3a3 | refs/heads/master | 2020-09-29T17:45:00.357010 | 2019-12-11T09:55:25 | 2019-12-11T09:55:25 | 227,086,421 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 455 | r | Query.R | getYear <- function(title) {
title <- enquo(title)
movies %>%
filter(title == !!title) -> temp
return(temp$year)
}
# function(data, metric = title) {
# # Convert vor NSE
# metric <- enquo(metric)
# # Open data
# movies %>%
# # Filter for the title specified in function -> o... |
43a92ea6aea307070abf778d4032edf315d1ea98 | 1f8bdf4a8638978a38c25293848057ea40b3854f | /R/report.r | b20befbd350e2c49921bc2254af3463e8da8c784 | [] | no_license | jcal3/rj | b8bff846c14983c92504fed452a908cd2515bc28 | 3b51a477f139c19f3dd6fd1b8d533e713720719a | refs/heads/master | 2021-01-16T19:32:52.314482 | 2013-06-04T20:59:06 | 2013-06-04T20:59:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,028 | r | report.r | #' Generate a status report.
#'
#' @param articles list of articles to generate report for. Defaults to
#' all active reports in \file{Submissions/}.
#' @export
report <- function(articles = active_articles()) {
rpt <- do.call("rbind", lapply(articles, report_line))
rpt <- rpt[order(rpt$date, rpt$ed), ]
rpt$sta... |
bed8bbc390cf4256d9c59aedab0066840a23cb2b | 5bf5969c93eed2a9484f9aa22f90d7946572be8f | /graficar.R | f0a63009a3f5a952fcc6ad0e84b09422b5bed2fd | [] | no_license | SergioMateosSanz/Rexamples | 891ec1b6ecf4dd3bf2d4080838ee2c3126177243 | 85a2fa59312eb0b79422f42e4c47044757405618 | refs/heads/main | 2023-04-26T01:55:02.257440 | 2021-05-27T18:15:59 | 2021-05-27T18:15:59 | 330,391,609 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,246 | r | graficar.R | # Diferentes formas de graficar en r
# 1. graficar con base graphics (froma tradicional)
year <- c('2010', '2011', '2012', '2013', '2014', '2015', '2016', '2017', '2018')
disney <- c(11, 13, 11, 8, 12, 11, 12, 8, 10)
# graficando con codigo
plot(x = year,
y = disney)
# editando la grafica
plot(x = year,
y ... |
8d7f955f68e027699216630c1735f1402d9ff4a3 | 3d0787d24620c700303ecdc4453325b6235c0e5d | /02-decision_loop/break_next.R | c5a5a75d1e4e4eaf5c3e3cd3e466cf8a5002acf4 | [] | no_license | lincolnbrito/r-examples | 2244e0160944f65c276a58c9e97b5a4ead8923b4 | ab75c88576026ee839befb0f9acccf52ec6f2e4e | refs/heads/master | 2020-03-08T10:55:10.518422 | 2018-04-05T03:21:00 | 2018-04-05T03:21:00 | 128,084,946 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 158 | r | break_next.R | x <- 1:5
for (val in x){
if (val == 4) {
break
}
print(val)
}
for (val in x) {
if (val == 3) {
next #go to next iteration
}
print(val)
} |
04d004abb765f503fdb8fea554c3f74e924d6509 | 28bf4e2873739174b39181ebb6a52ab1b685f8f2 | /src/archive/junk.R | 4dc9c10b9806cb2d78ea8d2ff858d0d7bbe72d35 | [] | no_license | camroach87/capture-recapture-code | 95ec4d9e584ca7a7af34c52b2d338bec464de463 | e1e00b1c65e3c1fc379dc67d08f86e8a5380ef46 | refs/heads/master | 2021-01-22T14:20:17.610587 | 2014-06-04T12:09:53 | 2014-06-04T12:09:53 | 17,207,384 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,845 | r | junk.R | #### 23/9/2013 ####
CR_RobustDesign(10,sim="Y", N.0=4000, p=0.02, nsampOcc=200, pBirth=0.03)
#### 22/7/2013 ####
mkOpenSimMtrx(N.0=5000, t=14, p=0.05, phi=0.9,pBirth=0.25, pImmigration=0.25)
table(rowSums(output[[1]][,1:8]))
CR_RobustDesign(1, sim="Y", N.0=5000, p=0.02, phi=0.9,pBirth=0.25, pImmigration=0.25)
#### 1... |
d72c84a25f55f316f723c116c71fd9a83caa2b29 | 2287e839ddf6bde1773161ac723e7aeda0baedea | /tests/test-mfdb_sql.R | 17d5da3fdf3988dd03f113b3417a963d33217638 | [] | no_license | gadget-framework/mfdb | 3e95a0d2331b310328f096bff87319c28ce6f0b3 | 1a5d866ddf9e82a178b63f34f269b9e171c70c58 | refs/heads/6.x | 2023-04-19T00:14:08.733554 | 2021-03-17T12:12:30 | 2021-03-17T12:15:03 | 19,570,112 | 2 | 3 | null | 2021-03-17T09:16:27 | 2014-05-08T10:48:44 | R | UTF-8 | R | false | false | 10,313 | r | test-mfdb_sql.R | library(mfdb)
library(unittest, quietly = TRUE)
helpers <- c('utils/helpers.R', 'tests/utils/helpers.R') ; source(helpers[file.exists(helpers)])
logging::logReset() # Don't let logging messages sneak into test output
ok_group("sql_quote", {
sql_quote <- mfdb:::sql_quote
ok(cmp_error(sql_quote(c()), "empty"),... |
ec13e20dc983f03ceaea5c66605b1a6ffcc83efd | 87220c1f9a5cd789272fb950d47887a3a15ef0f5 | /pySensorbase/client/client.R | fbd55f49cd9f7b2da8a62fc4ce7b60ec896faa73 | [] | no_license | nesl/splt | 1f25c631536e0d639d5bf2acd6739c34a5bb35a0 | 4de9adc58ad38bd1e42545102c150403d2da72b1 | refs/heads/master | 2021-05-16T03:08:10.781402 | 2017-11-17T15:11:45 | 2017-11-17T15:11:45 | 12,226,748 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,656 | r | client.R | client = function(rfidFile, pmFile, userID) {
# This is the client to make sense of the read data
# RFID file format
# Timestamp, Appliance ID, Tag ID
# PM file format
# Timestamp, Appliance ID, Watt
# Usage time
USAGE_TIME = 60
total_power = 0
# Read the data from the file
rfid_data = rea... |
0eeb7e7a8650cef707670482fe5bbf224fa2c0f8 | 3dbb408ab830a572260dd9c8f755d7ee00cdf89c | /day02/part1.R | f8b88ae2930dcf7c534251e78368a477476a2d95 | [] | no_license | ryanbthomas/adventofcode2020 | 32bf46be3b91479ccab69ae67d6cc95dbb2d6da6 | 2dfd227538c08e6d6fdf30c25b8ac5b6b72574c2 | refs/heads/main | 2023-04-09T08:50:51.176833 | 2021-04-23T19:36:58 | 2021-04-23T19:36:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 645 | r | part1.R | input_file <- "day2/input/day2_real"
passwd <-readLines(input_file)
library(stringr)
library(purrr)
policy_passwd <- str_split(passwd, pattern = ":")
policies <- map_chr(policy_passwd, pluck, 1)
passwd <- map_chr(policy_passwd, pluck, 2)
chr <- str_split(policies, pattern = " ")
rng <- map_chr(chr, pluck, 1)... |
1b7af165b1fe91011cd02641058b072c7a0efb25 | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/CLVTools/R/pnbd_dyncov_LL_Bi.R | a53a975ec3573748a006b2865349f2f9bb688bb8 | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,769 | r | pnbd_dyncov_LL_Bi.R | .pnbd_dyncov_LL_Bi <- function(data.work.trans.aux, cbs.t.x, i){
t.x <- Aji <- adj.Walk1 <- d <- Id <- Aki <- Num.Walk <- adj.Max.Walk <- delta <- NULL
# because there are only AuxTrans there is exactly one single row for each customer
# -> there is no need for by=Id
#Also replacing Walk_i with Max.Walk was o... |
9e15ebaf5a8a438d362240e87bf034c837aa72b1 | f834196d68e850df95f24bec0ed38ccf686b2e17 | /man/anno_barplot.rd | 8589c7229816ee8850c0d1b071133a0c7818e8b3 | [] | no_license | kassambara/ComplexHeatmap | 141bfc3fb0a22619697d7a418c5eb262c5ddac96 | ff9ffa810ca9f16a253861d97301062962dbe38b | refs/heads/master | 2020-12-03T05:14:27.135170 | 2015-07-13T21:25:54 | 2015-07-13T21:25:54 | 39,065,677 | 1 | 2 | null | 2015-07-14T09:20:58 | 2015-07-14T09:20:58 | null | UTF-8 | R | false | false | 882 | rd | anno_barplot.rd | \name{anno_barplot}
\alias{anno_barplot}
\title{
Using barplot as annotation
}
\description{
Using barplot as annotation
}
\usage{
anno_barplot(x, which = c("column", "row"),
gp = gpar(fill = "#CCCCCC"), axis = FALSE, axis_side = NULL,
axis_gp = gpar(fontsize = 8), ...)}
\arguments{
\item{x}{a vector of va... |
f7f32967fce750fc6cab577cc66f5dbe378f4b3a | 29585dff702209dd446c0ab52ceea046c58e384e | /FSAdata/R/WalleyeEL.R | 563a704ec70c5c4e1ce6b4369781332a87bf1347 | [] | 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 | 1,426 | r | WalleyeEL.R | #' @title Stock and recruitment data for Walleye from Escanaba Lake, WI, 1958-1992.
#'
#' @description Abundance of age-0 and age-5 and older Walleye (\emph{Sander vitreus}), abundance of adult Yellow Perch (\emph{Perca flavescens}), and coefficient of variation of May temperatures for Escanaba Lake, WI, 1958-1992.
... |
27a49832cfef19d5bab1c186dd140b6b747c4808 | a96e99a689291c49dd86d377f074ebadb2437fe9 | /man/vno.Rd | 705de40aaaa4b9c076c6b66380fe1e8ff7436ba4 | [] | no_license | cran/GPIC | 9d6d0322fe75d055607569f381f8d4cdde87a293 | f8d8ddaee313328db92cf88004f888042cbe850e | refs/heads/master | 2023-03-18T05:29:13.277515 | 2021-03-01T08:00:13 | 2021-03-01T08:00:13 | 343,411,693 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 609 | rd | vno.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vno-data.R
\docType{data}
\name{vno}
\alias{vno}
\title{Results of Vietnamese National Olympiads 2010-2020}
\format{
A data frame with 24151 rows and 5 variables:
\describe{
\item{ID}{student ID}
\item{Year}{year of award}
\item{Team}{adminis... |
d5473a285dfe0aa5230139ea54c0b3d9f1e1e8f5 | bf2d49ee7650586b57f846faf3b8915dece85cc4 | /best.r | e662e6cf572fcc1ae8316f11d4c33c9d66e45455 | [] | no_license | SnowCrash35/ProgrammingAssignment3 | 16adfeca86c2572b87799715edd3c9b62b5c0868 | df9b455fca8e6fcf989b37123d6bd09acc88df3a | refs/heads/master | 2020-06-27T05:07:35.273886 | 2017-07-13T23:46:27 | 2017-07-13T23:46:27 | 97,048,929 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,671 | r | best.r | best <- function(state, outcome)
{
# read outcome data from file
# ===========================
# Column 2: Hospital Name
# Column 7: State
# Column 11: 30-day death rate for heart attack
# Column 17: 30-day death rate for heart failure
# Column 23: 30-day death rate for Pneumonia
... |
c6e903ff2b11166efd2cd2aabdfae3290d1e1c9f | 2492c8dee590ff43db2189ddca8c68ac32d49bdf | /TSExperiment/R/boxtest.R | 9b4e407abc0c2b769364a2ad947a926690518c29 | [
"MIT"
] | permissive | dfreestone/TSLibrary | 1848fd0f7cc601bee816dd377742b0901ab3045f | 5b864d23e2c26da1745fc039b5c0358dbda7e69a | refs/heads/master | 2023-03-08T12:07:22.163911 | 2020-04-08T21:21:52 | 2020-04-08T21:21:52 | 83,917,970 | 0 | 0 | MIT | 2022-12-12T10:27:35 | 2017-03-04T19:10:41 | HTML | UTF-8 | R | false | false | 13,298 | r | boxtest.R | # boxtest
# perform standard box tests and email the results
#
# Author(s) : David Freestone (freestoned@wpunj.edu)
# Date : 2017-05-28
#
# This code is covered under the MIT license
# Copyright (c) , David M. Freestone
# All rights reserved.
#
# ----------------------------------------------------------------... |
bcdbbf5b2430f0544ef057fa4ef95adce8fcb782 | f2d3a834eb614c444e4c4d2f863577e804d9fb70 | /man/scale_01.Rd | 9b3d062f9575daa35bd9a26e09f4a17651061a96 | [] | no_license | David-Hervas/clickR | 150669cc67575659258e2bb44f429544e52e809c | cb738e505375376d91ac37eb01813ac3fb0e1432 | refs/heads/master | 2023-08-14T05:06:15.095067 | 2023-08-07T17:01:53 | 2023-08-07T17:01:53 | 90,495,146 | 3 | 3 | null | null | null | null | UTF-8 | R | false | true | 283 | rd | scale_01.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/descriptive.R
\name{scale_01}
\alias{scale_01}
\title{Scales data between 0 and 1}
\usage{
scale_01(x)
}
\arguments{
\item{x}{A numeric variable}
}
\value{
Scaled data
}
\description{
Escale data to 0-1
}
|
25c4caf73cbcf7069e997c4bf7b30c79c941c954 | 13895420920703501ab66c28a3927089a2de042e | /R/ICLUST.diagram.R | d0b9cd5d3f60f59f1dacfb77e1386366d2487a76 | [] | no_license | cran/psych | 3349b3d562221bb8284c45a3cdd239f54c0348a7 | ee72f0cc2aa7c85a844e3ef63c8629096f22c35d | refs/heads/master | 2023-07-06T08:33:13.414758 | 2023-06-21T15:50:02 | 2023-06-21T15:50:02 | 17,698,795 | 43 | 42 | null | 2023-06-29T05:31:57 | 2014-03-13T05:54:20 | R | UTF-8 | R | false | false | 15,658 | r | ICLUST.diagram.R | #modified 6/6/20 to vectorize the labels and rectangles.
#modified 8/19/22 to make labels characters (which they are normally)
"iclust.diagram" <-
function(ic,labels=NULL,short=FALSE,digits=2,cex=NULL,min.size=NULL,e.size=1,colors=c("black","blue"), main="ICLUST diagram",cluster.names = NULL,marg=c(.5,.5,1.5,.5),plot=... |
825e2d2535c0e93ad482bdb82c5344915bb3fde9 | 87927a36c2b4d2f5c528724d57c801766302cae2 | /wsjchart1.R | 9d8d68f3c0a3f8eedb9a41d8eb294e79fdbb3237 | [] | no_license | econdataus/ipums | d79c25519f81b6a023b31d3b5e9747b1b38e8f39 | 1db144c9f38c8456cd08a3269755fde9d117614b | refs/heads/master | 2021-01-10T21:35:40.009565 | 2015-04-19T18:24:36 | 2015-04-19T18:24:36 | 31,491,924 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,881 | r | wsjchart1.R | dd <- read.csv("wsjstem1.csv")
labyears <- "1990-2010"
source("stem1labels0.R")
with(dd, plot(native_coll_wkwage_change ~ immig_stem_change, xlim=c(-2,4), col=col, cex=0.6,
ylab="Percentage change in real native college-graduate wages",
xlab="Percentage change in foreign STEM workers"))
with(dd, text(native_coll_wk... |
3f38dfa38ee90bf1abbcb0c87f7fc7937cbf3ff2 | 1c5620ebfe6b2ce9e9a1b6332ac229e041d433c8 | /oldman/annotateTrans.Rd | cca6cce273d32a225f279908606625f0b634c9b5 | [] | no_license | lawremi/VariantTools | 33a752d2a68ca0212c79f3849f8081733da33072 | fdcc2e645f034667e89cfe230b84034efb942d3b | refs/heads/master | 2021-06-03T12:12:14.520204 | 2020-04-10T19:58:01 | 2020-04-10T20:00:16 | 101,421,367 | 1 | 1 | null | 2018-01-30T17:36:21 | 2017-08-25T16:18:06 | R | UTF-8 | R | false | false | 1,731 | rd | annotateTrans.Rd | \name{annotateTrans}
\alias{annotateTrans}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
%% ~~function to do ... ~~
A function to annotate a transcript grl with variant information.
}
\description{
%% ~~ A concise (1-5 lines) description of what the function does. ~~
Given a txbd, co... |
6971df31a30fecac33f6f41d8f81a1b017b6d350 | 5d25d2b58e5b8e3fda7d1f4f9564d6e3662f1a87 | /man/ctSFTM.Rd | 9a514a3b0f484f2421b4e13eed76d5321ac91bc2 | [] | no_license | shuyang1987/contTimeCausal | 4bd1f9c2045b6c401eb4b2fbb0ae21a19688d559 | 00bf39ffeb270db86c77edafbbdf727d1e9c8c25 | refs/heads/master | 2021-06-08T07:48:50.036125 | 2021-05-06T16:28:11 | 2021-05-06T16:28:11 | 170,953,343 | 6 | 2 | null | null | null | null | UTF-8 | R | false | true | 6,145 | rd | ctSFTM.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ctSFTM.R
\name{ctSFTM}
\alias{ctSFTM}
\title{Continuous-time Structural Failure Time Model (ctSFTM)}
\usage{
ctSFTM(V, deltaV, U, deltaD, Lti, Ltd4Vtime, Ltd4Utime)
}
\arguments{
\item{V}{the time to treatment discontinuation or failure or ce... |
dbb41fe4354d994eca3266d96fa28fd6b9585342 | 295a2ae5946d7481ac067822577ec9ad3f09c6cb | /man/installing.rcasc.Rd | 850aec364f5f10bf9be2c463c228775943de6c01 | [] | no_license | kendomaniac/BCsctutorial | c61b134581b66736d5a352cc88860883638775d0 | c121631ed7f89e1f97f2af42daa4b0090d007a02 | refs/heads/main | 2023-02-15T07:13:31.640633 | 2021-01-11T08:16:25 | 2021-01-11T08:16:25 | 322,218,433 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 496 | rd | installing.rcasc.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/installing.rcasc.R
\name{installing.rcasc}
\alias{installing.rcasc}
\title{A function prepare the environment for the SCA tutorial.}
\usage{
installing.rcasc()
}
\description{
This function check that dcker is installed and download locally t... |
2f587adbd42cc1172b18978a34f805a0873793a6 | a21b4d4c4ca56f0accab4924df346d896186be39 | /cachematrix.R | 8647a730cc750db5e8e26849e92e181f64798289 | [] | no_license | RajatAst/ProgrammingAssignment2 | fdd2732737ff5571deb1686e70fd52dd619a6020 | 477324b833c26a04d6e1b08207e59bd4b8c5a448 | refs/heads/master | 2022-11-23T05:17:23.326618 | 2020-07-29T12:51:07 | 2020-07-29T12:51:07 | 283,414,300 | 0 | 0 | null | 2020-07-29T06:10:12 | 2020-07-29T06:10:11 | null | UTF-8 | R | false | false | 1,437 | r | cachematrix.R | ## Put comments here that give an overall description of what your
## functions do
## Write a short comment describing this function
## This function allows to set & get value of matrix,
## and its inverse.
makeCacheMatrix <- function(x = matrix()) {
i <- NULL ##initialising i with null
##setting the matrix... |
3db4830f1aa5d29cfc7ce368006ae4823cb8668c | a560269290749e10466b1a29584f06a2b8385a47 | /Notebooks/r/sociopath00/titanic-with-socio/titanic-with-socio.R | f97fb7010ae679ce50cb9bb5517077a523c217e2 | [] | no_license | nischalshrestha/automatic_wat_discovery | c71befad1aa358ae876d5494a67b0f4aa1266f23 | 982e700d8e4698a501afffd6c3a2f35346c34f95 | refs/heads/master | 2022-04-07T12:40:24.376871 | 2020-03-15T22:27:39 | 2020-03-15T22:27:39 | 208,379,586 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,318 | r | titanic-with-socio.R | # This R environment comes with all of CRAN preinstalled, as well as many other helpful packages
# The environment is defined by the kaggle/rstats docker image: https://github.com/kaggle/docker-rstats
# For example, here's several helpful packages to load in
library(ggplot2) # Data visualization
library(readr) #... |
078a6539c292cdc61e5913175872a94c417d48c0 | 680f31307651d40672fca41c08df08be053d478b | /man/maxGripFinder.Rd | f46c980ea883cca5ecd92c4c1cb74c011f563611 | [] | no_license | jonkeane/mocapGrip | ad30226f8a5fd486cc8c11f652e536762bb18136 | ffeaafc8071a2e2d94dcf1518e61e56ba647a76f | refs/heads/master | 2020-12-24T20:52:13.258443 | 2016-06-11T21:59:14 | 2016-06-11T21:59:14 | 56,876,628 | 3 | 0 | null | 2016-05-27T17:23:35 | 2016-04-22T18:22:16 | HTML | UTF-8 | R | false | true | 1,008 | rd | maxGripFinder.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/processingFunctions.R
\name{maxGripFinder}
\alias{maxGripFinder}
\title{Processing function for finding maximum grips}
\usage{
maxGripFinder(data, percOcclusion = 0.05)
}
\arguments{
\item{data}{the data to process.}
\item{percOcclusion}{the... |
d2ab6a0fd7376a8ef0f5a074340a80ce19d01ad7 | 1ed87c596958af5205fe6efe481d97f456e1fae6 | /Assignments/midterm/wendy.R | c4ba36de924cc47aca909f6dce96520ef0e5c595 | [] | no_license | aaronxhill/dataviz14f | 1530a3d16803c3e49d0f940dde687da6ebe3b6f5 | 290187d53b1e88bcf255c23dd2ba8e3af7294ea2 | refs/heads/master | 2020-03-30T19:02:34.451718 | 2014-11-15T00:33:58 | 2014-11-15T00:33:58 | 23,426,895 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 882 | r | wendy.R | setwd("C:/Users/Wendy/Desktop/Data Visualization/Assignment 1")
titanic <- read.csv("titanic.text")
is.numeric(titanic$Pclass)
titanic$Pclass.f <- factor(titanic$Pclass, labels = c("First Class", "Second Class", "Third Class"))
# add a fourth variable / shape
is.factor(titanic$Pclass.f)
summary(titanic$Pclass.f)
is.... |
abb1b12a3825a5416e6a830c1000cb07074353dc | 27beeb71964e1064586bc9390ea5a21af4e4fe3f | /Functions.R | 505de70bb33990e5db95ef93f4ba39beabb1de3f | [] | no_license | Zaphiroth/ntm_docker | a9e849aa74e3e78a4e26f95c99b0ec8f96ec0bf2 | ba66278df818c0cf34e2399a6a006c6cb2f71c11 | refs/heads/master | 2020-05-16T17:23:32.481792 | 2019-05-17T09:25:42 | 2019-05-17T09:25:42 | 183,192,573 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 34,591 | r | Functions.R |
##------------------------------------------------------------------------------
##-- Get previous data
##------------------------------------------------------------------------------
get_p_data <- function(proposal_id, p_sales_report_id, personnel_assessment_id) {
## p_sales ----
db_s... |
d1bd085d13dcda7a230c3a8498b97e5828ed8add | 6c4464440bf42df3df8eb947b3a2798476dfac78 | /PBSmodelling/man/resetGraph.Rd | 62b01df3536f29ef9daa9faff7bde4c6732ed508 | [] | no_license | pbs-software/pbs-modelling | ad59ca19ced6536d2e44ff705e36a787341f60d7 | 44b14f20af33d5dee51401bad2ff3dce2dfd3cea | refs/heads/master | 2023-01-11T16:18:06.846368 | 2023-01-06T22:45:05 | 2023-01-06T22:45:05 | 37,491,656 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,076 | rd | resetGraph.Rd | \name{resetGraph}
\alias{resetGraph}
\title{Reset par Values for a Plot}
\description{
Reset \code{par()} to default values to ensure that a new plot
utilizes a full figure region. This function helps manage the device
surface, especially after previous plotting has altered it.
}
\usage{resetGraph(r... |
59ed252e089c16cde05601837df50c68d9f73e07 | 2db8d6baaf70d7254c7cd9b1d2098f2c61580c96 | /DataSetOne/Occupancy_Tuesday.R | 78a777bbc13d4a3f770e81a2c1c08b70d6d2207a | [] | no_license | ShaneColeman/Big_Data_Occupancy | 9bc1095bdfc682a772594fffcf2d1188298f1b1c | bfdc95d283cdd033f21f51228579df82684d48a2 | refs/heads/master | 2021-01-01T05:09:26.926197 | 2016-05-02T22:10:59 | 2016-05-02T22:10:59 | 56,057,718 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,032 | r | Occupancy_Tuesday.R | #Occupancy_Tuesday.R
#library(plyr)
#Setting Histogram Colour
colourHist <- c(1:3,4:7)
#Count Attributes
TuesdayTemperature <- count(occupancyTuesday,"Temperature")
TuesdayHumidity <- count(occupancyTuesday,"Humidity")
TuesdayLight <- count(occupancyTuesday,"Light")
TuesdayCO2 <- count(occupancyTuesday,"CO2")
Tuesda... |
e90477500ad68830c3b11dd72b5aac0e8fdddd94 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googleanalyticsv3.auto/man/management.filters.delete.Rd | 27c25dd1086e45022b096e78160493d39701897a | [
"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 | 871 | rd | management.filters.delete.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/analytics_functions.R
\name{management.filters.delete}
\alias{management.filters.delete}
\title{Delete a filter.}
\usage{
management.filters.delete(accountId, filterId)
}
\arguments{
\item{accountId}{Account ID to delete the filter for}
\ite... |
1efb25ac55c0cc72f726ec2785fc78f57f631101 | fa6bf6d629ce6a6524526d4c8ec0c37600106780 | /src/utitlities/bar.R | 0a59210b54df8b04016501c932a20b28aaf31be4 | [] | no_license | whyshu/TWITTER_FAKE_NEWS_DETECTION | 2ab17327f626452219d56e38e0c91781394aae15 | 837cef195bc8ad4b4d7f4ff021880de4625dc351 | refs/heads/master | 2021-05-08T20:28:53.096443 | 2018-01-31T00:29:40 | 2018-01-31T00:29:40 | 119,612,431 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 664 | r | bar.R | correct<-c(1000,1500)
wrong<-c(50,75)
m<-c(correct,wrong)
mat<- matrix(m,nrow=2,ncol=2,byrow=TRUE)
rownames(mat)<-c("Correct", "Wrong")
colnames(mat)<-c("Spam", "NonSpam")
par(mfrow=c(2,2))
barplot(mat,main="Accuracy of classifier using training data",
xlab="Classes", col=c("green","red"), legend = rownames(m... |
50f4a07c78b66a75764372c7de05e35fb2289ca7 | 748fb3a6f9b194bdaad36813b090e56dd4f40582 | /Week 3 2020/Passwords.R | 3a9c28f24076a343ef182e29bf46d04be1b4d98c | [] | no_license | Jazzalchemist/TidyTuesday | 768fc0b2895bbddb121e4a44eb500bdcda0802fa | 3ca4115502c4e5453a78edd207fc816263b18c4b | refs/heads/master | 2022-08-31T02:08:33.291198 | 2022-08-09T05:13:33 | 2022-08-09T05:13:33 | 175,743,720 | 31 | 11 | null | null | null | null | UTF-8 | R | false | false | 3,140 | r | Passwords.R | ## Tidy Tuesday Week 3 2020 - Passwords
## Data Source: Knowledge is Beautiful
#Load packages
library(tidyverse)
library(extrafont)
library(ggfittext)
#Import data
passwords <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-01-14/passwords.csv')
#Inpect data
hea... |
b95f550304e5a3b26189a70a0c6b188e97b1276e | 62715380a7dddcce8b5bc2c84c6c5d4a32b10d4f | /Baidu_Geocoding.R | bba8b5f60130e95da51f7c8b9f110e5e8d8fd3c5 | [] | no_license | iandmozart/CN_Addr_Geocoding | a90161c5f444699d0bdedda3c177cb480da4c2be | d1f9af8d7f2156dd70d1017ea610356de4c1a8f9 | refs/heads/master | 2020-08-25T02:27:42.289295 | 2013-08-21T12:59:25 | 2013-08-21T12:59:25 | 216,948,535 | 1 | 0 | null | 2019-10-23T02:14:24 | 2019-10-23T02:14:24 | null | UTF-8 | R | false | false | 4,893 | r | Baidu_Geocoding.R | #Baidu Maps Geocoding Service documentation: http://developer.baidu.com/map/webservice-geocoding.htm
#Please read through the Google_Geocoding.R firstly,
#Baidu GeoCode sample: http://api.map.baidu.com/geocoder?address=地址&output=输出格式类型&key=用户密钥&city=城市名
#Baidu ReverseGeoCode sample: http://api.map.baidu.com/geocoder?lo... |
bbb13aa4ac848325bb5ce9ae0d2167344ba3e380 | ef3315aa25c746c84a6357bd46fb3a67fc0b7b41 | /man/zbind.Rd | 30e9950e1445db5fbf361da71b97b7da8caf6add | [] | no_license | jweile/yogitools | 4bbdba6f2ade9a2ef38c1fac14be9c883e159e39 | 35265272206d2e3daed1b8b0cc11da4c17166d49 | refs/heads/master | 2023-05-10T21:36:48.707325 | 2023-05-03T21:29:22 | 2023-05-03T21:29:22 | 120,494,457 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 372 | rd | zbind.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/yogitools.R
\name{zbind}
\alias{zbind}
\title{3D-bind matrices}
\usage{
zbind(...)
}
\arguments{
\item{...}{Any number of matrices of the same size}
}
\value{
A 3D array of the bound matrices
}
\description{
Binds matrices of same size togeth... |
bf6530900bc44fdcc2bcfa49c2216f92378e96ac | 2161e2c9b1463f3f0b8d27a9447c136e5e08d2b9 | /R/barplotRichness.R | 6b5e522646ac4be0a50ffae480dff333b81645b4 | [] | no_license | NCRN/NCRNbirds | 14a258e8182849bb0434eb4368fa291105d56a7c | 5a512b736d674d9308c27667e7a99b142aebfcef | refs/heads/master | 2023-08-16T13:00:26.367713 | 2023-07-11T15:54:50 | 2023-07-11T15:54:50 | 32,335,489 | 5 | 12 | null | 2023-08-17T15:09:47 | 2015-03-16T15:44:44 | R | UTF-8 | R | false | false | 6,993 | r | barplotRichness.R | #' @include NCRNbirds_Class_def.R
#'
#' @title barplotRichness
#'
#' @importFrom dplyr case_when mutate
#' @importFrom ggplot2 aes coord_flip element_blank element_rect element_text geom_bar ggplot labs scale_fill_manual scale_x_discrete theme
#' @importFrom magrittr %>%
#' @importFrom RColorBrewer brewer.pal
#' @... |
bcf441d6ddb9f570d134c08cee3aa8658d38fa03 | d8873812872be794f291a120940ccaa298238b6c | /tests/testthat/test-schema.R | e89963ba32120e2f6929c7a0399583a390428788 | [] | no_license | cran/mdbr | 6dcdb582d80a5210535a9b7bd9bc523512af3c3e | 3afb6a8332a514b2bd5e79864fdf49422e0b54ec | refs/heads/master | 2023-01-06T06:27:15.750095 | 2020-11-09T08:30:02 | 2020-11-09T08:30:02 | 311,429,395 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 488 | r | test-schema.R | library(testthat)
library(mdbr)
test_that("schema returns col spec", {
skip_on_cran()
dat <- mdb_schema(mdb_example(), "Flights")
expect_s3_class(dat, "col_spec")
})
test_that("schema can be condensed", {
skip_on_cran()
a <- mdb_schema(mdb_example(), "Flights")
b <- mdb_schema(mdb_example(), "Flights", co... |
0a6e7fdbe341f831e357d45f9104c5139001328c | 660b7765755e497ddc066f808dc7992fc905fc89 | /script/train.R | 74c7bd06ab0291a4e2aed8b9089e106ec357080a | [] | no_license | pykler/predmachlearn-006 | 797070f2eae4db2146c90b3b17d495f938c372d0 | 36c60cfb18c49e5c9a528e3dae0052f8dc53d092 | refs/heads/master | 2021-01-22T17:22:05.614216 | 2014-10-20T14:15:22 | 2014-10-20T14:25:14 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 384 | r | train.R | #!/usr/bin/env Rscript --vanilla
args <- commandArgs(TRUE)
method <- args[1]
if (is.na(method)) {
stop('No training algorithm supplied')
}
library(caret)
pdir <- '~/projects/predmachlearn/project'
load(paste0(pdir, '/data/pml_training_noagg.Rdata'))
project_dir <- pdir
print('NoAgg approach')
print(paste('Traini... |
b4da3869b1ead2dd9195c34d298d6be14c6e3bcd | 91437aa75903254a42f677a6c61e0b16975789ac | /plot4.R | 8adacdfddcb381842732396162d11a985cdc12a7 | [] | no_license | pgirish/ExData_Plotting1 | 56c166c8c9b4ebc80877ba8bdaadd24a0a4671d5 | de7cc089fc82fd819339423ec3fac6f1f2b2b8c3 | refs/heads/master | 2021-01-16T20:44:27.431683 | 2016-02-17T23:28:10 | 2016-02-17T23:28:10 | 51,870,353 | 0 | 0 | null | 2016-02-16T21:08:39 | 2016-02-16T21:08:37 | null | UTF-8 | R | false | false | 1,575 | r | plot4.R | # Read the entire data from the given text file
# subset data by filtering two days of data
dataFile <- "household_power_consumption.txt"
data <- read.table(dataFile, header=TRUE, sep=";", stringsAsFactors=FALSE)
dataSubSet <- data[data$Date %in% c("1/2/2007","2/2/2007") ,]
## read in date/time info in format 'd/m/y h... |
f07f8f5671bdfcf1d97829d00b76f2cf9cf6b3a9 | 2b471d85b488a05aff1c19dd2ea8870daa11ed9a | /R/package-sparsepp.R | 8a369e9f2e935a66be3dc48e8a7a93de09956166 | [
"BSD-3-Clause"
] | permissive | dselivanov/r-sparsepp | 8501ecc6c6cdf60a5de8f124503b0d34d750dd25 | fe71f4f99eff216b4115fd554b7eb407bd59c4c0 | refs/heads/master | 2021-09-23T12:04:33.371257 | 2018-09-22T12:35:51 | 2018-09-22T12:35:51 | 77,609,339 | 8 | 3 | null | 2018-09-22T12:35:52 | 2016-12-29T12:03:32 | R | UTF-8 | R | false | false | 1,746 | r | package-sparsepp.R | #' sparsepp
#'
#' \code{sparsepp} provides bindings to the
#' \href{https://github.com/greg7mdp/sparsepp}{sparsepp} - fast, memory efficient hash map for C++.
#' \code{sparsepp} is an open source C++ library derived from Google's
#' excellent sparsehash implementation, but considerably outperform it - \url{https://gith... |
1708c0f1edd947fde7e30145a81c9c4e17777b6d | a03da6a1edc7b1a1cf4b0829f5ece771f584df95 | /R/EmpRule.R | b4d2b8a6312d98daf34f97f3b45a932bb9e53a3b | [] | no_license | homerhanumat/tigerstats | 4fbcc3609f46f6046a033d17165f7838dbd77e1a | 17067f7e5ec6b6cf712b628a4dbf5131c691ae22 | refs/heads/master | 2021-07-06T06:24:07.716196 | 2020-09-22T15:24:01 | 2020-09-22T15:24:01 | 15,921,287 | 14 | 7 | null | null | null | null | UTF-8 | R | false | false | 5,932 | r | EmpRule.R | #' @title Empirical Rule
#' @description An app to investigate how the Empirical Rule applies to symmetric data and skewed data. The user can select
#' is they want to view a histogram of symmetric data or skewed data. Vertical bars are also plotted to signify
#' one, two, and three standard deviations from the mea... |
0d1db9167b98e0eb07abe07f1bad4a4937f7b4fb | bb5cc42782e2751e7df4c1f8330402df8611bf5c | /scripts/analyze_discussion.R | ee3515b2e7c7b1d154561f438964b0576a29702a | [] | no_license | femeunier/LianaRemoval | 5365ef7d9e050ae74eff6211f014f732910dc01b | 8a818ab8618e05bc4bf837525f8a18e1c5c385c7 | refs/heads/main | 2023-01-28T05:33:26.582573 | 2020-12-08T10:04:56 | 2020-12-08T10:04:56 | 319,260,643 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,977 | r | analyze_discussion.R | rm(list = ls())
library(ggplot2)
library(dplyr)
library(albedo)
library(reshape2)
library(tidyr)
# load("/home/femeunier/Documents/projects/LianaRemoval/outputs/removal.RData")
# control <- datum
# removal <- datum
N = 100
init = 99000011369
directory <- "/data/gent/vo/000/gvo00074/pecan/output/other_runs/removal/ou... |
cfc9e82ac958c082e8c80e378e4c83c349e84ab8 | ea0bc1dfa2a9d499a05eaf0995064c15ba37fa24 | /man/randomWalkByMatrixInv-matrix-method.Rd | 5d18409a4fdabab286eb2a6b5a4a230a6090b65f | [] | no_license | sqjin/netSmooth | 7fde4b241294d97f635ea9c8bccc784c5817b811 | 136384b31fe51e56acbb86400b33527489c273b2 | refs/heads/master | 2020-11-27T12:28:45.467858 | 2020-01-15T07:22:11 | 2020-01-15T07:22:11 | 229,440,928 | 0 | 0 | null | 2019-12-21T14:43:33 | 2019-12-21T14:43:33 | null | UTF-8 | R | false | true | 884 | rd | randomWalkByMatrixInv-matrix-method.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/randomWalkByMatrixInv.R
\name{randomWalkByMatrixInv,matrix-method}
\alias{randomWalkByMatrixInv,matrix-method}
\title{Smooth data on graph by computing the closed-form steady state
distribution of the random walk with restarts process.}
\usag... |
42d934a148d471dd8706df88ba2359bb125c6d23 | a7cf5209b264a8879c25ce652c030d9d308601f7 | /R/text-functions.R | 198c221bc636debe7d3e6e69b6b4db20bd23170d | [] | no_license | cran/scraEP | cfb79b4ae2be47a988073b96af70ba93c8623c5c | 782a58f9b26cba4bfd6ec323cc9f69eebe68f817 | refs/heads/master | 2021-07-14T17:08:02.369469 | 2021-06-23T06:00:02 | 2021-06-23T06:00:02 | 110,838,033 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,011 | r | text-functions.R | ## Function to remove all accents from a character string
unaccent <- function(text) {
text <- gsub("['`^~\"]", " ", text)
text <- iconv(text, to="ASCII//TRANSLIT//IGNORE")
text <- gsub("['`^~\"]", "", text)
return(text)
}
## Compare two string vectors for common elements.
strcomp <- function(text1, text2) {
... |
b371041c57dfbb103e73685a6fca8de9f104afbf | 9a1277a635b73c72472ae40442994d6c301ca1b4 | /docs/articles/nifti_basics.R | d7069dbbaf180561244d0335f897121794583911 | [] | no_license | muschellij2/neurobase | eaf8632de4659cd857bb5a864bf3a60f83333a89 | 375101bab5a546bd8c8a092c21190b48b36f9a13 | refs/heads/master | 2022-10-25T16:00:24.322516 | 2022-10-23T16:07:05 | 2022-10-23T16:07:05 | 68,750,968 | 5 | 4 | null | null | null | null | UTF-8 | R | false | false | 4,484 | r | nifti_basics.R | ## ----setup, include=FALSE------------------------------------------------
library(neurobase)
library(oro.nifti)
library(methods)
library(ggplot2)
library(httr)
library(reshape2)
knitr::opts_chunk$set(
echo = TRUE, comment = "")
## ---- eval = FALSE-------------------------------------------------------
# package... |
0b92c07c5d790ee6acd018c4bc9d0243df72e83a | 416b6b1b4678cbe68302af528fe95c366d9e23df | /man/dot_plot_profiles_fun.Rd | f042d0449f8c6a0d0f052af2c0cf26cff580e02e | [
"MIT"
] | permissive | GenomicsNX/SPOTlight | c9a9e7171a0891d5b686c50067c4553a553a91d5 | 1f364a965ab275ac54a711e28c67554db25d547e | refs/heads/master | 2023-05-01T13:12:05.810905 | 2021-05-26T09:02:57 | 2021-05-26T09:02:57 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 938 | rd | dot_plot_profiles_fun.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dot_plot_profiles_fun.R
\name{dot_plot_profiles_fun}
\alias{dot_plot_profiles_fun}
\title{This function takes in the H coefficient matrix object from and NMF object and returns plots to visualize the topic profiles between and within cell typ... |
48acf50e89c86930c7405bf8dd75dac080f441d3 | 10a489c8b3d0b174a54c0aa9ae1452ff2cd36a0a | /paperFigs.r | 15a0225159da79381d675116d795f74cc67a7afd | [] | no_license | jfelectron/Statiscal-analysis-of-large-biologial-datasets | 2d9832eb7bbd330d25917d335bb999ee6a79a3d6 | 3f6f28d28742460b3637eafce1c2ec32338a5915 | refs/heads/master | 2020-12-24T18:50:36.480693 | 2013-03-09T23:44:24 | 2013-03-09T23:44:24 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 20,901 | r | paperFigs.r |
library(ggplot2)
library(scales)
library(flowCore)
library(gridExtra)
library(reshape)
library(plyr)
library(grImport)
library(Hmisc)
library(corrplot)
source("/Users/jonathan/Documents/flowset2ggplot.r")
# generates Figure 1
#Figure 1a Clonal Workflow
color<-TRUE
if(color) {
PostScriptTrace("Clonal_workflow_co... |
78e6320138ec1ed3f27dd26ef95968ff58255574 | 7cdefcb3fcc0fde97aa607043ffd55bab8c3d21d | /project_code.R | 21ebff320b3bf55ebf4137e778affdc632d707f8 | [] | no_license | rahulb99/covid19 | f3d3f8f2fe92ad556db43edfa7e4ae8a8dbb1183 | e555667c21f5f8862869ec68f589be101764de11 | refs/heads/master | 2022-12-24T17:55:28.206450 | 2022-12-11T09:22:31 | 2022-12-11T09:22:31 | 261,263,752 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 27,269 | r | project_code.R | install.packages("devtools")
devtools::install_github("covid19r/coronavirus") # coronavirus dataset - updates every 24 hours
library(coronavirus)
data("coronavirus")
View(coronavirus)
coronavirus = subset(coronavirus, select = -c(Province.State)) # removes the Province.State column from the data
#EDA
library(tidyr)
su... |
2d88320fe8e2ed57228a856af33f707e1089d7db | f2bb233babbf25ab5373f543e3416dc3d5f11b51 | /examples/simulation_study/Simulate_Growth.R | 67b7d91663c5146b76380624254b35b7215d41da | [
"MIT"
] | permissive | quantifish/TagGrowth | 0170febd1697cda65887b2921c119f5e4cc9dc42 | cd57fd83902b976348f513262e533bf63603db1b | refs/heads/master | 2021-01-17T14:47:25.920221 | 2018-06-30T20:51:38 | 2018-06-30T20:51:38 | 23,371,721 | 0 | 0 | null | 2015-05-12T23:22:34 | 2014-08-27T00:42:42 | R | UTF-8 | R | false | false | 4,459 | r | Simulate_Growth.R | #=================================================================================
# SIMULATION DESIGN
#=================================================================================
# Make sure R is clean
rm(list=ls())
#=================================================================================
# USER SPECI... |
b195b398b9e06a453c04b23d12e35582c3ed0139 | 8eafdded307265eecb95adcbea7711d42113a9bb | /src/06_score_data.R | ecb987989b5340f6b2b907f4b3bba7a914e01b15 | [] | no_license | jvenzor23/ReboundNet | 5144c819027cc2c1d69399468648fbeac5e82efa | 3d7dfa9debebd740bf9297ff1a6ad6d99718db69 | refs/heads/master | 2022-12-07T12:49:12.283960 | 2020-09-02T21:49:39 | 2020-09-02T21:49:39 | 286,569,078 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 41,522 | r | 06_score_data.R | # This code examines the basketball pbp data
# Clean workspace
rm(list=ls())
# Setting Working Directory
setwd("~/Desktop/Deep_Learning/nba-movement-data/rebounding_data/output/")
# Calling Necessary Libraries
library(tidyverse)
library(dplyr)
library(ggplot2)
library(lubridate)
library(reticulate)
library(ggimage)
... |
4d5cb0959a5f35f6df0bfd0aa3d09d272f8c2c4a | 861b10b00863c66d1fefcf7451dc4cf0ab0e38c0 | /man/ggstrip-6v.rd | c7967c9937cdce7235b8c98968b4139e9259fd67 | [] | no_license | rmasinidemelo/ggplot | c96e50f1fa0f432a596a7649bd1285cfbb5e968e | 749060851fdc76f9885fb57196f93eb7ade02f74 | refs/heads/master | 2021-05-27T19:21:16.534374 | 2007-05-05T00:00:00 | 2007-05-05T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 425 | rd | ggstrip-6v.rd | \name{ggstrip}
\alias{ggstrip}
\title{Grob strip}
\author{Hadley Wickham <h.wickham@gmail.com>}
\description{
Grob for strip labels
}
\usage{ggstrip(text, horizontal=TRUE, strip.gp=ggopt()$strip.gp, text.gp=ggopt()$strip.text.gp)}
\arguments{
\item{text}{text to display}
\item{horizontal}{orientation, horizontal or ve... |
fe3219caa01d97ee528de0b6c773a1d0d40aca1d | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/nlme/examples/as.matrix.pdMat.Rd.R | 1a04faebdbb3f56438bacc3dad6cda82828875c2 | [] | 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 | 176 | r | as.matrix.pdMat.Rd.R | library(nlme)
### Name: as.matrix.pdMat
### Title: Matrix of a pdMat Object
### Aliases: as.matrix.pdMat
### Keywords: models
### ** Examples
as.matrix(pdSymm(diag(4)))
|
b7fefd870eb16a30ff125a98a8d0397801536f58 | dfcb29724707768dcff0e0dbb4fc200c97caa1aa | /Faster-with-attributes/faster_multinet_SIR_only.R | c920d7bbd7b1935bad4ca968d305e11ffb0221b7 | [] | no_license | niebieska/MasterThesis | f497fe1fc9dc6c99d4867e1062999513bcd8b130 | 930574bfa88b1326c6b14e6d4fd34a2667646b77 | refs/heads/master | 2022-11-06T14:58:40.211424 | 2020-06-22T22:34:24 | 2020-06-22T22:34:24 | 258,297,641 | 1 | 1 | null | null | null | null | WINDOWS-1250 | R | false | false | 7,516 | r | faster_multinet_SIR_only.R | # biblioteka
library(multinet)
listBeta <- c(0.19,0.28,0.22)
listgamma <-c(0.1,0.08,0.02)
networkName <- "MoscowAthletics2013"
countryDirectory <-"Italy"
scritpType<-"SIR_only"
networkFileName <-"MoscowAthletics2013_4NoNatureNoLoops.edges"
network<-read_ml(paste("C:/Users/Paulina/Downloads/FullNet/",networkFileName,s... |
8d7f5e3f09799f3074e998be17613b85b949639b | 678c7a152cc00df4d1c38fae6c59511b417aef54 | /R/aggregateData.R | d31186bbcf35744bcca3d5a21d9649515e04c6c6 | [] | no_license | GabrielHoffman/muscat | 368c21e3caae95abe29d6b2be79b174ed4ef79c0 | 93a3d88fd4a6bacb92811f12af10b5895b912bd7 | refs/heads/master | 2023-08-24T10:27:27.795931 | 2021-10-14T17:04:31 | 2021-10-14T17:04:31 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,244 | r | aggregateData.R | #' @rdname aggregateData
#' @title Aggregation of single-cell to pseudobulk data
#'
#' @description ...
#'
#' @param x a \code{\link[SingleCellExperiment]{SingleCellExperiment}}.
#' @param assay character string specifying the assay slot to use as
#' input data. Defaults to the 1st available (\code{assayNames(x)[1... |
6846486c39830d78334325c6a35b0df8f01a78f2 | 4320dcc8598eb1bf08ee2ebd71dcd2558fb579d8 | /man/gn_leaflet_basic.Rd | 14c65e6bd8c9a58afa21f8caf579554f87dc6a6b | [] | no_license | jacob-ogre/us.geonames | 74716ee395fc44aa4b472ff0b71b4f2a35e593aa | 94b2f8b5a8adb415c8c351312685a545e6aabf09 | refs/heads/master | 2021-01-20T10:29:47.349100 | 2017-10-24T18:36:08 | 2017-10-24T18:36:08 | 100,292,189 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 784 | rd | gn_leaflet_basic.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/map.R
\name{gn_leaflet_basic}
\alias{gn_leaflet_basic}
\title{Basic leaflet map of points identified in a \code{us.geonames} search}
\usage{
gn_leaflet_basic(df, weight = 1, color = "red", fillColor = "red",
fillOpacity = 0.3, radius = 5)
}... |
8c2c525c3776406e258006d80ab82d548d162f44 | 56208c93517c510bbe3a25fbee15735001f3fae4 | /Binaritize.R | 38730d0df6c36697129ec99e7ca10d24d07df0f2 | [] | no_license | AdiModi96/Hindi-Numbers-OCR | d83caea3fa00e7a9b8c80076fd67b9c6e73c4d43 | c1ef253bfdd04892826d375393fe87a7e396b655 | refs/heads/master | 2021-07-16T14:21:09.936474 | 2017-08-11T12:20:37 | 2017-08-11T12:20:41 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,134 | r | Binaritize.R | #installing and importing package
#declaring reading location
read_loc <- ("D:/Codes/Data-Science-OCR/OCR Test Alphabets-Discretized")
#declaring writing location
write_loc <- ("D:/Codes/Data-Science-OCR/OCR Test Alphabets-Binaritized")
#Getting the list of directories in the base read location
dirs_in_discretized <... |
47ed5869432377141ab7a3a31b6c926a2391a52a | ca41bb40b940bf70e3f3895ce1953a82e449c2f6 | /2020-08-19/app.R | acea9f0116015b1daf6452a0c01dbb419ba3491e | [
"MIT"
] | permissive | colinquirk/LivestreamCode | e78f5183296c4352c545ace49c5f7298ec89f300 | 67aa98ec0e35028284fbe1969f69bec4c926e851 | refs/heads/master | 2022-12-17T09:22:33.233048 | 2020-09-24T03:46:27 | 2020-09-24T03:46:27 | 283,785,358 | 2 | 3 | null | null | null | null | UTF-8 | R | false | false | 1,563 | r | app.R | library(shiny)
library(lubridate)
library(tidyverse)
theme_set(theme_minimal())
ridership = read_csv("CTA_Ridership.csv") %>%
mutate(service_date = mdy(service_date))
ui <- fluidPage(
titlePanel("CTA Ridership Data"),
sidebarLayout(
sidebarPanel(
sliderInput("year", "Pick a year:"... |
b214361824c23ced65b0fb78618734f32d3731f8 | aae46958c9b9ca7b33fd2e530f8cfc713d546560 | /ITEX_analyses/old_code/TraitsImputation_Bootstrapping.R | 6b4d4f5782280044fbb7fd6fd9a9fe05233811be | [] | no_license | EnquistLab/PFTC4_Svalbard | a38f155c5f905af74b7e265ace7dc256eaa4e2f9 | f372df13dc8002f347e2fe8810c4034ed02f06fc | refs/heads/master | 2022-02-16T09:20:34.170459 | 2022-01-28T14:14:50 | 2022-01-28T14:14:50 | 130,364,868 | 2 | 13 | null | 2021-05-19T11:11:34 | 2018-04-20T13:19:53 | HTML | UTF-8 | R | false | false | 1,909 | r | TraitsImputation_Bootstrapping.R | #### COMMUNITY WEIGHTED MEANS ####
# Libraries
# install.packages("devtools")
#devtools::install_github("richardjtelford/traitstrap")
library("traitstrap")
library("tidyverse")
comm <- read_csv(file = "community/cleaned_data/ITEX_Svalbard_2003_2015_Community_cleaned.csv", col_names = TRUE)
traits <- read_csv(file = "... |
019516ca18f764b4b5e9b8033704f17547f7d19f | 1b672dbb6a88af1ca8c99d0784d62f577c5e7ae0 | /plot3.R | 3119cfbc9ac2f40859e31f992941b8f98d069b0b | [] | no_license | 50stuck/ExData_Plotting1 | 2cfa5e9e3503fcbe655df2d59a32312d4d204417 | dccc7a25a66dea4bf8175578e39214e18b4da977 | refs/heads/master | 2021-01-09T06:36:21.394778 | 2015-01-10T02:28:57 | 2015-01-10T02:28:57 | 29,040,156 | 0 | 0 | null | 2015-01-09T23:29:39 | 2015-01-09T23:29:39 | null | UTF-8 | R | false | false | 1,660 | r | plot3.R | data <- read.table("household_power_consumption.txt", header=TRUE, sep=";",
na.strings="?")
data$Date <- as.Date(data$Date, "%d/%m/%Y") #converting date to propar class
subdata <- data[(data$Date=="2007-02-01" | data$Date=="2007-02-02"),] #subsetting
... |
8926a4636256b58cde902b222f63a557d05159cb | 91c63b8afda86eafa167101f8e2451eb570de3e1 | /R/hello.R | ec6da4d4780331a11c55d9cd6938762c53139314 | [] | no_license | valenwp/gitprobability | 0e796490049b3d4b967c95ca91a33c978dbf07ff | e64216474f556b012336ebde92a610fd5bd1803f | refs/heads/master | 2020-04-08T13:11:45.963428 | 2018-12-06T17:49:06 | 2018-12-06T17:49:06 | 159,379,866 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 465 | r | hello.R | #' @description Rejection sample from a pdf
#'
#' @param n a number
#' @param pdf a random variable
#' @param a a number
#' @param b a number
#' @param C a number
#'
#' @return the samples
#'
#' @examples
#' pdf<-function(x){x/2}
#' rejsample(2, pdf, 0, 5, .5)
rejsample<-function(n, pdf, a, b, C){
accepted<-0
samp... |
fa92be5724421aa808bd5493ff01bead25afe5fe | 70a9d1afa993fdf7b36673a6a72a4635d0948cb2 | /3.R | 81bdd67c6ee141d1f06a2c3720053af666f238e5 | [] | no_license | blanket77/R_Coding | a8171ca56c68102d8a483319968e3702c66e938a | 0033ba50226d1a9325b89596208bb924df6bd18a | refs/heads/master | 2023-06-23T22:16:23.697148 | 2021-07-25T05:01:32 | 2021-07-25T05:01:32 | 388,464,562 | 0 | 0 | null | null | null | null | UHC | R | false | false | 937 | r | 3.R | library()
# Sys.setlocale("LC_ALL", locale ="English")
library()
# Sys.setlocale()
installed.packages()
colnames(installed.packages())
installed.packages()[, c("Package", "Version")]
search()
m <- matrix(1:6, 3, 2)
m
t(m)
t <- function(x) x+100
t(m)
base::t(m)
xyplot(dist ~ speed, data=cars)
library(lattice)
sear... |
1809200888cdd546b0b22c56d49770845b5e59da | bc536251f89d76d70f702647fc63a0b8df50032c | /Estructuras-Programacion-R/closure.R | 129ddc66816724ab3defc18631e40b3590ee4ac8 | [] | no_license | Louiso/Curso-R | 50ff8439ff42e6cb987bee9ead88a795e04e51ed | 0c0880196ca086b51eb718983fc45cfdab1c3ad1 | refs/heads/master | 2021-01-24T00:03:55.885946 | 2016-06-11T03:13:49 | 2016-06-11T03:13:49 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 144 | r | closure.R | # Closure en R
w <- 12
f <- function(y){
d <- 8
h <- function(){
return(d * (w + y))
}
return (h())
}
environment(f)
ls()
ls.str() |
beb8fedb69e548a00224ecafb5a5f26327c40cf8 | 2fe4c16e0377a99e198ab04d5c378ca247ae4329 | /Rscript/R/mzkit/man/MolWeight.Rd | 7b4e937882b35a7d8af297a4ea4562dfa4a290b7 | [
"MIT"
] | permissive | xieguigang/mzkit | 1964d28b0fad5f6d44950fdccdd4a70877f75c29 | 6391304b550f7e4b8bb6097a6fb1c0d3b6785ef1 | refs/heads/master | 2023-08-31T06:51:55.354166 | 2023-08-30T08:56:32 | 2023-08-30T08:56:32 | 86,005,665 | 37 | 11 | MIT | 2023-03-14T14:18:44 | 2017-03-23T23:03:07 | Visual Basic .NET | UTF-8 | R | false | true | 353 | rd | MolWeight.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/MolWeight.R
\name{MolWeight}
\alias{MolWeight}
\title{Molecule weight calculate helper}
\usage{
MolWeight()
}
\value{
A list module that contains member function:
\enumerate{
\item \code{Eval}
\item \code{Weight}
}
}
\description{
Mo... |
bb3bda1706fe4355f9202c4673aef74c6d9b1340 | 35f05bea37f788d5eb969131c46b223d539a3452 | /2021/Week 23 - Survivor/survivor.R | ec28e33c70dcffa57f6b74be001958bf2dc9e54e | [] | no_license | Rohan4201/tidy-tuesdays | 66551be773da9a1dc5e1aa976efc90ab7e009a71 | 03a438ddeba91a290b998d682344e842f10f762b | refs/heads/master | 2023-07-16T15:59:14.055589 | 2021-08-31T19:50:54 | 2021-08-31T19:50:54 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,767 | r | survivor.R | library(ggplot2)
library(dplyr)
library(tidyr)
library(ggtext)
#fonts
sysfonts::font_add_google(name = "Roboto","Roboto")
showtext::showtext_auto()
castaways <- readr::read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2021/2021-06-01/castaways.csv')
df <- castaways %>%
select(sea... |
15a3b76cd48244f3e42b84eb13b8c2703a58c8db | 05f8b78b517ff731153deb34ee005e7883fa5510 | /man/aliases.Rd | 10b72b4ecbfebcdb7b539c8274fb25c8c27458ef | [] | no_license | cran/Rd | 468728b63f36c7c5f47422210aa40b3b57dfe19e | 17dfa33df36554a6b7483425cad7bbc5f4fa9f3c | refs/heads/master | 2020-04-17T05:11:26.453022 | 2019-05-23T03:10:27 | 2019-05-23T03:10:27 | 166,267,156 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,949 | rd | aliases.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/util-aliases.R
\name{aliases}
\alias{aliases}
\alias{s}
\alias{cl}
\alias{undim}
\alias{named}
\alias{clean_Rd}
\alias{get_attr}
\alias{forward_attributes}
\alias{fwd}
\alias{is_whitespace}
\title{Internal Utilities
These util... |
a40e7d8e28aae5fd53694483429ad4ff297f00cf | 83058c3faf9a4b2c7e0d0de1bf7426b60a59d64f | /man/bm_compound_poisson.Rd | 2de3b5432ad3dbd6ef2996e9d3ebe6352e7f493e | [
"MIT"
] | permissive | valcourgeau/ntwk | 55d163d11cb79eb888c2c4ad6b9e9f73e8bfb515 | 668657ee962fa6ccbd0cbf195673a36aed50b79b | refs/heads/main | 2023-07-26T18:28:44.556409 | 2021-09-03T10:35:28 | 2021-09-03T10:35:28 | 391,296,572 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,019 | rd | bm_compound_poisson.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/path_generation.R
\name{bm_compound_poisson}
\alias{bm_compound_poisson}
\title{Generates a (correlated) Brownian motion path with
correlated but unsynchronised Gaussian jumps.}
\usage{
bm_compound_poisson(
n,
sigma,
jump_sigma,
n_jum... |
526a43f9cc504f4d11e0f7ec818c2abc914d4def | 3d07946ba8756030d99e4afcf2ec79023d6451d6 | /drawNodeSupportSymbol.r | 88ee1f76a6715cf3d8af7e16157f86a736e27d9a | [] | no_license | samuelcrane/draw-node-support-symbol | a33f843ec02505250a7a4256540daa506a9e2e3f | 4dcd86b69468900665caa90a3ec7361c4aef6a05 | refs/heads/master | 2020-05-19T22:03:16.371586 | 2013-06-26T17:06:06 | 2013-06-26T17:06:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,287 | r | drawNodeSupportSymbol.r | ## This R script draws filled circles on the nodes of a phylogeny corresponding to the bootstrap
## support values. It has been adapted from the excellent book, "Analysis of Phylogenetics and
## Evolution with R" by Emmanuel Paradis.
## To handle posterior probablities from a MrBayes consensus file, either change the... |
22d578be0775bf1243a84703f4b21c01ffd487cb | f05ce58140ec9316e2449cda141d3df089fdd363 | /src/main/java/time_series/m4.6/m4.6.data.R | 5ba4bd046ab5b44b988c539cd3325f34480ed111 | [] | no_license | zhekunz2/Stan2IRTranslator | e50448745642215c5803d7a1e000ca1f7b10e80c | 5e710a3589e30981568b3dde8ed6cd90556bb8bd | refs/heads/master | 2021-08-05T16:55:24.818560 | 2019-12-03T17:41:51 | 2019-12-03T17:41:51 | 225,680,232 | 0 | 0 | null | 2020-10-13T17:56:36 | 2019-12-03T17:39:38 | Java | UTF-8 | R | false | false | 35,769 | r | m4.6.data.R | n <- 544
height <-
c(151.765, 139.7, 136.525, 156.845, 145.415, 163.83, 149.225, 168.91, 147.955, 165.1, 154.305,
151.13, 144.78, 149.9, 150.495, 163.195, 157.48, 143.9418, 121.92, 105.41, 86.36, 161.29, 156.21, 129.54,
109.22, 146.4, 148.59, 147.32, 137.16, 125.73, 114.3, 147.955, 161.925, 146.05, 146.05, 152.7048, 1... |
1a08226d520b1c7160d205a76c4e50b292703b2c | 1d3c33bfd5fb2d08b91ea2fda0ae178fe2f94919 | /fakeWeblogGenerator.R | 79a7fcf33c1b723371326d8ce069b835dcf03c9c | [] | no_license | jkebinger/drillable-stacked-time-series | dc3b35d25055bb92892d823402f85f622f358e82 | 77645d9e22b2cdb4a299e182dbc65f54700a0226 | refs/heads/master | 2021-01-21T07:39:47.447951 | 2010-01-17T23:49:01 | 2010-01-17T23:49:01 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 942 | r | fakeWeblogGenerator.R | generateGrowingSequence = function(initialValue,length) {
randomSequence = rlnorm(length-1,0.15,1/6);
growingSequence = c(initialValue);
for (i in 2:length)
{
growingSequence = append(growingSequence,randomSequence[i-1] * growingSequence[i-1]);
}
return(growingSequence);
}
generateFakeWeblog = function... |
716a2df323e30f561606b215436fb6eaa2016e0a | 4201e9b754760dc35fc0aeef9df5a8b9d801c47f | /bin/R-3.5.1/src/library/base/man/environment.Rd | 6bffe932a732d6ac200ec798eb541a537188852e | [
"GPL-1.0-or-later",
"GPL-2.0-or-later",
"GPL-2.0-only",
"LGPL-2.1-only",
"LGPL-3.0-only",
"GPL-3.0-only",
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | 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 | 6,121 | rd | environment.Rd | % File src/library/base/man/environment.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2012 R Core Team
% Distributed under GPL 2 or later
\name{environment}
\alias{environment}
\alias{environment<-}
\alias{.GlobalEnv}
\alias{globalenv}
\alias{emptyenv}
\alias{baseenv}
\alias{is.environment}
\a... |
274a92d111bb751d25fa0a29fcf4f6a660ece56d | 45dfbdeaeaa213f373ac41a492e2ec71553f1540 | /ui.R | da7b025c8a10deb76f913e2370bd8f4342060382 | [] | no_license | AnaLira/WineQualityApp | 71fef132d3b8a9bffb7ccced258fc67975c970b8 | 64f43d18057f694cdfeb6aaad98ea368dd241fab | refs/heads/master | 2016-09-01T13:21:28.933936 | 2015-09-24T22:28:15 | 2015-09-24T22:28:15 | 43,170,844 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,476 | r | ui.R | library(shiny)
#
shinyUI(fluidPage(
# Application title
headerPanel("Assignment - Wine Quality Modeling"),
# Sidebar with to collect input variables:
# One radio button list to indicate the type of output the users wants
# One checkbox list to indicate which variables from the data set are going to be... |
c648e4f8bd2245d5a955b83a92666fee51ecb32e | de9468da30d02ade3b7a600fa096dd50e12fb3d8 | /3 Getting and cleaning data/Week 3/SolQuizz3.R | 48438d4b4a4b9aef6d0591ab2d5e4fd89a0b0b1a | [] | no_license | MariaBravo/DataScienceSpecialization01 | 0bb9d39bd71e0f1215895811191923225d7701a8 | e727c681225a99fafeb48914251b22590348c367 | refs/heads/master | 2021-01-10T16:17:25.586351 | 2015-11-13T10:06:29 | 2015-11-13T10:06:29 | 46,025,439 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,486 | r | SolQuizz3.R |
## Question 1
##***********************
ACR 1
Lot size
b .N/A (GQ/not a one-family house or mobile home)
1 .House on less than one acre
2 .House on one to less than ten acres
3 .House on ten or more acres
AGS 1
Sales of Agriculture Products
b .N/A (less than 1 acre/GQ/vacant/
.2 or more units in structur... |
ece44e53818e1c4937393f0f2ba47f608cf4482d | 753e3ba2b9c0cf41ed6fc6fb1c6d583af7b017ed | /service/paws.ssm/man/get_patch_baseline.Rd | d8d2cc530d4a9d95b4b4d1bff96c9c4c4b876133 | [
"Apache-2.0"
] | permissive | CR-Mercado/paws | 9b3902370f752fe84d818c1cda9f4344d9e06a48 | cabc7c3ab02a7a75fe1ac91f6fa256ce13d14983 | refs/heads/master | 2020-04-24T06:52:44.839393 | 2019-02-17T18:18:20 | 2019-02-17T18:18:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 491 | rd | get_patch_baseline.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.ssm_operations.R
\name{get_patch_baseline}
\alias{get_patch_baseline}
\title{Retrieves information about a patch baseline}
\usage{
get_patch_baseline(BaselineId)
}
\arguments{
\item{BaselineId}{[required] The ID of the patch baseline to ... |
8f6b6278883abd331fba539b8b8ef41581e07704 | 85bd593fc4603e99bbb6e8e097960ab832a469d3 | /man/cartesian.Rd | 9b13e8996478528bc280a5197633787dba551f55 | [] | no_license | cran/GeodesiCL | 2dab609c79d45ceba619cf478ad5f5382c1d7667 | 09c72a0c6deefe2b168024406087c2fcf8ae34b3 | refs/heads/master | 2023-04-25T15:26:14.862721 | 2021-05-25T11:20:02 | 2021-05-25T11:20:02 | 370,748,265 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,467 | rd | cartesian.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Cartesian.R
\name{cartesian}
\alias{cartesian}
\title{To convert from Geographic coordinate to Cartesian coordinate.}
\usage{
cartesian(a, longlat_df, digits = 4)
}
\arguments{
\item{a}{Selection of Ellipsoid.}
\item{longlat_df}{Point name, ... |
fafb4a5298b6a7bfe9014caddf7bcc8617812457 | 0d658054756f19a535a5ea48382437f071656882 | /plot3.R | 6334648137b0913fe91c7a11affcf8b37833b268 | [] | no_license | visheshtayal/ExploratoryDataAnalysis1 | b8eb87852e41e448d654f875a48c9e17844f7bdf | 23bd0400143e2efe95626fa6b77ab1acc30ac6ce | refs/heads/master | 2022-12-12T03:51:43.391429 | 2020-09-05T19:49:52 | 2020-09-05T19:49:52 | 292,792,856 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 500 | r | plot3.R | library(lubridate)
library(data.table)
DT<-data.table::fread("household_power_consumption.txt",na.strings = "?")
DT[, dateTime := as.POSIXct(paste(Date, Time), format = "%d/%m/%Y %H:%M:%S")]
DT <-DT[(dateTime >= "2007-02-01") & (dateTime < "2007-02-03")]
png("plot3.png",height=480,width=480)
plot(DT[, dateTime],DT[, Su... |
9021b611ad4190ba052287220942b5af6ff21839 | 87f61a31940ea636e2330909b72c0658496eac0d | /plot1.R | 4b32b8c6aee705bae80fcca30c440e0c2210a912 | [] | no_license | Vcub38/ExData_Plotting1 | e4bc1ed4f9ba4c62b6cd389f54ff5bc517a5151a | d21dabc50c7cc9bcdfbd2548e1decb3f69527118 | refs/heads/master | 2020-03-28T17:37:15.897885 | 2018-09-14T16:17:23 | 2018-09-14T16:17:23 | 148,807,983 | 0 | 0 | null | 2018-09-14T15:28:53 | 2018-09-14T15:28:53 | null | UTF-8 | R | false | false | 970 | r | plot1.R | ## set working directory to be the folder containing the raw data file, "household_power_consumption.txt"
## read data into R
data <- read.table("household_power_consumption.txt", sep = ";", header = TRUE, na.strings = c("?"))
## subset data to only include data from February 1, 2007 and February 2, 2007
sdata <- subs... |
3ee278c64f2a7b87bc2e8bda3cac34faa9656f05 | ee81f0c7496bf294ebc89046a85bf8e5b3b28ff4 | /man/plotCyclopsSimulationFit.Rd | 740d851554d4419779485cd09a2645cba171aead | [
"Zlib",
"Apache-2.0"
] | permissive | OHDSI/Cyclops | 34f5bf493fb89de9bb34970016c2089611fddb33 | c7710e1cda715470c1f8476aeda21221d9b529a2 | refs/heads/main | 2023-08-04T22:33:15.297098 | 2023-04-14T20:32:38 | 2023-04-14T20:32:38 | 16,480,696 | 36 | 36 | null | 2023-05-31T21:01:22 | 2014-02-03T13:50:33 | C++ | UTF-8 | R | false | true | 623 | rd | plotCyclopsSimulationFit.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Simulation.R
\name{plotCyclopsSimulationFit}
\alias{plotCyclopsSimulationFit}
\title{Plot Cyclops simulation model fit}
\usage{
plotCyclopsSimulationFit(fit, goldStandard, label)
}
\arguments{
\item{fit}{A Cyclops simulation fit generated by ... |
0f4f507632bb161920452d72e61b638eb1f5343d | b136b4bfef2449633275481a5aa62c60e32f07bd | /R/bolshev.rec.vec.R | 79e26429e1fada6c76c01def6d6ebdf53ec2dd00 | [] | no_license | cran/MHTcop | cba5339e5c2875ee8d9dfc318aeb132c8e89dcae | 496ee271b9e68adff69523e19dee05c469678ee4 | refs/heads/master | 2020-03-08T17:36:15.334807 | 2019-01-21T15:10:03 | 2019-01-21T15:10:03 | 128,273,287 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,658 | r | bolshev.rec.vec.R | #' Distribution function of the order statistics of i.i.d. uniform random variables
#'
#' \code{bolshev.rec.vec} is a vectorized and unrolled implementation of the Bolshev recursion described in Shorack, Wellner (1986)
#' which can be utilized to calculate probabilities for order statistics of i.i.d. uniform random ... |
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