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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
58d62f4f08719380b291c661e9b29987d7afdef3 | f8495690bcd97ccbde1e8fe4e43d2b00a90ff7cb | /reddit_survey.R | a7c0f57fe501286e9c6cfa9fa030211df1558614 | [] | no_license | BarnetteME1/Learning_R | de221661716d7e50d126be5ced06287a68132308 | 1a0671aa0b05ba4c4a20e75c7a94ecb62168ba19 | refs/heads/master | 2016-09-01T08:22:10.342651 | 2016-04-03T19:25:36 | 2016-04-03T19:25:36 | 53,447,850 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 638 | r | reddit_survey.R | setwd('~/R')
reddit <- read.csv('reddit.csv')
str(reddit)
dim(reddit)
table(reddit$employment.status)
summary(reddit)
levels(reddit$age.range)
library(ggplot2)
qplot(data = reddit, x = age.range)
levels(reddit$age.range) <- c('Under 18', '18-25', '35-44', '45-54', '55-64',
'65 or Above'... |
efdfe083e3fad546024d724f8e60c9d53911ed2c | 3050675a24f529b8e795bdc81bd84149c0b41476 | /files/install-packages.R | c71644220937d8d3f4b1a06f7129598a44585e2b | [
"CC-BY-4.0"
] | permissive | coadunate/ansible-role-qiime | 5d36b44398a1f4b730afbbe7bae987b0cc9cb648 | 816bf57ca2741332fccc2938ff72d37cd7bc72c3 | refs/heads/master | 2021-01-23T05:39:04.257400 | 2018-01-25T21:16:53 | 2018-01-25T21:16:53 | 92,977,491 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 212 | r | install-packages.R | install.packages(c('ape', 'biom', 'optparse', 'RColorBrewer', 'randomForest', 'vegan'), repos = "http://cran.us.r-project.org")
source('http://bioconductor.org/biocLite.R')
biocLite(c('DESeq2', 'metagenomeSeq'))
|
b5a2d723a855ac35c1cae5df2076886c8a47df2e | 0169e2d76b415c5ce11d290ff543f37fd9fec70f | /SMBKC/code/map_new.R | 61a98856a0a8a789a1c5da4bcfd0bb65ef847e68 | [] | no_license | commfish/BSAI_crab_assessments | 91765b2aeb96cdb3861e614c9fc1dbf811d77f5c | 4ed906b77c25ba6c1bc38c1586f91115693fbf28 | refs/heads/master | 2023-08-17T03:16:13.808993 | 2023-08-16T01:06:06 | 2023-08-16T01:06:06 | 197,654,608 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,786 | r | map_new.R | # katie.palof@alaska.gov 9-5-19 / 4-22-22/ 8-25-22
# map creation for SMBKC trawl survey samples from recent years
# WIP
# https://geocompr.robinlovelace.net/adv-map.html
# load -------
library(PBSmapping)
library(tidyverse)
library(mapproj)
data("nepacLLhigh")
cur_yr = "2022"
folder = "smbkc_22f"
### data ---... |
981105ac7b7e7db913e27e7821b6b473750f9f29 | eda7552fae1cbb9a51050484b90f6ffeb5fc670a | /scripts/alluvial_plots_v3.R | fe3688a30e726ed7c6150c80dcf385ac9506ecb1 | [] | no_license | mcjmigdal/ConnectOR | d5c70cdaebf9c70d68e046997f9d3cdcaa953119 | 78671742f0e187ff538183cc6a2663058a8787ec | refs/heads/master | 2022-11-21T03:34:17.625976 | 2020-03-26T12:08:26 | 2020-03-26T12:08:26 | 278,582,987 | 0 | 0 | null | 2020-07-10T08:39:12 | 2020-07-10T08:39:11 | null | UTF-8 | R | false | false | 4,026 | r | alluvial_plots_v3.R | library(dplyr)
library(ggplot2)
library(ggrepel)
library(ggalluvial)
library(grid)
library(ggplotify)
library(colorspace)
library(gridExtra)
#library(ggpubr)
#Packages for synteny plots
#install.packages("devtools")
#devtools::install_github("kassambara/ggpubr")
#install.packages("RIdeogram")
#install.packages("rsvg")... |
e2faf44e4d5efb1eb682636d276ed6d1a47f154f | 850898c179e63adf03e07ec066046e3eba524aee | /reduce_colors/reduce_image_colors.R | ea0d597290699b5a60cc67257be425ac2174d35c | [
"MIT"
] | permissive | zettsu-t/cPlusPlusFriend | c658810a7392b71bbcd0fbf6e73fa106e227c0d0 | 8eefb1c18e1b57b1b7ca906027f08500f9fbefcc | refs/heads/master | 2023-08-28T09:29:02.669194 | 2023-08-27T04:43:24 | 2023-08-27T04:43:24 | 81,944,943 | 10 | 1 | null | null | null | null | UTF-8 | R | false | false | 16,206 | r | reduce_image_colors.R | ## Reduce the number of colors in an image
##
## How to launch
## from command line (note that --args is required):
## Rscript reduce_image_colors.R --args -i dir/input.png -o outdir -t text-on-images
## on Rstudio:
## arg_set <- c('-i', 'dir/input.png', '-o', 'outdir', '-t', 'text-on-images')
## ... |
847e06ec0681f93b9dd841a0ab36b40c12552319 | 29792357241afdd2d527c5f17c990f78e5e3e69f | /plot2.R | 010524dadc68df80fde886b449940ed826ea3b2a | [] | no_license | wanggith/ExData_Plotting1 | c535e2a68b1d0586a385208f26591de270d9113c | 71e8be1492365750ad01c39f48579e986140002e | refs/heads/master | 2021-01-15T05:45:47.488619 | 2016-01-10T22:09:11 | 2016-01-10T22:09:11 | 49,376,982 | 0 | 0 | null | 2016-01-10T17:20:40 | 2016-01-10T17:20:40 | null | UTF-8 | R | false | false | 545 | r | plot2.R | data <- read.table("./household_power_consumption.txt", header=TRUE, sep=";", colClasses=c("character", "character", rep("numeric",7)), na="?")
data_sub <- data[data$Date %in% c("1/2/2007","2/2/2007"), ]
datetime <- strptime(paste(data_sub$Date, data_sub$Time, sep=" "), "%d/%m/%Y %H:%M:%S")
global_active_power <- data_... |
5510b5dc5ec737b3b6026faabc0242c2877b1dbe | 98a0bd2de4836b813642df0faf5f0b5bd31f7617 | /man/starInstallation.Rd | d364911e365219310240aaac940c640ade275ee7 | [] | no_license | inambioinfo/chimera | 7bf3834f72464e546b83f52704354acbc9c329bc | 17e0580ccd842a57f519fd968bc9df3d9ec29a0f | refs/heads/master | 2021-06-25T06:56:13.520654 | 2017-04-24T19:50:57 | 2017-04-24T19:50:57 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 617 | rd | starInstallation.Rd | \name{starInstallation}
\alias{starInstallation}
\title{A function to download STAR}
\description{A function allowing the download and installation of STAR (Dobin et al. Bioinformatics 2012) in chimera package folder. The function also creates soft links in the user bin folder to allow the call of the above mentioned p... |
ed234de3fee0d3dfe8ed52a667c0f46c601c84c5 | 266efa63779ac8ad5dbada8943fe1d6de8cb0cfe | /Shiny.R | ede887ffad2609fc8fbe6bec5208f4323927eda8 | [
"MIT"
] | permissive | evocativebloom8/m14-shiny | 1420d38a2621ae1d0e4e98f199ec7afa5adb2541 | 422888fd6d3939136e438d35a84688f022fb68dc | refs/heads/master | 2020-07-27T19:51:06.644558 | 2016-11-16T04:20:00 | 2016-11-16T04:20:00 | 73,426,443 | 0 | 0 | null | 2016-11-10T22:33:54 | 2016-11-10T22:33:54 | null | UTF-8 | R | false | false | 467 | r | Shiny.R | library(shiny)
# Define UI for an application that has a title
shinyUI(
# Specify a fluidPage layout (most common)
fluidPage(
# Create a title in your fluidPage
titlePanel("Hello Shiny!")
)
)
# server.R
library(shiny)
shinyServer(function(input, output) {
# Create a histogram property of the ou... |
51178beb0292e194eae1d7fa5b54e2ef22fcad2c | c6fca8eec6da3dc340ab6dd8b471d02c45acf022 | /power_expansions.R | 568c0c59329b4b5fe54d969467595e2dea991a3c | [] | no_license | lhf28/Signals-from-the-past | 7d40a78e440c10146a4bde49c8a54707eeebb430 | 3c848334c96f00b238e0a00c0de0b6cb15257393 | refs/heads/main | 2023-06-19T04:24:38.491875 | 2021-07-21T13:17:00 | 2021-07-21T13:17:00 | 368,926,139 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,413 | r | power_expansions.R | ########################################################### SETUP ##################################################################
setwd("~/Desktop/DissertationR")
library(coala)
activate_msms(jar = "~/Desktop/DissertationR/msms/lib/msms.jar", priority = 500, download = FALSE)
list_simulators()
###################... |
d465eaadea2b47178e940a48f94f174e52104f69 | c8b9dd433edc3ae10dfea91ec7e3c50123085ca5 | /app.R | 80514324fb3f46c46adf0cda06f1a019abfa50b9 | [] | no_license | brunocosta88/EvolucaoBandaLargaBrasil_2007-2020 | 06e21b7d2ff38f324cf967001878b928d8bce317 | f5793967383e84af0db2b78c0983ca717f19a170 | refs/heads/master | 2023-01-22T04:47:03.667380 | 2020-12-03T23:02:02 | 2020-12-03T23:02:02 | 318,315,411 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 16,248 | r | app.R | # More info:
# https://github.com/jcheng5/googleCharts
# Install:
# devtools::install_github("jcheng5/googleCharts")
library(googleCharts)
library(shiny)
library(dplyr)
url <- "https://github.com/brunocosta88/EvolucaoBandaLargaBrasil_2007-2020/raw/master/acessosBandaLarga.rds"
destfile <- "./temp.rds"
download.fil... |
5b6e2cfb78d049c7eca07f0ca13c10b5bf93c580 | 2d34708b03cdf802018f17d0ba150df6772b6897 | /googleadmindirectoryv1.auto/man/directory.customers.update.Rd | 86af9ff4d0a6f1d986d441a5f5ac3277835b8911 | [
"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 | 1,016 | rd | directory.customers.update.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/admin_functions.R
\name{directory.customers.update}
\alias{directory.customers.update}
\title{Updates a customer.}
\usage{
directory.customers.update(Customer, customerKey)
}
\arguments{
\item{Customer}{The \link{Customer} object to pass to t... |
13188b7c97b45b22bae21e306799b05e38d479ea | 7a7d01f06ec8ddf5dabab431ecef063955353ae1 | /misc/future_topics.R | 7bc05c6a67dedec470244871b16d7a04674dff87 | [] | no_license | rsoren/r_training_beira2017 | 314c190787821942e53e380b4d5521196f3eaa8b | 6e51e32c2ac3e07e24afcbcec5821a46a960b3ac | refs/heads/master | 2021-01-01T04:16:17.877155 | 2017-07-28T11:48:36 | 2017-07-28T11:48:36 | 97,157,463 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,148 | r | future_topics.R | #
# future_topics.R
#
# Reed Sorensen
# July 2017
#
# LISTS
# list, as.list
# str
# index by [], [[]] and $
# -- Challenge:
# 1. Create a list called 'my_list' that contains
# an element with 1, 2, 3 and another element with "a", "b", "c"
# 2. Have R give you the contents of the second eleme... |
919dcd6cd94da91f8d0b0e27f683a5e100727f7e | fcdbdb4dcbde7d0c37cca433de2ea317214ea6ae | /man/ZIPPCApn.Rd | a6cc2cd4c219638e0158b162c462832e580ec8dc | [] | no_license | YanyZeng/mbDenoise | c0566ca038ef2ad6eda8948e3f50370d3934b614 | 3200490f601b2b24898914d90fdbea503780d818 | refs/heads/main | 2022-07-27T13:55:55.308756 | 2021-09-26T10:47:25 | 2021-09-26T10:47:25 | 380,777,633 | 5 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,963 | rd | ZIPPCApn.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ZIPPCApn.R
\name{ZIPPCApn}
\alias{ZIPPCApn}
\title{ZIPPCApn}
\usage{
ZIPPCApn(
X,
V = NULL,
family = "negative.binomial",
n.factors = 2,
rank = FALSE,
trace = FALSE,
maxit = 100,
parallel = TRUE
)
}
\arguments{
\item{X}{matrix... |
b2f3e9f83cb0c9423cc0356c7e9200740a1cb081 | 39f8eec5c6c7210208675f48835d0a2254947fd5 | /man/MDScols.Rd | 4a7d725fee32b17c6e543cf6d36cd9532603abc7 | [
"MIT"
] | permissive | peterjuv/myHelpers | 5b4586433ae729f8e8b816b00b74841cbeb26d8e | cf976325abad166158428c89b4521149440580df | refs/heads/master | 2023-05-23T04:08:40.473975 | 2021-06-10T08:04:52 | 2021-06-10T08:04:52 | 292,005,498 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,353 | rd | MDScols.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/myHelpers.R
\name{MDScols}
\alias{MDScols}
\alias{MASS_MDScols}
\alias{plotIsoMDS}
\title{MDS by columns and optional plot using Minkowski metrics}
\usage{
MDScols(
data,
scale = FALSE,
center = FALSE,
FUN = "isoMDS",
p = 2,
selec... |
fa90387fab4d7c1b105062f029256473b0c5dfa7 | da5d0b3125b53246b84ef8f6250db0f932d74eb8 | /DataScience/Rscripts/d0315_Ex.R | 0d972bfea1da41263ee5f0b92cf1300c4812b3a4 | [] | no_license | HyeonGyuChi/2019_1st_Semester | fd373496a4970fdb5566fb33f48b28facad9a377 | 4d7bcf575634088110ade43951a49752ca3475f6 | refs/heads/master | 2020-05-07T17:36:32.285358 | 2020-03-19T13:33:28 | 2020-03-19T13:33:28 | 180,732,477 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,376 | r | d0315_Ex.R | #연습문제(2) == 실습 #2.배열연습
#20155342 지현규
# 3) @@@ 연습문제(2) 해결 @@@
#1) 짝수,홀수처리
# 1-10사이의 홀수 짝수벡터 생성
(odd = seq(1,10,2))
(even = seq(2,10,2))
# odd와 even벡터 결합
(total = c(odd, even) )
# sorting
(stotal = sort(total))
# stotal 벡터에서 짝수의 제외
(newEven = setdiff(stotal, even))
#2) 5명의 BMI처리
height = c(1.6,1.7,1.8,1.76,... |
8c0fd7e7b9cb42e5f9792bdd8267bf25eb885fe9 | 6c6334d3d716da34aae8079f7f673c2324ddf480 | /tests/testthat/test-function-info_to_text.R | 31608c553f3c92ee07c750bc56ccadb594a55108 | [
"MIT"
] | permissive | KWB-R/kwb.code | 94f80f51b2977cd0c0fda094f3c7796e1cea95cf | bc81324403e3881124fa2230c023807eba26e32d | refs/heads/master | 2023-08-17T07:40:18.766253 | 2023-07-15T05:50:50 | 2023-07-15T05:50:50 | 140,209,624 | 0 | 0 | MIT | 2023-08-06T22:33:32 | 2018-07-08T23:23:47 | R | UTF-8 | R | false | false | 394 | r | test-function-info_to_text.R | #
# This test file has been generated by kwb.test::create_test_files()
# launched by user hauke on 2021-11-27 17:51:46.
# Your are strongly encouraged to modify the dummy functions
# so that real cases are tested. You should then delete this comment.
#
test_that("info_to_text() works", {
expect_error(
kwb.code:... |
5d203b1bc49ceabda8cf9f58bf67eea5cdaaf47c | e8d3a7368b14680795236b836b97b63488b68544 | /terraform/provisioners/libraries.R | a8ce3df7e34bf6ac8b863de45355d6c7ecb18ee2 | [
"MIT",
"Apache-2.0"
] | permissive | Quantanalyst/insight_newvision_ci_pipeline | de1bf4f12ef9f155008470751cb334765eedb0c1 | 92b4adddfe62c4c37cc4e30bd695c67b835dbebc | refs/heads/master | 2022-11-19T22:02:17.882518 | 2020-07-06T20:54:06 | 2020-07-06T20:54:06 | 268,702,076 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 443 | r | libraries.R | # install additional R libraries
# install.packages('testthat')
# install.packages("RJDBC")
if(!"RJDBC" %in% installed.packages()) install.packages("RJDBC")
# if(!"dplyr" %in% installed.packages()) install.packages("dplyr")
# if(!"reshape2" %in% installed.packages()) install.packages("reshape2")
if(!"data.table" %in% i... |
e7cc0bd1d4915451bcaa0c926f8485f545b6568a | aa9735132f52b22bc6768ef7bec8e5e034a85b47 | /R/plotDirectClass.R | 1a4c88ff713429532d4c275c73f26382828599da | [] | no_license | cran/SPreFuGED | 6e8ed93276cc96c878b0e8535cf687ee17aad2f3 | a0146399644093188b3e62fbc53dff3ae6693dc1 | refs/heads/master | 2021-01-09T20:41:09.447515 | 2016-07-29T12:35:58 | 2016-07-29T12:35:58 | 64,473,076 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 761 | r | plotDirectClass.R | plotDirectClass<-function(restDirectClass){
classFxn<-rep(colnames(restDirectClass), each=dim(restDirectClass)[1])
acc<-c(restDirectClass[,1], restDirectClass[,2], restDirectClass[,3], restDirectClass[,4], restDirectClass[,5],
restDirectClass[,6], restDirectClass[,7], restDirectClass[,8], restDirectClas... |
18a89b570a4f3618309dad0d7043cf2bd84e1037 | 342edb52f539db557b03a36dd1163a755f2c2d81 | /Linear_Regression/AssignmentOne.R | f5bef1e6fa7d9e8f59fc009a9e043f9fe8a0dc0b | [] | no_license | Akmystery/Data_Science_R | 0ef90dd79c6d5fc6380dd8c9fb6d9253c43d6090 | 34ad0662e1c607bc3c3838553d912541dce07c58 | refs/heads/master | 2020-07-06T17:37:31.847012 | 2019-08-19T03:43:21 | 2019-08-19T03:43:21 | 203,092,682 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,083 | r | AssignmentOne.R | energyData <- read.csv("assign1_EnergyData.csv", header = TRUE)
str(energyData)
dim(energyData)
names(energyData)
head(energyData)
tail(energyData)
summary(energyData)
#histogram
hist(energyData$Compactness,col = 'lightgreen') #numeric
hist(energyData$SurfaceArea,col = 'lightgreen') #numeric
hist(energyData$Wa... |
f5dd256ad08a083cec99f7b3028d81de00ca4df2 | 3acc2f91e116ea0e5ea148dd1711e71b4d8d2c22 | /man/InteractionHelpers.Rd | 2b93d8f99953f789828811a63833a317c3dc3a44 | [] | no_license | LTLA/fugi | ecceeb4f0d2cd8f122481283549396f1ba554587 | d2f33b7d9c8deb468effc5d2fbe6b757837a7c93 | refs/heads/master | 2020-05-15T15:08:55.334600 | 2019-06-22T18:45:35 | 2019-06-22T18:45:35 | 182,362,581 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,344 | rd | InteractionHelpers.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AllGenerics.R, R/helpers.R
\docType{methods}
\name{is.pp}
\alias{is.pp}
\alias{is.pd}
\alias{is.pt}
\alias{is.dd}
\alias{is.dt}
\alias{is.tt}
\alias{isInteractionType}
\alias{is.trans}
\alias{is.cis}
\alias{InteractionHelpers}
\alias{is.pp,Ge... |
427332b6500584525012edc104aa8cee19c3adf0 | 1a47d66ed545c8d93953eb932d51d90c9cbf26a8 | /R/99_country_list.R | 2eeaf741791de03a2797f0d46aaf185514de6cba | [] | no_license | agbarnett/pollies | b8a731832d4bbe30abd8bf94895f0ba572f84d1b | 325d272c41e17b8f8084946511dd03c02d29b2bc | refs/heads/master | 2022-05-01T13:02:49.965562 | 2022-03-20T01:38:47 | 2022-03-20T01:38:47 | 189,006,425 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 586 | r | 99_country_list.R | # 99_country_list.R
# simple list of countries called by other programs
# April 2021
## dropped Japan in December 2019
# all countries:
countries = c('Austria','Australia','Canada','Italy','France','Germany','Netherlands','NZ','Switzerland','UK','USA')
# countries with imputed life table data
countries.imputed... |
441c1ab07b1eccf1d9f0b875ead87548d9bdad87 | 9b1127c1fa497e344018a603cde732980d0cc725 | /best.R | 7ff62befba0ad30367353abc7a790116c8427435 | [] | no_license | jbluesmith/ProgrammingAssignment3 | 5a3db4f5b1756bdc05904223879d4135b5a9e937 | 6f9a1237501fbcf4f10fcef6d475db43cb81c82f | refs/heads/master | 2016-09-10T21:27:29.508940 | 2015-03-02T17:31:15 | 2015-03-02T17:31:15 | 31,553,104 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,711 | r | best.R | best<- function(state, outcome) {
data <- read.csv("outcome-of-care-measures.csv", colClasses = "character")
states <- sapply(data[,7], as.character)
if (!state%in%states) {
stop("invalid state")
}
if (outcome=="heart attack") {
outcomes <- sapply(data[,11], ... |
a41a6251b633db009fd0f703c702b558c854fa49 | edc63123efa668eb1c0b6aab769c26d9ea59210d | /man/make_deseq.Rd | 2dd44066ddcb19695512cce21d8964a7fd23c326 | [] | no_license | seedpcseed/phylodeseqr | 3637463608675335fe93ef71745d1050fe9ffc52 | 89fe1981b06ace25adcbfbdc361674c7deb79846 | refs/heads/master | 2020-09-19T21:19:23.067925 | 2016-08-22T21:05:55 | 2016-08-22T21:05:55 | 66,208,384 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 717 | rd | make_deseq.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/make_deseq.R
\name{make_deseq}
\alias{make_deseq}
\title{Make a DESeq S4 object using a user design and a phyloseq S4 object
@param phy A phyloseq S4 object
@param design A string
@param design2 A string
@return A DESeq S4 object
@expo... |
9e1726c2a51fc162d07ebe17074e0c019a7dc00f | acfcc96992e838be8baab6fe3fc848165c21ad96 | /plot4.R | e310b623363c87788b99b2aab3f8bc780190b2b5 | [] | no_license | Nagateja/ExData_Plotting1 | 9fc9d1e10386f7b12463f59675aed17eb142e8ec | 41a761bad847ce85c694defbb3e7a7b88a6dc80d | refs/heads/master | 2021-01-17T23:38:21.856115 | 2015-12-11T21:39:36 | 2015-12-11T21:39:36 | 47,843,881 | 0 | 0 | null | 2015-12-11T18:24:35 | 2015-12-11T18:24:35 | null | UTF-8 | R | false | false | 1,664 | r | plot4.R | ##This program creates a plot which is names plot4.png
##Reading the data in using read.table
eda1<-read.table("exdata-data-household_power_consumption/household_power_consumption.txt", sep=";", na.strings = "NA", header = TRUE, stringsAsFactors = FALSE)
##Subsetting required data
reqdata<-subset(eda1, Date %in% c("1... |
b9c6ff17d0d682897455bd8851849e9363c13cd8 | 9c56e4ef9d59492e76f2f8d2b3516733852e5237 | /tests/testthat/test-calculate_complexities.R | 3e2f87a737524152598a9445b998e87ef11ac2c1 | [
"MIT"
] | permissive | openplantpathology/hagis | e12029b5dbec2b379196e1995d65076685551087 | 1f9e8d17bb6e33865da8e13e735e54c0214c9c9f | refs/heads/main | 2023-08-30T19:36:54.325248 | 2023-06-06T10:08:12 | 2023-06-06T10:08:12 | 164,751,172 | 4 | 2 | NOASSERTION | 2023-06-06T10:08:14 | 2019-01-08T23:38:30 | R | UTF-8 | R | false | false | 4,074 | r | test-calculate_complexities.R |
# test calculate complexities --------------------------------------------------
data(P_sojae_survey)
complexities <- calculate_complexities(
x = P_sojae_survey,
cutoff = 60,
control = "susceptible",
sample = "Isolate",
gene = "Rps",
perc_susc = "perc.susc"
)
test_that("calculate_complexities() works prop... |
a71579a3ba4630aa3d3891ca52ff717618f9d237 | cd8408d90328e53c6a8d7b21521e5a29e1d1d889 | /shinyapp/global.R | 0856e8d6da3eeb6fc431be6ca256e3ffba6c5944 | [] | no_license | amerus/BenchmarkingTensorflow | 8e46d740be872625706fc48104cab4aa0dcc5d29 | addda049aa44cb5bee7d217136a4fc543f619dd6 | refs/heads/master | 2020-05-09T14:41:17.463744 | 2019-05-10T20:31:01 | 2019-05-10T20:31:01 | 181,203,770 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 816 | r | global.R | library(shinydashboard)
library(tidyverse)
library(ggplot2)
library(DT)
library(naturalsort)
library(codeModules)
# load saved metrics from RDS files
ALL <- readRDS('./data/ALL.RDS')
# slider controls for seconds
sliderSeconds <- as.data.frame(ALL) %>%
select(seconds) %>%
unique() %>%
unlist() %>%
as.numeric... |
e2021194cec30d09a87570c0c66899da1ba40068 | 6fc1a75f0017bf73598075164a4a2c0bbfc2c521 | /man/argument.Rd | 232ccb3c98cfb48beaa71f373124282336a40383 | [] | no_license | nsgrantham/scriptr-deprecated | 88a3e1bab25d99de33a1166984dbaad90e201ad3 | 7d9b42e12c85b8d81911c2b45f00b3cb2dd4ea44 | refs/heads/master | 2021-09-07T08:25:05.211619 | 2018-02-20T06:40:17 | 2018-02-20T06:40:17 | 103,743,481 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 479 | rd | argument.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/scriptr.R
\name{argument}
\alias{argument}
\title{Argument}
\usage{
argument(scp, name, type = NULL, nargs = 1, help = "")
}
\arguments{
\item{scp}{Script object}
\item{name}{Name of argument}
\item{type}{String of data type, scriptr::inter... |
405728ee01d796eeec0b98c1956537fe2be8d23a | 3165136f79bb0154b8af62dc71a112ffc80ae787 | /funs/ub.wn.ign.R | 6474f4ae3a7e7a035d0d3e909a7813b0c68a91be | [] | no_license | yuliasidi/wilson_newcombe | 0dce8043477417799fe098f1a99645fb12f5e9d0 | 0b9b065bdb01b35f48088df787d0e3b6a15bda02 | refs/heads/master | 2021-06-23T00:14:48.715457 | 2019-10-21T01:28:03 | 2019-10-21T01:28:03 | 192,383,341 | 0 | 0 | null | 2019-10-21T01:28:05 | 2019-06-17T16:37:50 | R | UTF-8 | R | false | false | 255 | r | ub.wn.ign.R | ub.wn.ign <- function(z, qhat, nobs, rn){
(2*qhat + z^2/nobs + z^2*rn/nobs)/(2*(1 + z^2/nobs + z^2*rn/nobs)) +
sqrt(
(2*qhat + z^2/nobs + z^2*rn/nobs)^2/(2*(1 + z^2/nobs + z^2*rn/nobs))^2 -
qhat^2/(1 + z^2/nobs + z^2*rn/nobs)
)
}
|
11c195c9380abdf7350542c0cd719c635772eaa4 | db2cc56460b8054e4ade9b0b618cb3d9593e0632 | /genMBSliceTimes.R | f6c1f5d0f69c530b6a0a062ea829e0759a61d5ef | [] | no_license | LabNeuroCogDevel/mMRDA_analysis | 9a9845635c4e34212a9ac0de26ccedf2c82ef435 | 2fb8321a553851a80c47fd7921fd64b85c8842aa | refs/heads/master | 2020-04-08T12:10:31.167549 | 2014-04-03T16:09:29 | 2014-04-03T16:09:29 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,716 | r | genMBSliceTimes.R | ## Script developed by MH 2014
## adapted 20140319 (WF)
##output approximate slice times for MB data
##From Tae Kim email dated 2/26:
##Each slice took 83 ms, and 12 slices for each TR acquired with interleaved order, 9, 5, 1, 10, 6, 2, 11, 7, 3, 12, 8, 4.
##Used 5x acceleration, so need to replicate this for every 12... |
7b57fb612f2d608d109db2d6d52b5b7ad9c311ea | 48e31e278423d7910dbf50d21afce0cf5e5b32be | /kaggle_titanic_code.R | b58af96b9243eda6af191571965897629dcf6b9e | [] | no_license | mukeshviru/kaggle-titanic1 | e2a82ab069f824128a0df5fa4b307d2fdc1179fe | 5e2f9a93a79a8cea2c5ba01f17f3750994f6f0c5 | refs/heads/master | 2020-04-12T10:51:20.231407 | 2018-12-27T19:38:36 | 2018-12-27T19:38:36 | 162,442,566 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,626 | r | kaggle_titanic_code.R | # Load libraries
library(randomForest)
# Load the train dataset111
train_data <- read.csv("train.csv",stringsAsFactors = FALSE,na.strings = c("","NA"))
View(train_data)
str(train_data)
# Load the test dataset
test_data <- read.csv("test.csv",stringsAsFactors = FALSE,na.strings = c("","NA"))
View(test_data)
str(test_d... |
9dc11622f3ec918dabf252a2cdc5af4d81589402 | a73ca7a675e371d1af66e030fd18003e4821064d | /truth.R | 9d3950bf4703e8edd011398589e25b9c82376586 | [] | no_license | weiyaw/multi-curves | f5a80d28a91eb24bde367149a01e83e1b95a8e9a | 5feebf27e7b03d4f7e1e23d8280b18b318eb2db8 | refs/heads/master | 2020-03-10T21:45:44.085011 | 2019-08-19T15:01:50 | 2019-08-19T15:01:50 | 129,602,089 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 14,474 | r | truth.R | # generate some parameters
library(tidyverse)
library(gridExtra)
library(bayesplot)
library(doMC) # for parallel loops
registerDoMC(4) # use 4 threads
source("~/Dropbox/master/algo/subor.R")
knt <- seq(0, 10, 2)
simdata <- read_csv("~/Dropbox/master/algo/data/simdata.cs... |
ad66cc1f0d753ad0516da8238fb574051141eacc | b28e19cbd6a9945d8bbeaeecaac7cad2c48ea87e | /scraper/rap_eng/texts/Wiz Khalifa/B.A.R | 5a5b8a1c0f22f5b14c299fa7909a662e135f9fda | [] | no_license | clarnomargurite591/rapper_ml | 1a0a8d491a546bc0a1d6d051f2ffcdf2cf17d54f | f094af3b0af67e8c5e7c65df2390be8f541ba857 | refs/heads/main | 2023-03-18T06:56:49.555809 | 2020-12-20T16:21:45 | 2020-12-20T16:21:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,139 | r | B.A.R | [Intro]
Fuck hoes everywhere we go
Taylor Gang, paper planes
Uh, they loving what I say
Tell her keep count
What you other niggas speak 'bout
[Verse 1]
Lamborghini dreams
Beach house wishes
Pour bottles of champagne
For my beach house bitches
It ain't new to me
That money, boy, I been 'bout
Throwing hundreds on the fl... |
f3f7d192d13844475c9885a5fa732959980c6a6f | ddf318aa7903e2de192170948b1bac837c8b3abb | /R/GEDI_Utils_l2b.R | 07eaaeaf5feafa00694bf2bafeb07b37fb4c6d80 | [] | no_license | JohMast/GEDI_Yucatan | 2ba9b9bea7b51427260ebcd00eef4800479baafe | e54fa5b44606641c5f69cc5c6ffb474511fce797 | refs/heads/main | 2023-02-17T05:28:23.137686 | 2021-01-08T08:31:39 | 2021-01-08T08:31:39 | 327,345,859 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 17,576 | r | GEDI_Utils_l2b.R | ######################################################################################
#
# Utility functions for the processing of GEDI L2B Data.
# Most of these are related to extracting and visualising data:
#
# - make_transsect_plot() : Plots ALS elevation vs GEDI elevation in a profile along a transec... |
2f5337a5b763933739c61dc30f36c86d524c7b5f | 9c48287a818f1c2d3c596a5f9591b2d3a3bd68b6 | /man/print.igEdge.Rd | a8584f1f2c6b1bb277eb4fa0da580527f8355062 | [] | no_license | cran/integr | f158f19273de3ba0e62ae43449741e1e1661bc8d | 03130a5d2f779cad5bec854379f04faebd31dfd7 | refs/heads/master | 2020-12-22T00:32:03.660478 | 2019-05-24T10:50:03 | 2019-05-24T10:50:03 | 236,615,394 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 431 | rd | print.igEdge.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/interactionGraphs.R
\name{print.igEdge}
\alias{print.igEdge}
\title{Print generic method for Interaction Graph Edges (S3 class)}
\usage{
\method{print}{igEdge}(edge)
}
\arguments{
\item{edge}{An \code{(igEdge)} object}
}
\value{
P... |
896384afd669b5dd8db5fd4d6e3c8968252f0a3e | efcd73d82923061a933661202415da88f6f0975a | /R/eps_ind_dist.R | 61d55e4faff5290fb55a369e285df71cbfc111ff | [] | no_license | SimoneHermann/rexpar | 624b0d30bd3fde12a5e908bd90057dc6d260459a | 3883b9f8aa1685c28979c621d427ae3080a1cd8e | refs/heads/master | 2021-01-21T15:33:59.129522 | 2015-06-22T12:03:59 | 2015-06-22T12:03:59 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 188 | r | eps_ind_dist.R | eps_ind_dist<-function(v1,Mat,eps)
{
dists<-apply(Mat,1,Ele_Norm,center=v1)
v2<-Mat[dists==sort(dists)[2],]
v3<-Mat[dists==sort(dists)[3],]
m<-v1+eps*(((v2+v3)/2)-v1)
return(m)
} |
9ec93d7a1dc93ffb819665e9fdb4c3772dfc7edf | 56a0f9cb2b2d0765eec9740697b434516e2f4d04 | /R_code_classification.r | 936c6e3fef14531bebf7da9262d212e68da02b2b | [] | no_license | SerenaBarberis/Telerilevamento_2021 | 688a1fd3ad120aa936a1dbc0685180d28355a2a0 | b76dd1aaef6852b95d6a96088edee3e76a22a4af | refs/heads/main | 2023-07-02T04:01:02.497632 | 2021-08-05T17:18:07 | 2021-08-05T17:18:07 | 348,290,149 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,766 | r | R_code_classification.r | #R_code_classification.r
setwd('C:/Users/Sery/Desktop/lab')
library(raster)
library(RStoolbox)
#funzione brick: prende un pacchetto di dati e crea un raste con bande RGB
so <- brick("Solar_Orbiter_s_first_views_of_the_Sun_pillars.jpg")
#funzione plotRGB: permette di visualizzare il rasterbrick
plotRGB(so, 1,2,3, str... |
50188b7363508d1dd7475f6d381974ae5b097492 | d37afdcab3673f594bd9534b5134e805b588eb4f | /02-walking.R | 80f7a19194d18a2ee04c7b2a50e851d38e840f30 | [
"MIT"
] | permissive | dougmet/cloudml | 774b9eec0d59c505ad2ee66dc520df598d81734f | 0488a83661232d3c0d59a9c5f5bef93fda6d958e | refs/heads/master | 2020-05-02T09:39:16.080459 | 2019-04-09T08:31:40 | 2019-04-09T08:31:40 | 177,877,344 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 479 | r | 02-walking.R | library(here)
library(cloudml)
# Need to be in right directory to submit job
# The here function anchors us to the project root
setwd(here("02-walking"))
# Submit a job
cloudml_train("walking.R")
cloudml_train("walking.R", master_type = "standard_gpu")
# Collect a specific job
job_collect("cloudml_2019_03_26_2147582... |
bfab66f5fa7591469df4589f3085dcdb2f8ddef6 | fd372fc8e9887c560700636ca4f8af60625f3cd8 | /wordscount.R | 8942931d3ef51e56b17cefae6eb48c75b7605861 | [] | no_license | simoncarrignon/CHASM | dd8438fc3598ebf94e2f49e68ae4e4508240ea09 | 7c9b690da9adb36bba06690576c5cfb05d6f24cd | refs/heads/master | 2021-01-08T11:07:12.195430 | 2020-04-08T06:21:45 | 2020-04-08T06:21:45 | 242,012,645 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,873 | r | wordscount.R | library(tidyverse)
library(tidytext)
library(rtweet)
#Take a timeline and return all unique words from this timeline
getAllWords <- function(timeline,replace_reg=NULL,unnest_reg=NULL){
if(is.null(replace_reg))replace_reg <- "https://t.co/[A-Za-z\\d]+|http://[A-Za-z\\d]+|&|<|>|RT|https"
if(is.null(un... |
09db40d7839f36d375c5d2c0f7a72c4d327529f9 | 9eb7c16ab805bec439323c2c5fc9ee62cc197aa4 | /HierarchicalGOF/man/run.chain.2pl.list.Rd | f9d1fff0407797d3f16729fea09bd4325cfeb100 | [] | no_license | sadanapr/HierarchicalGOF | 51377da28eda8758148f719cd1dcdecaf18b7947 | ac01f0dd3a5ec73e96833af1db258885ef271248 | refs/heads/master | 2023-08-11T18:21:50.351626 | 2018-01-26T22:28:12 | 2018-01-26T22:28:12 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 951 | rd | run.chain.2pl.list.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/N_mixture_functions.R
\name{run.chain.2pl.list}
\alias{run.chain.2pl.list}
\title{Title Wrapper for parallel processing}
\usage{
run.chain.2pl.list(models, Y.list, X, W, n.iter, checkpoint, thin, name.l,
starting.values)
}
\arguments{
\item... |
1578fbfe0dd3df4951705eab9d978728793293bc | a61104488f204a969a825fae8aa292ba53267ceb | /R/cell_tissue.R | e7c77a6e16818ef312df61be8b9befce109b5bb1 | [
"MIT"
] | permissive | sigven/oncoEnrichR | 2dbfdca6d49d4b40862942d2997611f841d9c80c | 3a42581a7fdf90ff33d955b0b8135f71217412ec | refs/heads/master | 2023-08-17T00:01:36.046133 | 2023-08-16T10:10:05 | 2023-08-16T10:10:05 | 223,118,510 | 45 | 9 | MIT | 2023-08-16T09:49:02 | 2019-11-21T07:53:42 | R | UTF-8 | R | false | false | 13,085 | r | cell_tissue.R | gene_tissue_cell_spec_cat <-
function(qgenes = NULL,
q_id_type = "symbol",
resolution = "tissue",
genedb = NULL,
hpa_enrichment_db_df = NULL,
hpa_expr_db_df = NULL) {
lgr::lgr$appenders$console$set_layout(
lgr::LayoutFormat$new(timestamp_fmt = "%Y-%m-... |
71d2552507206443dfd342488acb09d885e55f09 | 5e094991872cd54c38fa10f8527030df89af6438 | /R/ordmove.R | b01546b71a6a71dd2930d269fd3dbf0740d54669 | [] | no_license | lshtm-gis/PHSM_SI_package | 39b0c34f0f2190c39f20a5f745eee53e89352462 | 43c41f6da721e68748777bbcf9689aca4d1b8413 | refs/heads/main | 2023-03-31T05:19:38.416560 | 2021-04-09T07:14:45 | 2021-04-09T07:14:45 | 353,692,002 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,288 | r | ordmove.R | #' Compute the Ordinal Scope Scale for Movements
#'
#' This function read the output of the \code{ordgather} function
#' and compute the Ordinal scope scale for Indicator 4.5.1,4.5.2,4.5.3,4.5.4.
#'
#' @param x Output file from previous run - \code{ordgather} function
#'
#' @return Computed ordinal scale for Movements ... |
0bd7a13c8a3079adbc0c20ce12aa506b458c73bf | 691cf0cdb5d1d26f1a5d11e913c4a4dc8574ff0e | /Assignments/Assignment 8 code.R | d8ecb91e8269949a5acaa0de2581aae2273af3af | [] | no_license | bharwood-data/IST-707 | 96253d23e22deb4e32efd099ae8f63aeeaa8128e | 91382d1b6798146bdc4d42b7219c351fefcfac65 | refs/heads/master | 2022-04-22T11:23:34.277047 | 2020-04-15T20:29:07 | 2020-04-15T20:29:07 | 256,027,405 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,535 | r | Assignment 8 code.R | # libraries
library(network)
library(wordcloud)
library(tm)
library(slam)
library(quanteda)
library(SnowballC)
library(arules)
library(proxy)
library(stringr)
library(textmineR)
library(igraph)
library(lsa)
library(tidyr)
library(gofastr)
library(mclust)
library(cluster)
library(stringi)
library(proxy... |
e00523f37604563adf81265589605d8af7546fd3 | ef84851bd06ab41faa62190f6c8464809605cbb9 | /functions/taxa.turnover.models.R | 8052c6ff28c75ee30ac182185fd62b5677de4f6e | [] | no_license | TimothyStaples/novelty-cenozoic-microplankton | f306c22161c7fdaf840c1662f67178a91c92748a | 0a062c18a6e661d1d0a4af750186a9e42448470a | refs/heads/master | 2022-12-23T11:58:01.238855 | 2020-09-15T23:36:37 | 2020-09-15T23:36:37 | 288,867,070 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,460 | r | taxa.turnover.models.R | taxa.turnover.models <- function(novel.list,
test.edge.effects = FALSE,
ext.cutoff = NA,
orig.cutoff = NA){
# calculate bin-to-bin turnover for each taxa
turnover.list <- lapply(1:length(novel.list), function(x.n){... |
9a571631b8de7c19402adb69baaab72daeb5e84f | 12efb36fec3c3a1296dc20f7c7e988668a4f9b7a | /R/export.relex.experiment.R | 4320b995508cfe878720db9a51452683bc67ecff | [] | no_license | drmjc/relex | d4ec694f6185657a6e11990730267bdb24fc7527 | 2d03dcbfa968e207fe4762efe78bc74c6dba47cf | refs/heads/master | 2020-05-02T02:45:49.397218 | 2019-03-26T04:12:54 | 2019-03-26T04:12:54 | 177,711,122 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,254 | r | export.relex.experiment.R | #' Export a Relex experiment to tab delimited files.
#'
#' Export the peptide, protein and normalised protein ratios from a Relex
#' experiment as tab delimited files.
#'
#' @param exp A list of RelEx experiments
#' @param dir The path to the directory where you'd like the files to be made.
#' @param prefix The file n... |
4f7ef9630782166ddc1d9ac7429a792565c60a88 | 0f64ac5e3d3cf43124dcb4917a4154829e7bb535 | /scripts/analyse_DKM-FRS5_VG.R | cbf4d1a791e0b642a39246c352549a52a0558f1f | [] | no_license | wactbprot/r4vl | 8e1d6b920dfd91d22a01c8e270d8810f02cea27c | a34b1fa9951926796186189202750c71e7883f8d | refs/heads/master | 2016-09-11T02:22:39.828280 | 2014-10-07T14:37:55 | 2014-10-07T14:37:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 253 | r | analyse_DKM-FRS5_VG.R | ## run with rproc
if(length(doc$Calibration) > 0){
doc <- refreshAnalysis(cdb,doc)
doc <- getOutIndex(doc)
doc <- dkm.calPdkm(doc)
doc <- frs5.calPfrs5(doc)
doc <- dkm.uncertPdkm(doc)
doc <- frs5.uncertPfrs5(doc)
doc <- calEn(doc)
}
|
b5f2fb80164ffd223be94f60fe8b4a0bd686b035 | b46248dcee9ce1affb3a436e9090eb65dc5406ad | /script/script_raw/winterWheat/BIC/7_WW_BIC.R | ecaff1082dfdf669904c7fce65998196d375bbd5 | [] | no_license | MikyPiky/Project1 | 43561e6e0c1f75e070f0c66c2817d8bd4c7e13c7 | 3053e5a45731b65eb3306ad33875bcbf253cf879 | refs/heads/master | 2021-01-23T12:38:56.332927 | 2017-06-06T08:52:56 | 2017-06-06T08:52:56 | 93,317,514 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 26,631 | r | 7_WW_BIC.R | ################################
#### Winter Wheat in July ####
################################
'
######################
## File Discription ##
The purpose of this script is to estimate the impact of weather fluctuations in the month mentionend above on yearly crop yield.
This is done by the following the steps:
-... |
3d0cc397284e95c104ad07ac399b5520a52b2039 | 2f74b6fa3057fcb98ad562247ea055ea63446146 | /man/reg_gam.Rd | 40168d224d5b13faca8a4753aa388f53b8367bdb | [] | no_license | strayMat/warpDE | 977e0f0b2d99d3ef1e7bdef9e2cad1a3ff6d8275 | 92e50beba7c54581173925aeff14ab02233980b5 | refs/heads/master | 2021-01-01T16:38:04.340919 | 2017-12-07T13:41:45 | 2017-12-07T13:41:45 | 97,879,353 | 2 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,476 | rd | reg_gam.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/regression_plots.R
\name{reg_gam}
\alias{reg_gam}
\title{Plot one gene raw data and its regressions}
\usage{
reg_gam(data, gene, reg.f = "loess", span = 0.75, s.df = 4,
regression = T, null.model = T, npred = F, sd.show = F,
legend.show =... |
d48aa2730807e8fa011c51933c3764fef40f5778 | 2cf96544b40099506217ddd7c3088cdc769fa796 | /man/get_sentences.Rd | 6ea55327d4ee1ec2a790e82c8f1fc430272c8e3a | [] | no_license | cran/sentimentr | 0e3e9b7097670f6deb3c194c69e0429ce8f182f8 | 42a00f5813ba2ddefe1499ec053c7d9fe0b4c311 | refs/heads/master | 2021-10-27T21:24:05.432619 | 2021-10-12T07:30:02 | 2021-10-12T07:30:02 | 66,079,531 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,001 | rd | get_sentences.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/get_sentences.R
\name{get_sentences}
\alias{get_sentences}
\title{Get Sentences}
\usage{
get_sentences(x, ...)
}
\arguments{
\item{x}{A character vector, \code{sentiment}, or \code{sentiment_by} object.}
\item{\ldots}{Other argume... |
4cb8efe213d1bd343fcccd7517f21a3f3488cabc | c17b385466d7a618f748d8768c63c09fc55a4d58 | /man/cleansubject.Rd | 5aebe9cc621115a0977f9123393a0ce8082bff42 | [] | no_license | johnsonnei/Faculty | 3155c11950ad846317719f69dba6f6511776c836 | 061b773a21c32312df247e0d2922d2ef8c9bd2e7 | refs/heads/master | 2021-01-10T09:57:50.748116 | 2016-02-08T13:04:07 | 2016-02-08T13:04:07 | 51,293,018 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 566 | rd | cleansubject.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/cleansubject.R
\name{cleansubject}
\alias{cleansubject}
\title{Cleaning the Data 3.0 - By Department}
\usage{
cleansubject(df)
}
\arguments{
\item{data}{frame The name of the data frame, Faculty (from cleanname)}
}
\value{
A ... |
65b29490564ac0b81ee703f7e6e2855cc7e15733 | 1552c44b53a9a071532792cc611ce76d43795453 | /Inteligencia_Artificial/One_row.r | 50df70489902934dc326a81ff9f680d1737a4097 | [] | no_license | robl-25/Faculdade | 8ce16cee93f5948d33d45714de66578d189163f4 | 0801f5748d8d7d79314699b2e35258e402a55bd1 | refs/heads/master | 2021-01-10T05:16:45.842442 | 2017-11-09T02:26:26 | 2017-11-09T02:26:26 | 45,509,015 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,633 | r | One_row.r | rm(list = ls())
# Arquivo csv
tabela = read.csv("~/Downloads/play_tennis.csv", header=T)
# Faz contagens
contagens = apply(tabela[,1:(ncol(tabela)-1)], 2, function(valores)
table(valores, tabela,[, ncol(tabela)]))
idx_coluna = 1
erros_valores = apply(contagens[[idx_coluna]], 1, function(cont){
... |
ce6c69475c6c1737e6c3d075ad7c2fc056d2db67 | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/RMKL/man/benchmark.data.Rd | 17d8e65b44f97e4cafe2c3783c40433b73a0eef8 | [] | 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 | true | 526 | rd | benchmark.data.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/benchmark.data.R
\docType{data}
\name{benchmark.data}
\alias{benchmark.data}
\title{Benchmark.data.}
\format{A list of dataframes with 3 columns and 200 samples, where the x and y
are generated from 2 multivariate distributions. The mean of t... |
c2c427cc2cbd18f5693892fc0da56132a5105f12 | e10191a3c8906bf4512ab16731e632185f84513b | /cachematrix.R | 4357699732aa0c93359c171a4511d7c10d045e3e | [] | no_license | suhitag93/ProgrammingAssignment2 | 9f34817935a5be3501d83cf8f50903e31304ac49 | fe82beb69f4050cf0c6899c31f3599ca033f1639 | refs/heads/master | 2021-01-21T23:33:17.663501 | 2015-06-20T18:04:23 | 2015-06-20T18:04:23 | 37,609,705 | 0 | 0 | null | 2015-06-17T17:23:53 | 2015-06-17T17:23:53 | null | UTF-8 | R | false | false | 1,083 | r | cachematrix.R | ## MakeCache Matrix takes the input of the dimension for the square matrix and generates a matrix of random values
## it then generates the inverse of that matrix and returns a list of the set and get functions for the two.
## Write a short comment describing this function
makeCacheMatrix <- function(x = matrix()) {... |
72b36d2dd8064c3656b1d99926c5fe02117fa93c | e206a00f45f9cb6e00438b61195bb5754c71ab3f | /R/model.R | f765754e724ddb9fa0610f953fd4fbf409aa41b7 | [
"MIT"
] | permissive | knifecake/forrelgui | e3602fa5ef8eac7332fd24b6572953dfa24ce51f | 7f15ab0dc231500ef88e98e7e53d0e16e4f0444c | refs/heads/master | 2023-03-15T08:22:23.418347 | 2021-03-18T12:04:02 | 2021-03-18T12:04:02 | 298,838,696 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,934 | r | model.R | empty_model <- function() {
list(
# a pedtools::ped object, or a list of such
claim_ped = NULL,
# a pedtools::ped object, or a list of such
true_ped = NULL,
# a character vector containing the IDs of the individuals which are marked
# as available for genotyping. this is indented to... |
eb6c5e7fd6940baa1d737b6380b7e2a326289d4b | 87b55c6c2fea04aafd73ba793a251c836ec8eba1 | /lib/summary.df.R | 0397e8e7149b646c25d2b02dd04f1e895312b039 | [] | no_license | irishlouis/DIA_TEETH_POC | 38660dea4f2eeed74bd168ff61a238e4a34bb9a4 | 5837e5b21a7c22ce8b42a1031e879bd0475ae04b | refs/heads/master | 2021-01-21T13:57:32.336977 | 2016-06-01T13:51:29 | 2016-06-01T13:51:29 | 53,400,986 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 816 | r | summary.df.R | #' summary.df
#'
#' @param df data.frame to summarise
#' @param freq frequency device recording at
#' @param k window size of smoothing
#'
#' @export summary data.frame
#'
summary.df <- function(df, freq, k=10){
test <- select(df, time_minute, vector.mag) %>%
melt(id.vars = "time_minute")
times <- unique(d... |
5fc6c63c18d38b26fa3ad1607be58cfbff531bde | 04d12d9c20048ca86da8d05fc72a65b8f13da571 | /predict_logistic_regression.R | ab9855cd6aa3c14c292e0f8edc49140185036345 | [] | no_license | yashparekh/risk-prediction | 6712804fd8729a2b3c464f8cecbb264327cb16b2 | 2593d84fcc2a9ccaa2207686a5cea6b23e5711b1 | refs/heads/master | 2021-04-15T09:27:33.775949 | 2018-03-25T20:13:27 | 2018-03-25T20:13:27 | 126,735,789 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,511 | r | predict_logistic_regression.R | #part1
cars<-read.csv('car_data.csv')
set.seed(71923)
train_insts<-sample(nrow(cars),0.7*nrow(cars))
cars_train<-cars[train_insts,]
cars_test<-cars[-train_insts,]
#part2
attach(cars_train)
boxplot(VehOdo~IsBadBuy,ylab='VehOdo',xlab='IsBadBuy')
boxplot(VehicleAge~IsBadBuy,ylab='VehicleAge',xlab='IsBadBuy')
mak... |
34fc4e15e67ef454682405231d779a0da10820fe | ba2845eadc8880147e906ab727d322d875226efa | /Analyses/soilmoisture/savestan.R | 8824c04aefe5aaa8a69f53ed9540050483469f77 | [] | no_license | AileneKane/radcliffe | 80e52e7260195a237646e499bf4e3dad4af55330 | 182cd194814e46785d38230027610ea9a499b7e8 | refs/heads/master | 2023-04-27T19:55:13.285880 | 2023-04-19T15:15:02 | 2023-04-19T15:15:02 | 49,010,639 | 5 | 2 | null | null | null | null | UTF-8 | R | false | false | 553 | r | savestan.R | # Utility function which saves all stanfit or shinystan objects in the working memory to a .RData file with today's date. Optionally add a suffix to describe this set of models
savestan <- function(suffix=NULL) {
tosave <- which(
sapply(ls(envir=.GlobalEnv), function(x) class(get(x)))
=="stanfit" |
sapp... |
5b93af50dc5c360167267d2eaa89b5f5f58eef88 | 0ecc38c2cc3d5061f4668ca151475703ac8b5ee6 | /r/02.loadConvertCleanMergeData.R | 008e3ceb96e6f5b23f4d3803854f0f6d3af80b64 | [] | no_license | jsorbo/r-exposome | b9fca734550bfe6636a15542271c16fc9802b2b1 | 9d665cd12b49eaaec10045e6fe3cb08275cc4882 | refs/heads/master | 2021-01-22T20:26:49.117486 | 2020-10-16T02:33:46 | 2020-10-16T02:33:46 | 85,323,080 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 10,740 | r | 02.loadConvertCleanMergeData.R | ################################################################################
# 2. load data, rename columns, clean data, merge data frames
# Import from csv
independent <- read.csv(file="..\\exposome-data\\independent.csv", header=TRUE)
dependentQuintiles <- read.csv(file="..\\exposome-data\\dependentQuintiles.cs... |
49e78891ab0af6d2c9bc316b9978c6780bd51697 | ad07245f317e5bbd83668a97d9212dc9bd2d2df7 | /man/zscore.Rd | db7b1660a21d3dddd1093d0b3abbac976f441fde | [] | no_license | lin-jennifer/polstat | 895022dd114eafe80c11852bfc78edaa5a7093f5 | 33e73d8486b7c06e98af1b7d8c8c97a439d250d8 | refs/heads/main | 2023-01-21T15:00:26.850008 | 2020-12-01T15:59:48 | 2020-12-01T15:59:48 | 313,154,514 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 477 | rd | zscore.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/zscore.R
\name{zscore}
\alias{zscore}
\title{z-score Calculations}
\usage{
zscore(x, mean, sd)
}
\arguments{
\item{x}{the observation}
\item{mean}{mean of interest -- can be sample or population depending on zscore interest}
\item{sd}{stand... |
9dafe0e88e12b67baf5aa57238050a04ce11eb6d | 74cbb0028395fc41e172dffe63970acf19f53361 | /R/colors.R | 666731852ba69ecc016bdd28210c0c5df7bafddf | [
"MIT"
] | permissive | fionahevans/Ragronomy | 004cdc59f7fa9e5b89be7dbc25f797dad8c4eb09 | 1b5420b15796f59499f8c33fc3457ee1f0ebe0ac | refs/heads/master | 2021-09-28T09:21:55.266071 | 2018-09-07T05:20:14 | 2018-09-07T05:20:14 | 112,438,858 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,475 | r | colors.R |
#' Makes colors for plotting
#'
#' Makes colors for plotting, stretched to cover the range of x
#'
#' @param x Input data.
#' @param col Color map (default is tim.colors).
#' @param range Range of x values to limit color to (not required).
#'
#' @author Fiona Evans
#'
#' @return Returns a vector of colors.
#' @expor... |
044ed973dedb882f740bef19b6ff7646da8e3538 | f10238b9bee304a4d035b4063923ba3b04a31b5d | /logspec/ranges.R | 03feb6d10a121271680bdb8d5a181c8bee1cd012 | [] | no_license | ClimateImpactLab/hierarchical-estimation | 9a6787e4388135ef25c29ac322cc2a686e175a58 | 267141f8dede7b5be11c6d15f58589c8e6a742e1 | refs/heads/master | 2021-01-18T20:16:43.242558 | 2018-09-12T09:43:24 | 2018-09-12T09:43:24 | 86,951,455 | 0 | 0 | null | 2018-09-12T09:44:06 | 2017-04-02T00:18:25 | R | UTF-8 | R | false | false | 12,127 | r | ranges.R | ## This library supports logspec.R, and logspec.R must be loaded.
## Calculate the log likelihood, computing ADM1 sigmas from residuals
calc.likeli.nosigma <- function(dmxxs, dmyy, zzs, kls, mm, betas, gammas, weights, prior) {
dmyy.exp <- calc.expected.demeaned(dmxxs, zzs, kls, mm, betas, gammas)
sigmas <- c... |
53a2fbd34302e7e974017c039d49f53eb6ef6180 | 13c60c86f5eaf15b0a5286cf28f4785c433a05d2 | /inst/manage/server.R | 90abf8b1108974675b25d75ed6dd490c0c11179a | [] | no_license | dondealban/marxanui | 8cfe95e93d37e42af0f35e06f3527eefb14316c8 | 8eb2a2f8c2f712b10c42c215283aa6a31d52aa8e | refs/heads/master | 2021-06-06T21:46:25.401672 | 2016-07-01T04:20:06 | 2016-07-01T04:20:06 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 17,931 | r | server.R | # marxan.io
library(shiny)
require(sp)
require(maptools)
require(PBSmapping)
require(foreign)
require(sqldf)
require(vegan)
require(labdsv)
require(xtable)
library(foreach)
library(rhandsontable)
library(iptools)
library(png)
library(rjson)
# which platform are we running on?
detect_platform <- function()
{
sPkgT... |
bc64979e465de9dadf0a50827732d426a9c7f8f2 | fc1d61d27acdd923dd91f78e6633ba62caa31c82 | /man/DCF-devel-package.Rd | fb14f4450b64ce2f868c22ac4f42ce14147bec79 | [] | no_license | dtkaplan/DCF-devel | 7cbba8f25403ae8cb6c2d86d5a3034073e813058 | cda59571dfeb3b4832705d83d4a1fa71d2f969af | refs/heads/master | 2021-01-21T13:08:42.353997 | 2014-07-03T21:40:16 | 2014-07-03T21:40:16 | 19,037,348 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 617 | rd | DCF-devel-package.Rd | \name{DCFdevel-package}
\alias{DCFdevel-package}
\alias{DCFdevel}
\docType{package}
\title{
Testing organization of Materials for the DCF course
}
\description{
This is a package to let me try out different ideas for organizing the DCF course
}
\details{
\tabular{ll}{
Package: \tab DCFdevel\cr
Type: \tab Package\cr
Ver... |
ed254b654745e5e3013fe4f565abddb01c0ce238 | c9ee3e253e94cfe599f7ebefa3cab108772a50a3 | /carcomp021721.R | ffbe92d7f5fd2289417e8423d0ebf140b7d6c5bd | [] | no_license | RAFrancais/UsedCarComparisons | 7b277ab2a4577ba5cade41187068c599d20551c4 | 90d3410258314e9ebc04aaf715b9290f381ee7e4 | refs/heads/master | 2023-04-24T12:30:40.486047 | 2021-05-12T09:01:46 | 2021-05-12T09:01:46 | 366,651,763 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 826 | r | carcomp021721.R | load("D:/RLearning/usedcarcomp/at_xbprice_20210217.Rda")
load("D:/RLearning/usedcarcomp/cars_xbprice_20210217.Rda")
load("D:/RLearning/usedcarcomp/tc_xbprice_20210217.Rda")
load("D:/RLearning/usedcarcomp/at_avalonprice_20210217.Rda")
load("D:/RLearning/usedcarcomp/cars_avalonprice_20210217.Rda")
load("D:/RLearning/used... |
1872a9e8bda5bc3349e322fb20f1310b7318a443 | 28e604609e6d97c95f1856d80b6ed4eb2fadefe0 | /man/neighbours.Rd | c6e40f80fe40e58dbc6f1b921315899dfb26e2ca | [] | no_license | beerda/hexmatrix | f75d4c4ad819c8a7d9049d475d92a5fda5ec7485 | 1ae37a739fb5803932d3e71a9ff972b4342ea809 | refs/heads/master | 2021-06-21T05:32:09.752989 | 2021-04-28T10:32:09 | 2021-04-28T10:32:09 | 210,574,230 | 0 | 0 | null | 2020-11-04T08:17:30 | 2019-09-24T10:20:51 | R | UTF-8 | R | false | true | 848 | rd | neighbours.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/neighbours.R
\name{neighbours}
\alias{neighbours}
\title{Returns an array that represents values of neighbours
in the clock-wise order starting from top-left neighbour}
\usage{
neighbours(m, self = FALSE)
}
\arguments{
\item{m}{a matrix or ar... |
9232f5ddd71051e8965428008acb666b93e228c0 | 12587953f560adfc3c1be32a2c9775d223389c6d | /plot3.R | 3b30d591e684d3613b586cc5016cc255d87c499e | [] | no_license | DrShashiPonraja/ExData_Plotting1 | 3a2bcb275dc19fac06fb74ab61b0c366c9ee97c7 | 2ad7d6d7b4dc11fa6ffcb4ee1cb972af37b680cc | refs/heads/master | 2021-05-08T14:47:58.791401 | 2018-02-04T06:01:45 | 2018-02-04T06:01:45 | 120,099,649 | 0 | 0 | null | 2018-02-03T14:44:25 | 2018-02-03T14:44:24 | null | UTF-8 | R | false | false | 421 | r | plot3.R | source('getData.R')
myDataSet<-getData()
plot(myDataSet$DateTimeFormat, myDataSet$Sub_metering_1, type="n", xlab="",ylab="Energy sub metering")
lines(myDataSet$DateTimeFormat, myDataSet$Sub_metering_1,type='l')
lines(myDataSet$DateTimeFormat, myDataSet$Sub_metering_2,type='l', col="red")
lines(myDataSet$DateTimeFormat... |
120eb797ebc7961175980e917acd1e7584645113 | b8e545dd1ff413af4d787567159f6b5419170070 | /setSeedsForClassifications.R | 974ceb47ce58f476a4d1b5a51e076e8ce71098a1 | [] | no_license | Wytz/DiseaseTrajectories | 3849bc9dd7c407eb58c1fb2f6e3fbe50b5bb810b | 58034f94d011fb92ab9a00eeb2abf7ca1c24799f | refs/heads/master | 2020-07-11T22:59:58.592695 | 2019-11-07T10:18:38 | 2019-11-07T10:18:38 | 204,661,816 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,067 | r | setSeedsForClassifications.R | # Set the seeds which are used to randomize in Caret, to enable a paired T-test between the AUCs
#directory = "Akker feature sets"
directory = "Jensen feature sets"
require(caret)
require(ranger)
require(doMC)
require(data.table)
registerDoMC(cores = 3)
# Select the seeds
SampledSeeds = sample(c(1:10000), size = 101... |
36b351721904d5573e9ceb0cfa738a4188d5d9c4 | 7af0de4a6767812f392bd69a2298f45550f8abb5 | /neuralnet_diags.R | a5be68fd323e1d0d1e1d064db4b922a8db5d6360 | [] | no_license | SudhakaranP/Statistical_Learning_Basics | 615077494c15c9ae8f28cd3e856eee7b8cd03678 | 40162b9831bdc165da5af926cc2c7ba8a9fe674f | refs/heads/master | 2021-06-14T18:56:40.890625 | 2016-12-14T02:04:34 | 2016-12-14T02:04:34 | 105,226,455 | 0 | 1 | null | 2017-09-29T03:37:24 | 2017-09-29T03:37:23 | null | UTF-8 | R | false | false | 7,521 | r | neuralnet_diags.R | # action like a lekprofile
neuralnet.diagnostics <- function(nn) {
outs <- unlist(strsplit(
as.character(
formula(nn))[2]
, split = " + "
, fixed = TRUE))
nouts <- length(outs)
if(nouts != 1) stop("Function can only handle single response variable")
ins <- unlist(strsplit(
as.character(... |
454f3c02acfa80def2e8dc3b7b5a5427d7e1755e | cea7b5b1a105534c57ddbfb9382553758f94ab0f | /Lectures/Week 6/DFA_with_the_MARSS_pkg.R | 27bf0e9fbdcd42fc135f7c98530c42589f4eaa30 | [] | no_license | YanVT/atsa2017 | 973ed4dc7fe812d0794421c516225da668cf6477 | 60313ca2e5a3aae47de68e1adb4f32c9c5cef4e0 | refs/heads/master | 2023-08-31T08:47:02.631251 | 2019-05-09T02:46:04 | 2019-05-09T02:46:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,572 | r | DFA_with_the_MARSS_pkg.R | # Here is the code from Chap 9 of the MARSS User's Guide
# Dynamic factor analysis (DFA)
###################################################
### code chunk number 2: Cs01_read.in.data
###################################################
# load the data (there are 3 datasets contained here)
data(lakeWAplankton)
# we ... |
711e3177a5969875069cfb3f2d9acfee9bfb1cc4 | 8cc220a74dff794980b29352a5eb451bd2044d6f | /weather_dash/app.R | 0a9476b70d0d5478fc0f560589886c9f65352fc7 | [] | no_license | austincauthon/weather_dash | 4dadaeb68b215725cc91087d5f00a83ba7505adb | a74e7fc382e257b02f2b446e1450e652d0492bcc | refs/heads/master | 2020-12-07T15:23:39.345039 | 2017-07-07T02:07:54 | 2017-07-07T02:07:54 | 95,505,645 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 3,589 | r | app.R | rm(list=ls())
library(darksky) # powered by dark sky
library(data.table)
library(ggplot2)
library(gridExtra)
library(magrittr)
library(lubridate)
library(scales)
library(shiny)
library(zipcode)
source("R/weather_functions.R")
source("C:/Users/set-darksky-api.R") # need key from darksky.net to work
data(zipcode)
setDT... |
55bf2ad70292b2f972967a2a26bcc5e24d1b7726 | 86422f71fb0db244ea0c49909563a9420c584128 | /R/facebook.R | 82adc5c5cb075c98a80afa53f4b0f5a4a8a835b8 | [] | no_license | Decision-Stats/s15_codes | 0d69fb9e95faabf35d41fd327ed490968cf2dbac | 673a8078163a2eddd02fe418744a71542326c2e0 | refs/heads/master | 2021-01-19T06:58:29.421813 | 2015-07-10T17:16:21 | 2015-07-10T17:16:21 | 38,714,623 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 599 | r | facebook.R | # use the follwoing site to generate the access token,
# https://developers.facebook.com/tools/explorer
library(Rfacebook)
library(Rook)
library(RCurl)
require(rjson)
access_tk="CAACEdEose0cBAIs9NDtrWnwYFtbAU38nNwKvk4BMmvg8rqnYVyDFigBflqaiHEIjdCMTbUCgtrZAZCkh9ZAM1RXFjKSJw7uJtn2F6mY13BOBrsiTWOxRMAKuQfQCHNX71310TXZBUDZB... |
409d39396d29cf3860c9ed4925b42bc3d4d92351 | eb8e225361c5a640d23207735e88d87aa8477533 | /man/Mstep.hh.MSAR.with.constraints.Rd | c4a98e8718c8ba6912ff86b10ce4a82f40fb7112 | [] | no_license | cran/NHMSAR | 6ec23ee69d3398005f85e64293b32fe5f71b5375 | 6fbbfdd21700d5b6b95322844abdc93129cddc22 | refs/heads/master | 2022-03-03T06:41:29.892008 | 2022-02-09T06:40:11 | 2022-02-09T06:40:11 | 27,052,794 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,616 | rd | Mstep.hh.MSAR.with.constraints.Rd | \name{Mstep.hh.MSAR.with.constraints}
\alias{Mstep.hh.MSAR.with.constraints}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
M step of the EM algorithm for fitting homogeneous multivariate Markov switching auto-regressive models with constraints on VAR models.}
\description{
M step of the EM alg... |
a8f017b0fa6f61fa7703a8eb1b3b9b25feb9e159 | 91d9b5e6c26b41b9e0dd369aa4984462a629b38e | /man/reorder_factor.Rd | 7faaab4f943cc7b1dbd569cdde80d38dbd2ccf7b | [] | no_license | jeffbone/First-Package | d3b421952bb709f2c7aa3cdc91ac82475880bbaf | d5888b58b07e2f66a7f8aa27956e2f458fc12c69 | refs/heads/master | 2021-01-10T09:02:21.907372 | 2015-12-01T17:41:51 | 2015-12-01T17:41:51 | 46,591,500 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 372 | rd | reorder_factor.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/reorder.R
\name{reorder_factor}
\alias{reorder_factor}
\title{Reorder the levels of a factor by frequency}
\usage{
reorder_factor(x)
}
\arguments{
\item{x}{factor}
}
\value{
factor
}
\description{
Reorder the levels of a factor by fre... |
ffd30f7f19db216190126a2cc325ff16b30e1dce | 1df7034a9bafd862b03994f97b4ead5445488a12 | /examples/ex01DistanceVNearness.R | edaabc4aee875e04d64dee3237dda9a0aa938a81 | [] | no_license | neurodata/U-Rerf | c28d76baacecbf8f8be4cce220294ade68575eeb | f3bf3d91892eae7817a6106caab094b620b964f3 | refs/heads/master | 2021-05-14T08:37:27.760419 | 2019-02-12T17:09:07 | 2019-02-12T17:09:07 | 116,304,664 | 2 | 8 | null | 2018-12-03T21:52:37 | 2018-01-04T20:31:15 | R | UTF-8 | R | false | false | 2,372 | r | ex01DistanceVNearness.R | source('../rfr_us.R')
library(ggplot2)
# number of trees for forest
numtrees <- 100
# number of dimensions in dataset
m <- 10
# number of samples in dataset
sizeD <- 1000
# the 'k' of k nearest neighbors
depth=8
k = 3
# create a sizeD by m synthetic dataset
X <- matrix(sort(runif(m*sizeD)), nrow=sizeD, ncol=m)
AkN... |
51827abd57ed22a4d30d1bf54b4f35a205031ed4 | 9ae55589b58f9393c342a353b99da4c9955497e1 | /man/str_2_list.Rd | eca636b54d0d34f4dc4ce7eca4f7a0f1a668db13 | [] | no_license | nrkoehler/xyzfuns | 25cf0b076122037cef6720a48b7d36bd1afe14ae | f57e8e759eba16e7fdf3bb216b6121b26077c60c | refs/heads/master | 2022-02-05T20:34:03.438697 | 2022-01-12T16:17:11 | 2022-01-12T16:17:11 | 223,168,481 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 255 | rd | str_2_list.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/helpers.R
\name{str_2_list}
\alias{str_2_list}
\title{{Character string to bullet list}}
\usage{
str_2_list(str)
}
\description{
{Convert a character string to a bullet list}
}
|
e27078b12c1c13f565f94206e071d1ece6172034 | e6549edacf38351730ca91ead2456d50ba20f1cd | /man/logabs.rd | cc7212ad0ad8ba539bf072c00203418824d7e7fa | [] | no_license | cran/wavethresh | 96f92574f59f62f77b9b5fe5c318e27011de585c | 433dac8d2b5f3bf806530a29b5fe022fd2fe9087 | refs/heads/master | 2022-11-29T22:37:39.292801 | 2022-11-16T14:20:02 | 2022-11-16T14:20:02 | 17,700,852 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 587 | rd | logabs.rd | \name{logabs}
\alias{logabs}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Take the logarithm of the squares of the argument
}
\description{
Take the log of the squares of the argument
}
\usage{
logabs(x)
}
\arguments{
\item{x}{A number
}
}
\details{
Description says all
}
\value{
Just the lo... |
425386ab1803598e8b7ae20e683ff65922cbebc2 | 8b4ada2a81d8f1ece2355197d37001d87b55f12c | /man/kumexp.Rd | 939a0b70c72eec98923a8a4de4418f5491febb94 | [] | no_license | cran/VaRES | f7685d92072b9646c47a62ed554dde0222e2ada9 | 1a17f2389450e7f67319a9f62e21cbb03bcb5d24 | refs/heads/master | 2023-05-06T00:09:29.334906 | 2023-04-21T23:42:37 | 2023-04-21T23:42:37 | 17,694,053 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,529 | rd | kumexp.Rd | \name{kumexp}
\alias{dkumexp}
\alias{pkumexp}
\alias{varkumexp}
\alias{eskumexp}
\title{Kumaraswamy exponential distribution}
\description{Computes the pdf, cdf, value at risk and expected shortfall for the Kumaraswamy exponential distribution due to Cordeiro and de Castro (2011) given by
\deqn{\begin{array}{ll}... |
6f73928f3ddf97afef37ba1d75c50e66961d67fb | 90b1d0ac1ce238ebb70998aec1d31adfa2eed463 | /plot1.R | 00e2a30867a4edb70bbcef11f67174736ce7fe1f | [] | no_license | dlmaas/ExData_Plotting1 | c827aebcf49479a5b634fc0d9919b3c352fc2280 | d736b4a72b1ab869ab5dd4aa2d6e62e565e7be68 | refs/heads/master | 2021-01-18T00:22:32.028137 | 2016-07-17T20:29:28 | 2016-07-17T20:29:28 | 63,515,152 | 0 | 0 | null | 2016-07-17T04:45:06 | 2016-07-17T04:45:05 | null | UTF-8 | R | false | false | 1,440 | r | plot1.R | download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip",destfile="dataset.zip")
#
# The zip file will be downloaded and store in the working directory of the user.
# The file is then Unziped and stored in the working directory of the user.
#
unzip(zipfile="dataset.zip"... |
fbcf9df21741461d51570a7f9c57daaa8d29122d | 27a4b648ab2dfb3c4279e2c20f5acd37f933e6c9 | /tests/testthat.R | 35f808afdecc97dfbcfa01c65330ba423294e2e8 | [
"MIT"
] | permissive | Sung-Huan/PerseusR | 2a8ece1a9c90bc5f3349a94dd3e06c82f8170f9f | bb36d046bc3925ca9dd0320ba66f2ab71c142448 | refs/heads/master | 2020-03-30T09:14:57.371581 | 2020-02-20T10:56:16 | 2020-02-20T10:56:16 | 151,067,743 | 0 | 0 | NOASSERTION | 2018-10-01T09:56:50 | 2018-10-01T09:56:50 | null | UTF-8 | R | false | false | 64 | r | testthat.R | library(testthat)
library(PerseusR)
test_check("PerseusR")
|
9f77a7d82d6e3450b683ba2e9e536e1fcabb64fb | 29585dff702209dd446c0ab52ceea046c58e384e | /pkgmaker/R/CLI.R | 49eaac200e4a3fb8242c2d749d2e4ea321c7d42c | [] | 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 | 10,184 | r | CLI.R | # Command Line Interface utils
#
# Author: Renaud Gaujoux
# Created: May 9, 2013
###############################################################################
.silenceF <- function(f, verbose=FALSE){
if( verbose ) f
else{
function(...){
capture.output(suppressPackageStartupMessages(... |
a71b0cf1a449dc07c4efb814b19bdce3cc50943c | 21290234281322dec6fdb3e7cf7d55629e65daea | /data/code-r/KD_TREE.R | 0304421bedc71485702be0e4c9f59e6a802b0ca7 | [] | no_license | chasememeda/POI | b55aa1e7557ee0fc4494d7f15e48131707ce3760 | cbfd234e779c347ac6591bb5cb85f430e51fbe24 | refs/heads/master | 2020-04-28T10:48:10.345790 | 2015-06-22T13:38:13 | 2015-06-22T13:38:13 | 37,855,983 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,520 | r | KD_TREE.R | library(RODBC);
db <- odbcConnect("poi",uid="root",pwd="root");
#info <- odbcQuery(db,"select ID, NAME, X_COORD AS X, Y_COORD AS Y , CATEGORY AS CAT from poi_info");
cats <- sqlQuery(db,"select count(ID) as total, category from poi_info group by category ORDER BY total DESC");
#################################
#Funct... |
dfe722dfeea1595f282741c04fb18901fd8ada51 | 5220d6bcfd84e4a5486253bad9b43ce9e7bd3d86 | /R/RDFBonesQuery-package.r | 21818cce6abc7e6bb063b20bcebc11082f600a9d | [] | no_license | RDFBones/RDFBonesQuery | e545e841911f5757a96a6b15a9877bc69df34059 | fd1dace72742ca558445064f08831e295556f23e | refs/heads/master | 2021-01-22T19:25:52.978543 | 2017-03-28T13:32:47 | 2017-03-28T13:32:47 | 85,200,569 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,755 | r | RDFBonesQuery-package.r | #' Provides predefined queries of RDFBones SPARQL endpoint
#'
#' Provides predefined queries of RDFBones SPARQL endpoint
#'
#' \tabular{ll}{
#' Package: \tab RDFBonesQuery\cr
#' Type: \tab Package\cr
#' Version: \tab 0.0.1\cr
#' Date: \tab 2017-03-16\cr
#' License: \tab GPL\cr
#' LazyLoad: \tab yes\cr
#' }
#'
#' @na... |
887199d41aeaa6feb5ae6ce93dd8179c426d2c49 | e796addadd71d250546a9a592d119b52efb5f447 | /man/combine_terms.Rd | ca59f33b1717c3ee3eba74efed28b31a3dd6f39c | [] | no_license | DanielReedOcean/ACCASPR | cab6be70a0167911170e9c1b2860844567aa90ff | 56267e22a3348645af831e445c79f8653cbb4062 | refs/heads/master | 2021-04-30T12:51:39.013388 | 2019-08-20T14:26:29 | 2019-08-20T14:26:29 | 121,279,940 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 327 | rd | combine_terms.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fit_models.R
\name{combine_terms}
\alias{combine_terms}
\title{Create right-hand side of GAM formula by combining terms}
\usage{
combine_terms(vars, kval)
}
\description{
Create right-hand side of GAM formula by combining terms
}
\keyword{int... |
fb49ede16e7b1ca64706a7763a7ac229adbadc9d | b59d136b1fdb4d3adf4f8984bece7b746d1d36cb | /cachematrix.R | 893757b0f7560bd2edea5d3aeacf9123f5d4ac37 | [] | no_license | acmars/ProgrammingAssignment2 | c2b80a0450c9a400eca8280bb84c5ca4d3947505 | d75cffb5d65252ddb25bbc4b936c2c3d86d24254 | refs/heads/master | 2021-01-09T07:36:25.982104 | 2014-09-18T00:58:26 | 2014-09-18T00:58:26 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,327 | r | cachematrix.R | ##---cacheMatrix.R---
## This script contains two functions: makeCacheMatrix and cacheSolve
## makeCacheMatrix is designed to create a matrix that can cache the
## inverse of a matrix, using the solve function.
## cacheSolve is designed to compute the inverse of the matrix created
## in the makeCacheMatrix function, u... |
5b0b575bc5bdcf096e7b24b68372e3baced173df | d5331ec752b979e7c0b7edb81536875f6400a97f | /inst/shiny/server.R | 863551146b8401bc973716deb7cfc4cc697cd6e8 | [] | no_license | AuHau/ISRaD | 81ef5005951ad1dfb0bd72d34d2aea0ebd257f9b | 4e69adfdfadd521d932898a0b01f436bd2328e8e | refs/heads/master | 2020-04-18T01:23:27.646220 | 2019-04-04T16:25:29 | 2019-04-04T16:25:29 | 167,116,873 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,053 | r | server.R |
library(ggplot2)
library(dplyr)
shinyServer(function(input, output, session) {
options(shiny.maxRequestSize=30*1024^2)
observe({
x <- input$presets
if (x==1) {
updateSelectInput(session, "y_var", selected = "lyr_bot")
updateSelectInput(session, "x_var", selected = "lyr_bd_tot")
updateS... |
d7a73e2c8b724252e6b3cd980013fc4c24c12a43 | 430fbb7da6ed247c9f0d43e18301608344c37800 | /man/temperature_curve.Rd | 7539ea2482e679bbbf969bc42d669737dc09bcc7 | [
"MIT"
] | permissive | nielsjdewinter/ShellChron | 5158a6b4a8325c5d9bd828a35d9329465eaea0bf | ac2ecdddd0cd1616e60b3711f6b2cbca56abc411 | refs/heads/main | 2023-04-10T10:00:53.741679 | 2022-08-18T13:57:00 | 2022-08-18T13:57:00 | 303,992,660 | 3 | 2 | MIT | 2022-08-15T07:37:48 | 2020-10-14T11:22:55 | R | UTF-8 | R | false | true | 1,218 | rd | temperature_curve.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/temperature_curve.r
\name{temperature_curve}
\alias{temperature_curve}
\title{Function that creates a sinusoidal Sea Surface Temperature (SST) curve
from a list of parameters}
\usage{
temperature_curve(T_par, years = 1, t_int = 1)
}
\argument... |
1138a7b28b99278666002a6808c6c1a648394c2f | 04479a0945363db519854f8aeb02d864690fc47a | /R/load_data_ss.R | 5ebb6c29223afe970c58add28d5bba2ed22db13e | [] | no_license | nissandjac/PacifichakeMSE | f398521fd096f0e55b5634ebfe08232b8d9839ef | cf967413fa052c1a843bfaf6f1fc1542afd994ce | refs/heads/master | 2022-03-08T14:45:01.953621 | 2022-03-01T09:21:06 | 2022-03-01T09:21:06 | 124,948,437 | 6 | 8 | null | 2020-05-01T06:34:23 | 2018-03-12T20:37:25 | HTML | UTF-8 | R | false | false | 7,037 | r | load_data_ss.R | ## Load the hake data
# year and age input
#' Set up a TMB data list from a SS object
#'
#' @param mod # SS3 object
#' @param sum_zero # Force the recruitment deviations to sum to zero?
#'
#' @return Returns a list for TMB
#' @export
#'
#' @examples
load_data_ss <- function(mod,
sum_zero = 0){
... |
8e272197e9dce77f880fb7ebdb900de2f7cceea6 | 057cb37817ffeec47fffecdabb59fc1f060884e8 | /old/experiment_real_data_missing_data_1/import.data.R | a22a2c41a46b16815040d37e60aff0852a09666f | [] | no_license | BIMIB-DISCo/MST | 7e1a89e430ed0c16f42a9caecafb0e1f426189fc | d1db82d70c6df9c19ab86153e3b7e696d1f7588b | refs/heads/master | 2021-01-13T06:56:36.494870 | 2018-12-09T22:22:08 | 2018-12-09T22:22:08 | 54,653,989 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,527 | r | import.data.R | # load the required R packages
library(mi)
library(TRONCO)
# set the seed
set.seed(12345)
# structure to save all the results
data_paper1 = list()
# read the data and format them
data_1 = read.table(file=paste0(getwd(),"/alterations.txt"),header=TRUE,sep="\t",check.names=FALSE,stringsAsFactors=FALSE)
rownames(data_1... |
a9c80a3d8e486e63640113a50f530a73909193d0 | 867426f0d9725bbcc73a41f22695c920df36bdc7 | /error_calculator.R | 64cf5be7a082a4816e4ebc3f02244cbb0d407f26 | [] | no_license | kasungayan/favorita-grocery-sales-forecasting | e3626ceef3d3739aea8af8b02f5d08badc78a566 | 1ba4a2419aaed65a67dfb07904a9030af36787ce | refs/heads/master | 2023-04-17T11:48:59.383550 | 2021-05-03T14:45:45 | 2021-05-03T14:45:45 | 275,045,527 | 0 | 0 | null | 2021-05-03T14:44:41 | 2020-06-26T00:58:26 | R | UTF-8 | R | false | false | 1,849 | r | error_calculator.R | # Favorita-grocery-sales-forecasting.
# Eror calculation script.
# Kasun Bandara, June 2020
# Define the generated forecasts and actual values file name.
generated_forecast <- "GENERATED_FORECAST_FILE_NAME"
actual_forecast <- "ACTUA_FILE_NAME"
df_forecast <-
read.csv(generated_forecast, sep = ",", header = FALSE)
... |
d14965711e7eec4f25449bc52a0edc10563789c7 | 3a42630716521b58a20d5a9445fd3eb1007188aa | /man/color-interpolation-presentationAttribute.Rd | 361d42ac018aa605b485d175b1402aaa3e74bbae | [
"MIT",
"LicenseRef-scancode-other-permissive"
] | permissive | mslegrand/svgR | 2a8addde6b1348db34dee3e5145af976008bf8f0 | e781c9c0929a0892e4bc6e23e7194fb252833e8c | refs/heads/master | 2020-05-22T01:22:16.991851 | 2020-01-18T03:16:30 | 2020-01-18T03:16:30 | 28,827,655 | 10 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,812 | rd | color-interpolation-presentationAttribute.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/doc_PresAttrPages.R
\name{color-interpolation-presentationAttribute}
\alias{color-interpolation-presentationAttribute}
\title{color.interpolation}
\description{
Governs the optimization strategy for color-interpolation.
}
\section{Available A... |
b39b2804ff8f21cd2b7a8a85afa5a2cbaa6d2d2a | 2cd54a4365c128d94c120a204aaccf68c3607b49 | /tests/testthat/test-random_subsampling.R | 14a05ed4d4d6e4a9446291eada3b61d0afd3f916 | [
"MIT"
] | permissive | tikunov/AlpsNMR | 952a9e47a93cbdc22d7f11b4cb1640edd736a5c7 | 748d140d94f65b93cb67fd34753cc1ef9e450445 | refs/heads/master | 2021-01-13T17:35:29.827357 | 2020-02-23T02:35:30 | 2020-02-23T02:35:30 | 242,443,517 | 0 | 0 | NOASSERTION | 2020-02-23T02:27:15 | 2020-02-23T02:27:15 | null | UTF-8 | R | false | false | 473 | r | test-random_subsampling.R | context("test-random_subsampling")
test_that("random_subsampling", {
subject_id <- c("Alice", "Bob", "Alice", "Bob")
replicate <- c(1, 1, 2, 2)
rnd <- random_subsampling(1:4, iterations = 2, test_size = 0.25, keep_together = subject_id)
rnd2 <- random_subsampling(1:4, iterations = 2, test_size = 0.25, keep_together = ... |
09c80199809e3a26c5d9658689fe6c518bf8ff75 | c972b8f8b15c9aafa0f0a2dd0e407c9ca08b8a54 | /R/hello.R | ade3905a72b437b194f32464cbe0a1358d7bf896 | [] | no_license | nathania/dummy | 4f2dbf0829986e5f6b951945cbc13ec78ee09595 | f1c62b5049521eb6eee02be4231f200c0f116814 | refs/heads/master | 2021-01-01T05:14:47.194611 | 2016-04-20T15:18:54 | 2016-04-20T15:18:54 | 56,693,076 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 529 | r | hello.R | # Hello, world!
#
# This is an example function named 'hello'
# which prints 'Hello, world!'.
#
# You can learn more about package authoring with RStudio at:
#
# http://r-pkgs.had.co.nz/
#
# Some useful keyboard shortcuts for package authoring:
#
# Build and Reload Package: 'Cmd + Shift + B'
# Check Package: ... |
b27478683d4ade9c7a95283b9667f0a138d177ec | 0d0cac5c14fad2728187b708c666c304ca249648 | /Multi_ sets.r | c20a743af9b2ba179c02e0ccc283098e651e444c | [] | no_license | bfuhs/R_disasters | feb6d69c2ece36b5cf058d784d35d01ae0026026 | e71fc10d5f4318ba0c9e07a9ac949117c6179adc | refs/heads/master | 2016-09-05T21:55:42.596117 | 2013-07-09T20:07:22 | 2013-07-09T20:07:22 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,008 | r | Multi_ sets.r | ##### Multi_sets.r
#
# Brendon Fuhs
# updated 2-11-13
#
# NON-DEFAULT PACKAGES REQUIRED
# ggplot2, (xtable?)
#
# FUNCTIONS
#
# makeStatsTable <- function(x, categories)
# # makes a table of descriptive stats for a single dataset split up by category
# makeFitsTable <- function(x, categories, analysis, modelNames=N... |
dc216326441530949ec72ab36da6a37873be4a45 | dc5568c5988381e9d46ac9779e0ff7bb72630301 | /tests/testthat.R | d85eb10df8106db6733c26ef504a8164d009dfcf | [] | no_license | SoftFx/TTWebClient-R | f6a0f756df7ff139f03fb31f7fa94a3471402c17 | a2538a19721828b8e439b1dca1611dcefde31633 | refs/heads/master | 2022-10-23T03:40:43.340643 | 2022-10-11T14:19:03 | 2022-10-11T14:19:03 | 35,541,118 | 0 | 1 | null | 2018-12-21T16:15:44 | 2015-05-13T09:50:34 | HTML | UTF-8 | R | false | false | 68 | r | testthat.R |
library(testthat)
library(RTTWebClient)
test_check("RTTWebClient")
|
b726d49ab837d43c77572eef2ed22c47f7e29ed0 | 24e58764de7e1ecc1efdd5eee25800d63ab96d26 | /GEO837_class_18_climate_plot_code_updated_20181031.R | bf6e885fd81f1e7afc37fe4e9698cab2c5078eda | [] | no_license | dpoursanidis/GEO837 | 73df21d639b3ec94fcb96a964632eced9d0d7c0d | 418b82887195dbaa22971b2aafb971b11287e0c8 | refs/heads/master | 2020-08-27T23:13:37.570992 | 2018-11-07T13:59:53 | 2018-11-07T13:59:53 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,141 | r | GEO837_class_18_climate_plot_code_updated_20181031.R | #### GEO 837 - Remote Sensing of the Biosphere ####
#### Author: Kyla M. Dahlin, MSU Geography ########
#### making climate plots from worldclim data #####
# note - in RStudio go to 'Tools > Global Options' to change background color,
# font size, and 'soft-wrap R source files' (in 'Code')
# load packages to d... |
c46a5315ed8e62563042b2d0481bfbb1f967f14f | 8fcd363c8dd5cb712cd8ed88a37f5138dd4cf079 | /man/ggGroup.Rd | d32d3e497da14bcc14f97dd0166bb1d82ed20f31 | [
"MIT"
] | permissive | GreenleafLab/ArchR | 2d4fd5b4febf21d0d0315922fc1690ef16a6a2a0 | c61b0645d1482f80dcc24e25fbd915128c1b2500 | refs/heads/master | 2023-09-04T05:04:35.202961 | 2023-05-17T12:47:27 | 2023-05-17T12:47:27 | 216,123,064 | 313 | 132 | MIT | 2023-09-01T16:14:59 | 2019-10-18T23:35:41 | R | UTF-8 | R | false | true | 2,101 | rd | ggGroup.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GgplotUtils.R
\name{ggGroup}
\alias{ggGroup}
\title{A ggplot-based ridge/violin plot wrapper function}
\usage{
ggGroup(
x = NULL,
y = NULL,
xlabel = NULL,
ylabel = NULL,
groupOrder = NULL,
groupSort = FALSE,
size = 1,
baseSize... |
8e8a82a052617c5c7046cd947665d57f09f07540 | e5c066999a2d2cc87565e54cdc4c1a03db11ac4d | /trees_randomForest_bagging.R | 7eaf5060eb586d43d5f9a3c7a712a6c40990b2b2 | [] | no_license | jpwyckoff/Trees | e745d9a67a15f65b10447d202737943f13951fb7 | 0780bf427be28b784599762ecd4668b47c5c66f4 | refs/heads/master | 2021-08-31T22:42:18.955542 | 2017-12-23T06:29:05 | 2017-12-23T06:29:05 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,217 | r | trees_randomForest_bagging.R | ##Fitting regression tree
library(MASS)
library(ISLR)
library(tree)
attach(Boston)
names(Boston)
set.seed(1)
#create training set
train = sample(1:nrow(Boston), nrow(Boston)/2)
tree.boston = tree(medv~.,Boston, subset=train)
summary(tree.boston)
#---in summary you will see: ----
#variables actually used in tree constr... |
b09c4f1208658fc4ff2d67c42934770c176c971c | f255ef3c7452a307bbaaf95a092e4279aa5f366e | /test_data/visibility_analysis_within.R | a7148e11aa6b79b6e9bcff3c2dfb8c6b0133cfd3 | [] | no_license | bbuchsbaum/eyesim | a1a61068f53a16925566deb81e03fa5943686f0e | 4d4f48ef0b1812d5200b86d7216f8d03792c2435 | refs/heads/master | 2023-05-11T00:43:30.086058 | 2023-05-08T15:02:35 | 2023-05-08T15:02:35 | 86,451,769 | 8 | 2 | null | null | null | null | UTF-8 | R | false | false | 9,601 | r | visibility_analysis_within.R | library(dplyr)
library(tibble)
library(tidyr)
## load study data
pcstudy <- as_tibble(read.csv("~/Dropbox/New_pc_behavioural_data/study_fixations.csv")) %>%
filter(Image != "." & !(Subject %in% c(28,32, 109))) %>% droplevels()
pcstudy$ImageNumber <- as.integer(as.character(pcstudy$ImageNumber))
## create table f... |
bced2746750af00b8b195a5a81ea6fb641bde80c | 6beef7a871c10d3baf74d87520ae53dbd52cf450 | /R/SequenceData-coverage.R | a83528b53f8b7c1e686792d89c2d33f35417897c | [] | no_license | FelixErnst/RNAmodR | d66ed5cb83b300b3d9e24f8310f46bb2f9b734ee | 114a9f8f781a896205e573c3a87f437978dfe03f | refs/heads/master | 2021-11-22T11:37:10.254735 | 2021-08-25T19:23:14 | 2021-08-25T19:23:14 | 53,844,127 | 2 | 0 | null | 2020-04-29T10:15:57 | 2016-03-14T09:40:42 | R | UTF-8 | R | false | false | 7,681 | r | SequenceData-coverage.R | #' @include RNAmodR.R
#' @include SequenceData-class.R
NULL
#' @name CoverageSequenceData-class
#' @aliases CoverageSequenceData CoverageSequenceDataFrame
#'
#' @title CoverageSequenceData
#'
#' @description
#' \code{CoverageSequenceData} implements
#' \code{\link[=SequenceData-class]{SequenceData}} to contain and a... |
0e33e9e2b1a2bfbcd457976c54dc3782c95faa72 | 16304becc4c42c9a07591d038526ce543bfc3700 | /man/validate.covariance.model.Rd | e99912ab08bdc011cc72ea86231ff61c5aca65a4 | [] | no_license | cran/saemix | 2884fd4df50006001b6b0b828092d4a05b3accf1 | 5aadc67a897200bb74187459e46c51a3e7b6268c | refs/heads/master | 2023-07-08T07:45:00.826030 | 2023-06-27T09:10:02 | 2023-06-27T09:10:02 | 17,699,444 | 0 | 2 | null | null | null | null | UTF-8 | R | false | true | 1,360 | rd | validate.covariance.model.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/SaemixModel.R
\name{validate.covariance.model}
\alias{validate.covariance.model}
\title{Validate the structure of the covariance model}
\usage{
validate.covariance.model(x, verbose = TRUE)
}
\arguments{
\item{x}{a matrix}
\item{verbose}{a bo... |
d07b80dc92dc4019bfcac5310400eca55722eb17 | 6e4b1d5db4f6d5a42a324adbae883177e4ab0f23 | /v105pn.R | 2909ebf8fecce8e1e726423efecdc952ece03ce5 | [] | no_license | alexanderm10/druckenbrod_ecological_time_series | b9c749fbc24e67bb7430729fa83b11376bd4d23f | 0033476196b6fc7e19a3b809a3475e54f2d0dc53 | refs/heads/master | 2020-06-04T08:36:48.936310 | 2019-06-14T16:41:15 | 2019-06-14T16:41:15 | 191,947,590 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 22,879 | r | v105pn.R | # v105pn.R
# This function extracts a single tree-ring time series from
# an input RWL file and places it in a vector for time series analysis.
# The function power transforms and removes the mean to create transformed
# residuals. The function then detrends with an iterative neg. exponential
# fit, or if that d... |
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