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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
6c3162b5bba55f238bfa6130559b49c9d5aca67f | afcd366c47419daf0687137c06e94c9b32117bdb | /man/peg_partido.Rd | 8d7906cce955dec8118f53ce917b12f188ad6a29 | [] | no_license | luizmartins1980/apida | 1963bcfff0be75805f057efb60d2af0b3be21a80 | 98677327fafaf5bc648f55b25bd179a3cae766fb | refs/heads/master | 2021-04-25T06:40:43.017069 | 2017-07-22T03:52:37 | 2017-07-22T03:52:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 335 | rd | peg_partido.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/peg.R
\name{peg_partido}
\alias{peg_partido}
\title{Pegar informações de um ou mais partidos}
\usage{
peg_partido(id_partido)
}
\arguments{
\item{id_partido}{Identificador(es) do(s) partido(s)}
}
\description{
Pegar informações de um ou mais ... |
90162bd42162cc36b8e827e84463b408056e2422 | a92c154607a68a36905e86843bae56065bed5a6b | /addOccFromGTM.R | 1522e96f1bfa0277f1525c0e9ce8073f3cc1b448 | [] | no_license | fabiolexcastro/centralAmericaCocoa | 41c7af22ef3bbde8d55750ac06741fb613e59e33 | de0c4bc0d4168fc27c8fcdfe732afe515f1855e2 | refs/heads/master | 2021-05-13T18:36:03.720454 | 2018-01-09T21:05:45 | 2018-01-09T21:05:45 | 116,870,527 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,222 | r | addOccFromGTM.R |
require(raster)
require(rgdal)
require(tidyverse)
require(spdplyr)
require(rgeos)
require(gtools)
options(scipen = 999)
path <- 'W:/_cam'
shp1 <- shapefile(paste0(path, '/_points/_new/_second/_shp/coordsWGS.shp'))
shp2 <- shapefile(paste0(path, '/_points/_new/_second/_shp/coordsGTM_WGS_clip.shp'))
df <- as_data_f... |
704ecd7764c758891843649e56c5db82cfceb3b7 | a4ef53e8d087ce99848c7c4960af09927e0a56cf | /adaBoost/regresion adaboost con gbm.R | 61aa60ca7632322c60176f18b9a0e7470f0a4afa | [] | no_license | fhernanb/modelos-predictivos | 0ba16c309a1f726e9e8ca36d37fe7add3a7d0cb5 | 909d65c40ba666fd473b98cb6610b698eff87aad | refs/heads/master | 2023-02-19T05:57:33.799881 | 2021-01-22T12:46:22 | 2021-01-22T12:46:22 | 296,086,556 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,306 | r | regresion adaboost con gbm.R | # -------------------------------------------------------------------------
# En este ejemplo se busca encontrar un modelo de regresion que explique
# la variable respuesta y en función de las covariables x1 a x11, los datos
# provienen del ejercicio 9.5 del libro de Montgomery, Peck and Vining (2003).
# El paquete M... |
f0f99629606fbbfdeb0cc9f67eb6f84ffd686da7 | 2f9663e05f7f2c48e3246626bcfcb3bb40f7876f | /data-raw/nyccollisions.R | 6cd0fc782ede9c93cc36e1796e7c696dd0fa889d | [] | no_license | sboysel/nyccollisions | 6444abfb876aa878cc323f21dd54ac4804447b99 | bd84dfb5b876b15bac099ecfd362aef6e029e6d6 | refs/heads/master | 2021-01-19T03:19:50.950492 | 2016-07-13T02:17:22 | 2016-07-13T02:17:22 | 53,287,792 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,503 | r | nyccollisions.R | library(dplyr)
library(jsonlite)
library(sp)
# Fetch NYPD Motor Vehicle Collisions data for July, 2015
# Source: https://data.cityofnewyork.us/Public-Safety/NYPD-Motor-Vehicle-Collisions/h9gi-nx95
collisions.src.url <- paste0("https://data.cityofnewyork.us/resource/qiz3-axqb.json?",
"$limit=5... |
484e85b5fd3a82ae0ff860ee323038fbe4e26918 | c0c7c24ac4d773c9295cc9dd38fb6ea5cfe1d586 | /R/rocRanks.R | 84b182d4866a74502d5891d02937e0032d86a906 | [] | no_license | rstojnic/PWMEnrich-supplementary | f3f3ed73db3aeb0c76ac5c94a95e4ff2f029bcf9 | 1c8fe278aee1c1a4f13466c83e2f172ebc0b3cb5 | refs/heads/master | 2020-12-24T13:18:10.626712 | 2015-09-18T16:52:08 | 2015-09-18T16:52:08 | 42,733,871 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,002 | r | rocRanks.R | # roc curve for ranked data
#' Draw a ROC curve for ranks
#'
#' @param ranks a list of expected TFs and their ranks
#' @param num.motif the total number of motifs
rocRanks = function(ranks, num.motifs){
uranks = unlist(ranks)
max.rank = max(uranks)
roc = matrix(0, ncol=2, nrow=max.rank+2)
colnames(roc) = c("f... |
387ddee8654556a2cf8aec35f389515fafc5e47b | 802cd19e325687a8d5021af2966aeefcba4e104f | /covid_rent_burden/global.R | 46dfd4b4b47428af81aea1a4a0a269c602a36fca | [] | no_license | murray-cecile/renter-credit | a47ecf9bfda2af073610c7485c57c952e09588e6 | 7ea015d359a3e666680f310c7b065a299b992e34 | refs/heads/master | 2021-04-18T13:27:17.891577 | 2020-05-22T14:55:19 | 2020-05-22T14:55:19 | 249,549,513 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,256 | r | global.R | #===============================================================================#
# DEFINE OBJECTS AVAILABLE TO BOTH UI AND SERVER
#
# Cecile Murray
#===============================================================================#
library(tidyverse)
library(tidycensus)
#===============================================... |
55b16f501179ddbfe977cd6c600cb5a1758a72bf | 68c863b9d62695383d15e7ffdc8a13a38afafdc3 | /Exploratory_Data_Analysis/W4_CourseProject_2/plot4.r | 1d20c0bb8c7f6af22680bef1cea9b483abe455f3 | [] | no_license | tonoplast/datasciencecoursera | 4349e99109df4189d4dc5b79c023919aa412622b | 31373c3157307637e0e6fcaf53d23d454e18ab85 | refs/heads/master | 2020-08-05T21:26:30.389511 | 2020-04-15T08:27:48 | 2020-04-15T08:27:48 | 212,716,963 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,924 | r | plot4.r | # Fine particulate matter (PM2.5) is an ambient air pollutant for which there is
# strong evidence that it is harmful to human health. In the United States,
# the Environmental Protection Agency (EPA) is tasked with setting national ambient
# air quality standards for fine PM and for tracking the emissions of this p... |
1a4dcc94b3f1bbb840bacda86b374b28533bef4d | 6d0dad9419cea35d2c5f8472455efd6448c99e67 | /tests/testthat/test-DGR.R | 95b0a89e0ba7c2dfe3e40340681a8bebcb1e99f6 | [
"MIT"
] | permissive | ralmond/CPTtools | 224f0d720adf4003bd3a3cf76ca5ba8d1f315305 | 8ecbacd3997dd8a566048ade135b6c836fcc54a2 | refs/heads/master | 2023-08-07T18:45:07.408649 | 2023-07-18T15:56:35 | 2023-07-18T15:56:35 | 239,853,879 | 2 | 1 | MIT | 2023-07-18T15:56:38 | 2020-02-11T20:07:01 | R | UTF-8 | R | false | false | 302 | r | test-DGR.R | test_that("calcDPCTable", {
})
test_that("calcDPCFrame", {
})
test_that("calcDPCTable GR", {
})
test_that("calcDPCTable PC", {
})
test_that("calcDPCTable PC local-Q", {
})
test_that("calcDPCTable normalLink no parents", {
})
test_that("calcDPCTable normalLink parents", {
})
|
6fefcde71a6f9c7c42b5b67227c3d3cab353a730 | c52c9afa5dc0edf982b26fd2c6fba3d8ad5f3eeb | /R/alert20-package.r | 739a1b33425dba04de8781b800e2ce0ec8885bda | [] | no_license | kevin--zhao/alert20 | 3eaa615be9f0eab821f341bb024b9cf83d63cd7b | e5e76af8d02858145c8dfc54594d151874b85e9d | refs/heads/master | 2016-09-05T22:30:21.695751 | 2015-01-05T10:04:25 | 2015-01-05T10:04:25 | 28,801,461 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 56 | r | alert20-package.r | #' alert20
#'
#' @name alert20
#' @docType package
NULL
|
73298fccebaa1c5f0754da260c6123b286936fdb | 34f5587daf6b1a7b34b9b694d900128923ec7d05 | /R/ANN_predictor.R | 6de0d44c14b5795ff9e8e6bf6eab1e04e897c0cf | [] | no_license | BJLIYANLIANG/ids-1 | 2c6bd2ae6fc66fc4bc774b987193bfbb310b67ee | 7c57610651c7c5aa494988a7a1b031e442477b98 | refs/heads/master | 2023-03-22T17:39:49.515208 | 2015-12-13T00:30:04 | 2015-12-13T00:30:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,556 | r | ANN_predictor.R | #!/usr/bin/env Rscript
#---- Dependencies ----
dependencies <- c("neuralnet")
for (d in dependencies) {
#cat(d, "\n")
# Try to install if not found
if (!(d %in% rownames(installed.packages()))) {
install.packages(d)
library(d, character.only = TRUE)
}
#---- Config ----
configure <- function(day = 14... |
34cd55b23af8140e03aad4203dc1cb6d383f4994 | 1bfe8a5f4c781641ed35b230d90d2da1f9503ee4 | /Renxu/evaluate_reproducibility_09.03.2017.R | 41fabf031825676a892880d47b2f2be020752864 | [] | no_license | chang-che/Work | 7b62814d0f718778fb6883e8f186ccc966ce6428 | e9c94e58eb91d2af994287c1c229a5a486b29883 | refs/heads/master | 2020-03-10T20:50:25.235845 | 2018-05-06T19:16:07 | 2018-05-06T19:16:07 | 128,847,851 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,449 | r | evaluate_reproducibility_09.03.2017.R | ## compare the estimated log2FoldChange from DESeq2 output
library(glmnet)
load(file = '/export/home/xurren/WTCProject/Results/lfc.RData')
load(file='/export/home/pfkuan/WTCproject/Epigenetics/Results/Results_Feb2017_RNASeq/cv.fit_DemoCellAdj_17Feb2017.RData')
dataPathRNASeq <- '/export/home/pfkuan/WTCproject/Epigenet... |
88707f0e56873d5297109bce44168340a523eadb | a66ce47010e69b5279e5c3df0b619a1fa27b7f41 | /set up.R | 1b1786450a5bca6ffe79a3f1c1ff698e85dbd2c8 | [] | no_license | Moohan/mode_of_birth_dashboard | b9696b3d2d20317378e3c88f34edf426e9c5c1a6 | 7a310287c58224b56164264e310b3e787a6b43d5 | refs/heads/master | 2020-05-28T06:43:45.785966 | 2019-09-30T15:13:11 | 2019-09-30T15:13:11 | 188,911,929 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 779 | r | set up.R | library(tidyverse)
library(janitor)
library(tidylog)
data <-
read_csv(
"https://www.opendata.nhs.scot/dataset/df10dbd4-81b3-4bfa-83ac-b14a5ec62296/resource/8654b6d8-9765-4ced-8e9b-4611aa4596eb/download/12.1_delivery.csv"
)
ca_names <-
read_csv(
"https://www.opendata.nhs.scot/dataset/9f942fdb-e59e-44f5-b... |
cdc576174df3cde34f6eca15a803e37abb3545ed | 7204e3bfeea08327b4bda576b082b9dd5e254046 | /man/BootstrapEdgeDistn.Rd | 6d86103de5d956f9441965df4342d5a0a601a007 | [] | no_license | EpidemiologyDVM/duke-rnet-quick | fd2717c3146b2b4a38af494820bd28b1033a3d80 | b979af770522aff93d736c0d0c4a9f0f7b17c0a7 | refs/heads/main | 2023-05-01T16:26:25.930895 | 2021-05-26T16:35:46 | 2021-05-26T16:35:46 | 371,102,574 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,469 | rd | BootstrapEdgeDistn.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Bootstrap_Edge_distn.R
\name{BootstrapEdgeDistn}
\alias{BootstrapEdgeDistn}
\title{Penalized Partial Correlation Distribution Estimates}
\usage{
BootstrapEdgeDistn(
x,
L1,
vertices = NULL,
subset = NULL,
B = 500,
n_b = 0.5,
repl... |
cf43b12ca153d1980a1cf70a0bab35d75ee10ce4 | 94b0d2bfb62c711572df8198b2f1529e8ce7927c | /experimenting with dist mat.R | 3094278cec6e39d1292de89f7cc161b58a354349 | [] | no_license | GeneralRaspberry/Breaking-down-the-epidemic-code-for-the-purpose-of-diagnosing-the-dispersal-kernel-Chapter-1- | 1b2e03ffa82eebfa99cc77175c7a028fc1c44c5b | 45ba019509539b76d6a4c235ae6e059e630e3ca6 | refs/heads/main | 2023-05-31T01:34:16.324493 | 2021-06-13T18:51:48 | 2021-06-13T18:51:48 | 374,421,096 | 0 | 0 | null | 2021-06-13T17:10:02 | 2021-06-06T17:21:20 | R | UTF-8 | R | false | false | 5,310 | r | experimenting with dist mat.R | packagedelivery<-function(fry,leela){
if(fry == TRUE){
require(leela,character.only = TRUE)
} else{
x<-grepl(leela,search())
n<-0
for (j in x){
n<-n+1
if (j == TRUE){
detach(pos=n, unload=TRUE, character.only = TRUE)
}
}
}
}
packagedeli... |
7c9cfd44edc929c07092d66797bd845954de9ac1 | 11e0c11a69bed57c00859cb80b61a41d437c06f3 | /users/analysis/SUS/non_param_tests.R | 18c56ab19ec04f7e460b2b4aa0d9bb2d96813cc6 | [] | no_license | janisso/BeatBopper | 7771a12b9c791873d3f8f0b2dd0dcff8a971212f | 5bea60bbb273b49caea71de70978bf4cd08b67cf | refs/heads/master | 2022-03-04T12:29:26.167493 | 2019-11-20T10:24:45 | 2019-11-20T10:24:45 | 157,095,197 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 606 | r | non_param_tests.R | #NON parametric tests
#taken from http://rcompanion.org/handbook/F_01.html
rm(list=ls(all=TRUE))
.rs.restartR()
library(psych)
library(effsize)
library(coin)
library(dplyr)
library(BSDA)
A = Naive#c(2,4,3,1,2,3,3,2,3,1)
B = Phase#c(3,5,4,2,4,3,5,5,3,2)
cliff.delta(A, B)
wilcox.test(A,B)
g = factor(c(rep("A", leng... |
3bbd82b3cae4dd6a218bf7693f0c00678bb646ee | 4caeaa501d9497ddddbf033904e019974e0e1b7e | /assets/2.temporal_variation.R | 8d1e59fc49005a81e8983c06a51cdb11c859633c | [] | no_license | macroevolution/workshop-OSU | b545e8612cb8d0185ec78e711c5e23482be04b09 | a43b40a6868a4a2730f86eac1ea9470763d1517a | refs/heads/master | 2021-01-11T14:01:22.563366 | 2017-09-05T16:59:19 | 2017-09-05T16:59:19 | 94,931,335 | 3 | 2 | null | null | null | null | UTF-8 | R | false | false | 980 | r | 2.temporal_variation.R |
#----------------------------------------------
# Exercise 4: Gamma statistic
warbs <- read.tree("data/warblers/warbs.tre")
gammaStat(warbs)
skinks <- read.tree("data/skinks/skinks216.tre")
gammaStat(skinks)
#-----------------------------------------------
# Exercise 4b: Simulate trees with time-dependent ... |
a91ff6be94c4ffd82a35b06a14caf7427b650446 | 90f1fe26d2c514e8e07e9afb668a5bc7e48a8dce | /Complex_Predictors_Demo.R | ef96da76822c7a12229b9586c74021e34692bd93 | [] | no_license | awahl1/Stats_Course_Supplements | b7889c29fd732620d9594ab073747dd1e8d5edeb | 4dd9903597394c9d261e6e7c7f924851216eecc0 | refs/heads/master | 2021-06-19T21:47:05.264559 | 2017-07-26T14:07:23 | 2017-07-26T14:07:23 | 98,427,959 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 19,762 | r | Complex_Predictors_Demo.R | library(ggplot2)
library(car)
library(pastecs)
library(effects)
library(gvlma)
###Interaction between two interval/ratio predictors (multiple regression)
#Outcome variable is how crazy someone is
#Predictor 1: how many beers per week that person drinks
#Predictor 2: how many years they've been working at the unive... |
93a7ff625fb0d4c814c8d3c2b1a99dfa94a658e3 | b8712324e3195a76d138f8063ad3638ff7dc2e8a | /twitter_bot.R | b631b95315c151425129b34b7aa7266ccf4f7e22 | [] | no_license | albnd/lgbtrights_bot | c4d9678b119b86dfd374e3360c09c20ed2540efd | 579fe8c20143b69f81ceb1b810f2f55b644ab849 | refs/heads/master | 2020-03-19T06:53:03.567250 | 2018-06-04T08:03:44 | 2018-06-04T08:03:44 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,094 | r | twitter_bot.R | #Assuming that the table was nicely formatted, which it isn't
library(rtweet)
library(here)
library(jsonlite)
library(rvest)
setwd(here())
wait_in_r <- T
wait_duration <- 211*60 #Number of seconds to wait if wait_in_r == true
flag <- F
continents_vec <- c('https://en.wikipedia.org/wiki/Template:LGBT_rights_table_Af... |
ca2fb6be43c9285c87f799b8afc1cd2054d20c7e | bb8f905a8fd6c482f5e5201eda2148de4ebebcea | /src/R/load_exac.R | 5cbf376d25d004ad0e4c1349888ac56fa5c24285 | [] | no_license | birndle/ExAC_analysis | 6063d85524838119dfa23dd69618e23363919af0 | ad4840de84792d9d02630c356e210fa0728f9f1f | refs/heads/master | 2021-01-25T05:34:17.918872 | 2015-04-07T05:34:50 | 2015-04-07T05:34:50 | 32,942,036 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 460 | r | load_exac.R | exac_all <- get(load('R_data/exac_pass.RData'))
exac_lof <- subset(exac, lof == 'HC' & is.na(lof_flags) & use)
pops <- c('afr', 'fin', 'nfe', 'amr', 'sas', 'eas')
pop_sizes <- apply(exac_lof[,paste("an",pops,sep="_")], 2, max)/2 # in people number
world_pop_sizes <- data.frame(
row.names=c("eas", "sas", "nfe", "Middl... |
1102b2c9c948ec17a9bf4a3a17b24721f94ed460 | 665f3842c37fc5730c9cefee95ff480cabf0ae36 | /man/estimateTau.Rd | 5d66219b9ae8ce98e6a47d0e696f4a072bba4848 | [] | no_license | BarkleyBG/multilevelMatching | c0bc128c81d1513c52dda7eafa3b6bc7b6ee1aa6 | 58e7a0b2a612671d4d0214f0d545ca90bd599d70 | refs/heads/develop | 2021-01-23T04:13:49.838974 | 2018-03-03T16:54:11 | 2018-03-03T16:54:11 | 86,175,312 | 0 | 0 | null | 2018-01-26T17:04:46 | 2017-03-25T17:25:14 | R | UTF-8 | R | false | true | 1,540 | rd | estimateTau.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/estimateTau.R
\name{estimateTau}
\alias{estimateTau}
\title{Calculate the estimates of population-level estimands (e.g., tau).}
\usage{
estimateTau(trt_levels, mean_Yiw, num_trts, num_contrasts, N, M_matches, Yiw,
Kiw, sigsqiw, W, ...)
}
\a... |
d9638f8742487445ae97411f54c7ee86b57dc371 | 0ead36631dc316f9f7577dd59b4fa7cb610829f3 | /man/ET.default.Rd | eebbdd57d7d196dbf3496b8a1f73c4eff81aab41 | [] | no_license | cran/Evapotranspiration | 81d2a94ac383d12fdbc9ccf1960caba62f23ee01 | 8e4a3936d6747728d4812f9415cdf01d47167329 | refs/heads/master | 2022-01-24T11:17:42.959617 | 2022-01-10T04:22:41 | 2022-01-10T04:22:41 | 17,679,056 | 8 | 12 | null | 2017-06-07T03:24:09 | 2014-03-12T18:50:23 | R | UTF-8 | R | false | false | 570 | rd | ET.default.Rd | \name{ET.default}
\alias{ET.default}
\title{ET Formulations(Internal)
}
\description{
And internal function to select the ET formulation to use when \code{\link{ET}} is called, without user-specified ET model.
See \code{\link{ET}} for details.
}
\author{
Danlu Guo
}
\seealso{
\code{\link{ET}}
}
% ... |
d19308569f445079aeee7d8018b0f82df4156b5a | dbc6954f25fb1fa4f584eb3e6c7f6b90d1766fbb | /MVE_BASED/models.r | 50a31ed583099f0352fff79182c26e8afb113fca | [] | no_license | RannieWan/diversity_in_e | 05da7390903972e3574861d61fa3344f3c668611 | 72649009420c0ebc068ecd81c2f36a4dc6f3b6a6 | refs/heads/master | 2023-03-10T17:07:20.147042 | 2021-03-01T08:54:23 | 2021-03-01T08:54:23 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,460 | r | models.r | library(raster)
library(rgdal)
library(rgeos)
library(MASS)
library(cluster)
library(dplyr)
source("addEllipse.R")
source("genCircle.R")
NDquntil <- function(nD, level) {
n <- floor(nD * level)
if (n > nD)
n <- nD
return(n)
}
in_Ellipsoid <- stats::qchisq(0.95, 2)
args = commandArgs(trailingOnly=TRUE)
group... |
b965feb1b6bd6c14b6f782522ada75516da98268 | ba77311895a3bfc6e4006e9600041d3d2185c4bd | /r-workshop.R | abc1286699117ce06ad0733e4e62bd80f2f4b284 | [] | no_license | milesc06/r-workshop | 80421e3f205c6e9f11235a5fc692d971187b2c4f | 98b01c7455fb6e086563629883e0c117c7d83a9c | refs/heads/master | 2020-12-21T21:41:39.005296 | 2020-01-28T19:03:10 | 2020-01-28T19:03:10 | 236,571,232 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 123 | r | r-workshop.R | #new file
install.packages("usethis")
library(usethis)
use_git_config(user.name="milesc06",user.email="miles@rstudio.com")
|
edf5bf9e5a91892b69a2eb45c24721fee651802d | 4efbe1d55ea0f650168d1323d1813ea0eaa2ca8b | /misc/Stepwise_OFPGAM.R | aa684e083b0d70cceb10f79a3d40ac010c9c0201 | [] | no_license | panders225/semiparametric-regression | d8e7470576f7d3fd988ba7e677eaceed3216caea | 1fd5a22f4283daf856aad61af2f4abccfa4fc324 | refs/heads/master | 2021-05-11T08:32:43.127850 | 2018-04-24T00:55:53 | 2018-04-24T00:55:53 | 118,055,099 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,724 | r | Stepwise_OFPGAM.R | ########## R script: Stepwise_OFPGAM.R ##########
# Stepwise fit for the Poisson generalized additive model
# fit to the physician office visits data on both the
# link scale and the response scale.
#
# I do only quasilikelihood in this analysis
#
# Because the stepwise regression uses gam and not mgcv, you d... |
bbd64c9a8cee355fb349367a5a908400a1e6623c | 49bc4a40b43070e91367f520db0215d40faf5eb0 | /createNodes.r | 8cd4620237582606395cb635d5c711633a817dce | [
"MIT"
] | permissive | bevvvvv/DS220Proj2WineReview | d8846324036a1e914bf933aac93c815f4cd0b4c4 | bfc7a4c5195cb3c17d0eecaa051598c502722d9d | refs/heads/master | 2020-05-07T11:24:33.381625 | 2019-04-23T19:54:24 | 2019-04-23T19:54:24 | 180,459,872 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 989 | r | createNodes.r |
library(data.table)
library(mdsr)
wineInfo <- fread(file = "D:\\GitRepos\\DS220Proj2WineReview\\winemag-data-130k-v2.csv")
wineInfo <- wineInfo[1:10000,]
wineInfo[taster_name %in% c(""),10] <- "Unknown"
wines <- wineInfo %>%
select(variety, price, winery, taster_name, title)
wines <- wines[!duplicated(wines[,c('... |
c0c685f2ebf87ad6192b500ffac974d00fc63814 | 63f8a1d7f06526022d65534ff044376f0a15cb9a | /man/preproc.Rd | 0c41e9abf11642307da31f0599344c955bd6b7f1 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | mgondan/rolog | b28722e9913540c51cb53ece0bb125a53bc83f41 | 96ccd6a5e815cb8304566a61f9de9758b6efe176 | refs/heads/main | 2023-08-11T16:51:53.486382 | 2023-07-21T07:34:36 | 2023-07-21T07:34:36 | 372,880,585 | 6 | 2 | null | 2023-07-21T07:33:00 | 2021-06-01T15:37:38 | Prolog | UTF-8 | R | false | true | 578 | rd | preproc.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/preproc.R
\name{preproc}
\alias{preproc}
\title{Default hook for preprocessing}
\usage{
preproc(query = quote(1 <= sin))
}
\arguments{
\item{query}{the R call representing the Prolog query.}
}
\value{
The default hook translates the inequalit... |
0fbf07d9d622d32dbd627f7e5746efad48ab75bb | f42d1165f3ebcff06bc2d555d42a2d4770db687c | /R/get_png_logos.R | 419782ccba5c2a7d7d6730edfbc637d0ff7a9ea2 | [] | no_license | IvoVillanueva/mlbstatsR | 11fc14d7d6a070d46dcde76fc451e204333afe66 | 2f20733d75be7cc11d88c452e4eea7d47788d750 | refs/heads/main | 2023-08-04T01:33:34.286957 | 2021-09-09T17:57:27 | 2021-09-09T17:57:27 | 361,255,437 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,642 | r | get_png_logos.R | #' @title 4 png Logos & colors for MLB (baseball)
#'
#' @description MLB Profesional league baseball data table , logos and colors
#'
#' @return Logos and colors
#' @export
#' @importFrom jsonlite fromJSON
#' @import dplyr purrr
#' @importFrom utils sessionInfo
#' @importFrom janitor clean_names
#' @examples
#'
#'
#' ... |
b3b91b92bc36bcfc26dab47600c48298781acc9a | 6f6a9faa7cea6501b170a3b584b7d55abff6546f | /stan_examples/gp_stan.R | 14bf38447967a3d593abb8e0e1b7f345b506261d | [] | no_license | jiunsiew/bayesian_machine_learning_r | 6e7e9c869122c163da227105e84b66921bf1e6d9 | 54089bb063396b690c4b6be46383596adcda5fae | refs/heads/master | 2021-01-15T03:40:39.423569 | 2020-03-16T04:05:34 | 2020-03-16T04:05:34 | 242,866,515 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,447 | r | gp_stan.R | library(data.table)
library(magrittr)
library(rstan)
library(stringr)
rm(list = ls())
rstan_options(auto_write = TRUE)
options(mc.cores = parallel::detectCores()-1)
## run the stan file
nSamples <- 25
nNew <- 1
x.star <- as.matrix(seq(-5, 5, len=nSamples))
stanData <- list(N=nNew,
nr_1=nSamples,
... |
2541395c2b573bda021b7af766155803cb65af08 | 884903fd3978d5a35e531d4738154fe225a32657 | /Euphrates/GWAS experiment/Composite functional mapping.R | 2c5ab091a98137fe66c68112ad609e0c5cc99a51 | [] | no_license | CCBBeijing/PPMultilayerNetwork | ec1b9f7b430f0e7299ddc1336a54779c6e948332 | 794fc4a0bc0529ddf551d5c1ae7ec1388f21ff13 | refs/heads/main | 2023-04-07T12:46:08.534260 | 2022-05-31T00:24:05 | 2022-05-31T00:24:05 | 359,453,869 | 1 | 0 | null | 2021-06-13T23:39:49 | 2021-04-19T12:37:19 | null | UTF-8 | R | false | false | 3,642 | r | Composite functional mapping.R | library(mvtnorm)
get_miu3 =function(B,t){B[1]/(1+exp((4*B[2]*(B[3]-t)/B[1])+2))}
SAD1_get_matrix = function(par, times = t, options=list()) {
n <- ifelse (is.vector(times), length(times), NCOL(times) )
phi<- par[1]
v2 <- par[2]
tmp <- (1-phi^2)
sigma <- array(1, dim=c(n,n))
for(i... |
fc28ad000b2ee717edb9f92a16a0086ef5e65bc2 | a5bbcb2b8c60e803c0bc6c5f3b6acd6f76f608cd | /man/popover.Rd | c0fe0e610178f04f9e41efd6bc88f5f5f20553ca | [] | no_license | DataXujing/shinyBS | fdfaf0784b40c3693e43ade945bec22efa411bd1 | 6bfa2a44b6d05cebd251d7470b039878510fce3d | refs/heads/master | 2021-07-05T21:12:42.048441 | 2015-01-23T15:12:03 | 2015-01-23T15:12:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,039 | rd | popover.Rd | \name{addPopover}
\alias{addPopover}
\alias{bsPopover}
\alias{removePopover}
\title{
Twitter Bootstrap Popovers
}
\description{
Functions to add Twitter Bootstrap popovers in shiny.
}
\usage{
addPopover(session, id, title = "", content,
placement = "right", trigger = "click")
bsPopover(id, title =... |
3722ea46fc7d8224052c747c89225333c4abdae6 | dd521637dcf91fe0591cd7aa5bccf7e0b7eb15c5 | /191015 Lecture 5/Class05.R | ec647e6077461a695715a397e3455635ebfa8476 | [] | no_license | Mark-Jacob/BIMM143 | 60bcd19509526f9bd7d024801ef0556de51fc2c8 | 2dba92d53460034d9ad641487fd190ac667c4c87 | refs/heads/master | 2020-09-01T00:29:32.004799 | 2019-12-07T06:43:15 | 2019-12-07T06:43:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,875 | r | Class05.R | #' ---
#' title: "Class 05: Data exploration and visualization in R"
#' author: "Mark Jacob"
#' date: "October 31st, 2019"
#' output: github_document
#' ---
#Class5 Data Visualization
x <- rnorm(1000)
#Looking for help
#EZ commands to use in the future
mean(x)
sd(x)
#Numbers will differ among people due to different... |
ffdba39901e9cf3868b6920965f8a8d326958db4 | 143f25eb68b88b975eb576ea95c731e932b55a38 | /man/getScriptWords.Rd | acbc283545d0964763cb6bee86d2d505c188d660 | [] | no_license | lockedata/TextAnalysis | 87fe2dd3b752cb9547ffd2606fb24f27bd8c43d3 | 607203fb3f80abe470cc904454eb8ee666659f2f | refs/heads/master | 2021-01-23T08:00:11.059081 | 2019-11-21T18:24:51 | 2019-11-21T18:24:51 | 86,470,408 | 4 | 2 | null | null | null | null | UTF-8 | R | false | true | 521 | rd | getScriptWords.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getScriptWords.R
\name{getScriptWords}
\alias{getScriptWords}
\title{Get words used in Monty Python movie lines, with stop words removed}
\usage{
getScriptWords(offline = FALSE)
}
\arguments{
\item{offline}{Use an offline copy instead of fetc... |
98e5323b9bf1a9411c5ea64a32262035098fb830 | 38434b7cc32750b7c6d6d133e5657bb3757a7230 | /auxiliary.R | 57078e2ce150effb8caaf52e98e9d8b3281a981f | [] | no_license | tanujitdey/causal-me | 896fb7e2e1b0043a010de645c66dec352515c7c3 | f64b243c7230e2474acd71a26c25d27b33ac5e53 | refs/heads/master | 2023-08-14T09:59:57.038265 | 2021-10-01T02:11:35 | 2021-10-01T02:11:35 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 814 | r | auxiliary.R |
# regression calibration function
pred <- function(s, star, w, sl.lib = c("SL.mean", "SL.glm", "SL.glm.interaction", "SL.ranger", "SL.earth")){
# set up evaluation points & matrices for predictions
ws <- data.frame(w, star)
ws.tmp <- data.frame(ws[!is.na(s),])
s.tmp <- s[!is.na(s)]
colnames(ws.tmp) <- col... |
ee12b42839a5730c5c8227d4633e7ad487c16357 | 74ce34dfcd0971aa389b379b7484fddde4cdffc9 | /man/bsearch7.Rd | b5122e4f7f478e00bb2f589b2c78f2defdf1e313 | [] | no_license | cran/stackoverflow | 294b5425c89167d3278faa19d88905f821ef194f | 3bd6c79acafa3ba9caa681a740cae22da2c18416 | refs/heads/master | 2020-04-04T03:44:41.465303 | 2020-01-10T03:50:02 | 2020-01-10T03:50:02 | 35,567,770 | 2 | 1 | null | null | null | null | UTF-8 | R | false | true | 713 | rd | bsearch7.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bsearch7.R
\name{bsearch7}
\alias{bsearch7}
\title{Efficient binary search for character vectors}
\usage{
bsearch7(val, tab, L = 1L, H = length(tab))
}
\arguments{
\item{val}{values}
\item{tab}{table to find values in}
\item{L}{lower bound}... |
aa70b19245c84d137deb10f4a6490d48091da257 | 7880f7fb7eead03f1e655f405f6e770b7e3e8ead | /R/sgph.R | e5d0c4a608cf64decafadc330a7bf7b0f9088e09 | [] | no_license | tselert/sgholidays | c6f3f7afd9410bb49f27386edf69823c4752e9b3 | 5570490c310515fc9cfc897f8e57ed7cb043d0c9 | refs/heads/master | 2023-07-19T11:20:28.018084 | 2021-09-03T00:48:22 | 2021-09-03T00:48:22 | 399,330,903 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,922 | r | sgph.R | #' Data of Public Holidays in Singapore
#'
#'This dataset contains all the dates of gazetted public holidays (PH) in Singapore since 2008. It also contains dates of off-in-lieu (see Note on OIL below).
#'This dataset will be updated annually as per the official website of the Ministry of Manpower Singapore.
#'
#' Sin... |
9ee529cea0144986280533317f0f5d438d1cd32f | 06382b9d2a348003ffed076537f0ad9cb0a63f2f | /run_analysis.r | aff34c6ca56279d44aaaf776431734f279585bfb | [] | no_license | avikmoulik/data_cleaning | 42f3cffc743dfd530e7017df7503562d9ae673fe | adefa5ca589541ebee8ec234108f2b8f372e2fae | refs/heads/master | 2021-01-10T14:01:58.193811 | 2015-09-27T13:12:14 | 2015-09-27T13:12:14 | 43,245,448 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,200 | r | run_analysis.r | ## reading all test files
##----------------------------------------------
subject_test<-read.table("/home/avik/rfile/UCI HAR Dataset/test/subject_test.txt")
x_test<-read.table("/home/avik/rfile/UCI HAR Dataset/test/X_test.txt")
y_test<-read.table("/home/avik/rfile/UCI HAR Dataset/test/y_test.txt")
## reading all trai... |
2e0c4cc923a19cc80ce50807770e1b4033933fe4 | 0b535741c301358fd1510a8db3f5fa2a2c479862 | /man/getXcoords.Rd | 92415b19b85382c2107e02400f2096067074a500 | [] | no_license | arcolombo/qusage | 83f7514159c5881035c3dc2597b67d9a4c0a9267 | 6085f2cbac1883af2e83d249db4726ea6606d6e3 | refs/heads/master | 2021-01-17T08:56:52.732039 | 2015-10-13T19:59:53 | 2015-10-13T19:59:53 | 50,695,728 | 1 | 0 | null | 2016-01-29T22:31:31 | 2016-01-29T22:31:31 | null | UTF-8 | R | false | false | 2,483 | rd | getXcoords.Rd | \name{getXcoords}
\alias{getXcoords}
\title{Get the X coordinates for the points of the PDF}
\description{
Calculates the x-coordinates for the PDF of a given pathway.
}
\usage{
getXcoords(QSarray, path.index=1, addVIF=!is.null(QSarray$vif))
}
\arguments{ ... |
1a2b19067fd54f13451c3cc06cac03da9352c95c | 61c7597aad45fbd3a648f6629b7d813222cf3766 | /man/add_grid_layer.Rd | 1331dc3d1c902d46ac49ef37d0c1dc6f84a836bc | [
"MIT",
"BSD-3-Clause"
] | permissive | xytczh/deckgl | 3d7ba021dcaf3b59860510d66a345e2b93acadec | 3d38b3e4a7c718030efe8e61090f0b01beb92255 | refs/heads/master | 2022-04-21T16:24:28.118634 | 2020-04-13T17:19:57 | 2020-04-13T17:19:57 | 258,428,819 | 1 | 0 | NOASSERTION | 2020-04-24T06:42:16 | 2020-04-24T06:42:15 | null | UTF-8 | R | false | true | 1,589 | rd | add_grid_layer.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/layers_grid-layer.R
\name{add_grid_layer}
\alias{add_grid_layer}
\title{Add a grid layer to the deckgl widget}
\usage{
add_grid_layer(deckgl, id = "grid-layer", data = NULL,
properties = list(), ...)
}
\arguments{
\item{deckgl}{A deckgl wid... |
4061395a6b184983320509179c992648815d825b | 07ab8b101571b2b3c991368e0d7791e4b7abc342 | /script.r | 78ee2c55e0a4c9f016c24993723ef0cf04f340be | [] | no_license | x5pid/CRYPTO | 294db9f02c1a0569e966a225ad79f7ebfd185cf2 | 213a91d14a36e1032727c6690da3e0c156e605f0 | refs/heads/master | 2021-04-03T10:23:50.547434 | 2018-04-08T21:00:45 | 2018-04-08T21:00:45 | 125,222,457 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 138 | r | script.r | #! /usr/bin/env Rscript
d<-read.table('collisions2.txt')
d <- unlist(d, use.names=FALSE)
cat(min(d), max(d), mean(d), sep=' ')
cat('\n')
|
efbed10e630424a8c34e122d48c502430b73b3c0 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.developer.tools/man/codepipeline_list_tags_for_resource.Rd | 8aa18f7d8e95ce7d6971a158dd36b2cf505823a8 | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 1,017 | rd | codepipeline_list_tags_for_resource.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/codepipeline_operations.R
\name{codepipeline_list_tags_for_resource}
\alias{codepipeline_list_tags_for_resource}
\title{Gets the set of key-value pairs (metadata) that are used to manage the
resource}
\usage{
codepipeline_list_tags_for_resour... |
2c82bc3aee2e415ef98d475b4ba6c282cabc6e07 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/MSnbase/examples/normToReference.Rd.R | a8b7bd29d996e8448f79de41e695e27630d36c94 | [] | 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 | 398 | r | normToReference.Rd.R | library(MSnbase)
### Name: normToReference
### Title: Combine peptides into proteins.
### Aliases: normToReference NTR
### ** Examples
library("MSnbase")
data(msnset)
# choose the reference run automatically
combineFeatures(msnset, groupBy=fData(msnset)$ProteinAccession)
# use a user-given reference
combineFeatur... |
972b0d5c6a43c1a7d91e717b42414f90ced1cb32 | c7e0ea5ce7aa2a6d322bf34613f4373b502abdb8 | /Lab Homework/lab 7 homework/Lab 7 Homework Problem 2.R | 787a67b91fd441571453fe7c22bc6c49ca4df9e1 | [] | no_license | alliyahg/BIS15W2020_agalvan | eb23623123a449d5475641651842dfae62b604cf | 36845e30c487b77bb9d2f4b644f551d977677925 | refs/heads/master | 2020-12-13T12:08:49.156454 | 2020-03-13T01:25:52 | 2020-03-13T01:25:52 | 234,412,044 | 4 | 0 | null | 2020-01-30T17:48:52 | 2020-01-16T21:07:27 | HTML | UTF-8 | R | false | false | 906 | r | Lab 7 Homework Problem 2.R | library(tidyverse)
library(shiny)
library(shinydashboard)
UC_admit <- readr::read_csv("data lab 7/UC_admit.csv")
UC_admit %>%
mutate_at(vars(Academic_Yr), as.factor) %>%
mutate_at(vars(Ethnicity), as.factor)
ui <- dashboardPage(
dashboardHeader(title = "Ethnicities Data App"),
dashboardSidebar("UC System"),... |
4f3cf62abb5a7e65bc98ca78d49ed0ed3be2ee52 | cb4ef01ac32a5c72abd6977ae13edc97d2b18d0f | /R/dci.R | 1ca721b82af46d9cff84eed25119bf590b8ad543 | [] | no_license | jsta/dciR | 735627ea3e1ac3f63e7a2be7122f1f353b60df14 | f255af7e7e32cb2aeea371e515c74f536ae4fd1e | refs/heads/master | 2021-01-17T08:10:44.051394 | 2016-07-31T00:15:56 | 2016-07-31T00:15:56 | 34,424,333 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,135 | r | dci.R | #'@name dci
#'@import RBGL
#'@title Directional connectivity matrix
#'@param mat matrix 2D matrix of zeros and ones, in which ones represent the landscape patch of interest. The axis of interest along which directional connectivity is computed is dimension 1 of this matrix.
#'@param xgrain pixel length in cm (i.e., alo... |
0b136c2b7e11ca95f6fc7cb008149d6b79c84555 | 5cc230ad95dfcea7c8780e2d4c44a661536ff3ad | /R/dependencies.R | 15e75e8ccfccef9fa31430ba6e7f1af0be5b278d | [
"MIT"
] | permissive | timelyportfolio/remiotic | 1abeb01a09c8adfaa2a9dd05e43f13e7aa8f1065 | ab33d051e8ba68633817b5b19c3cf0cda07d1efd | refs/heads/master | 2021-03-31T01:02:48.336346 | 2019-07-02T02:40:04 | 2019-07-02T02:40:04 | 124,822,933 | 7 | 0 | NOASSERTION | 2019-11-02T21:30:22 | 2018-03-12T02:29:41 | HTML | UTF-8 | R | false | false | 722 | r | dependencies.R | #' Dependencies for g2, bizcharts, and data-set
#'
#' @return \code{htmltools::htmlDependency}
#' @name dependencies
NULL
#' @rdname dependencies
#' @export
dep_corejs <- function() {
#shim/polyfill for ES5 and ES6 so react will show up in RStudio Viewer
#https://unpkg.com/core-js@2.5.3/
htmltools::htmlDependenc... |
85bb5f562ab8e7af67a7251407685090aad29b7a | f672121ef56b834ae5230cacb90fa97676fec1f9 | /Assignment 9.1.R | be406e322e02f0523670da6aa56155b46aa7dd96 | [] | no_license | adhishree1001/Assignment-9.1 | e46f4a33c3078dbb0ebfd65e3d878b0eeb7c23d7 | 259af099465a1e90420e8ff8b555f2d1804dbc7d | refs/heads/master | 2021-05-12T09:16:33.365882 | 2018-02-25T20:52:19 | 2018-02-25T20:52:19 | 117,312,334 | 0 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 1,467 | r | Assignment 9.1.R | #1. If Z is norm (mean = 0, sd = 1)
#Find P(Z > 2.64)
pnorm(2.64, mean=0, sd=1, lower.tail=FALSE)
#Find P(|Z| > 1.39)
answer <- 2*(1-(pnorm(-1.39, mean=0, sd=1, lower.tail=FALSE)))
answer
#P(|Z| > 1.39) = P( Z > 1.39) + P( Z < -1.39) = [1 - P( z < 1.39)] + [ 1 - P( z - 1.39)] =2*[1 - P( z < 1.39)] = 2(1 - 0.9... |
8326c9a0de16f57d9eda555509b3f616e01cf577 | 52a27a46e62e306fd2af922aa733d54019121061 | /pollutantmean.R | 0afead735ed3d7e406b44f6fc4bdecc91c93c4f1 | [] | no_license | RuchiJuneja1/RProgrammingCoursera | 8e8d40bb72e1bf87fb487448f6f3d3579edfc1e3 | ce58a024205989de289a73440589441a2803b6a9 | refs/heads/master | 2021-03-12T19:59:31.154943 | 2015-02-22T15:43:14 | 2015-02-22T15:43:14 | 30,932,011 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,307 | r | pollutantmean.R | pollutantmean <- function(directory, pollutant, id = 1:332) {
## 'directory' is a character vector of length 1 indicating
## the location of the CSV files
## 'pollutant' is a character vector of length 1 indicating
## the name of the pollutant for which we will calculate the
## ... |
d3125defb9059847078b02638b53ed1b4c8922ba | faca9fb310e0f5d25206dd7fbd8bd059e6facefb | /R/vcf.R | 69177ae4d25c69e5fb0e46d5458f5907f643d338 | [] | no_license | imbs-hl/imbs | 505f534fb68cd2d8fc6a3847f36784245cab3111 | 2d3ec95b81ea84623f007c5364ab19789a85715c | refs/heads/master | 2023-08-11T08:33:42.695944 | 2019-09-05T20:01:22 | 2019-09-05T20:01:22 | 66,840,758 | 1 | 1 | null | 2018-01-29T15:02:18 | 2016-08-29T12:13:16 | R | UTF-8 | R | false | false | 2,658 | r | vcf.R |
#' Normalize VCF file to bi-allelic variants
#'
#' Converting VCF files to plink format has never been easier. However, there are a few issues related to some intrinsic limitations of the plink format. The first is related to the fact that variants in a plink file are bi-allelic only, while variants in a VCF file can... |
583ac085a6ff16204536f1de5fffe1fe37bf3ae2 | 3e6d16419caa195694378801400dea03e56f64a6 | /W3.R | f9ee1293c07e13cfe0117d17a809b753361528c3 | [] | no_license | pablovmurcia3/Getting-and-Cleaning-Data | cdd1849a89fa9667c32f69261435de98480217e8 | 1fa7a843a06fdad9f2bc7d98f068ce0c1065511e | refs/heads/master | 2022-11-21T00:30:01.588456 | 2020-07-20T15:15:27 | 2020-07-20T15:15:27 | 277,130,880 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 12,316 | r | W3.R | ################################################################################
# WEEK 3 #
#########################################################################... |
74fb452c1646c7f26ff83744c24aa1f5fde6bb25 | 4ae0fd50679cc020ce92ba065211791448145f61 | /Cluster_Analysis/partioning_cluster_analysis.R | f860c84d8c897a3cb3214da0a409de9fb377fbd1 | [] | no_license | JMunch/r_scripts | 8950b1d2f96a999b4dc961c8329f94e83a7b7a16 | 5085a6173f75aa77f8c678b35f33de49ae5eb429 | refs/heads/master | 2020-07-02T14:20:41.855956 | 2016-12-21T19:12:42 | 2016-12-21T19:12:42 | 74,302,585 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,969 | r | partioning_cluster_analysis.R |
# Installing and Loading Required Packages --------------------------------
library(cluster)
library(factoextra)
# K-Means -----------------------------------------------------------------
set.seed(123)
# Simuklate some data wiith two clusters
df = rbind(matrix(rnorm(100, sd = 0.3), ncol = 2),
matrix... |
9f6d426829140fb825069b3143e7dd4c800c61f5 | b96e92d86bd142159e4674c59c6fbaf730049802 | /R/vc_column_apply.R | b3813a5be80b3e71072a80193a5c284628430655 | [] | no_license | trinker/valiData | 0ac536b9ed0435ff27f61973d949e9036fc8c1ac | 59caaa67acaafb2508e90281812997464766d6f1 | refs/heads/master | 2022-06-09T05:59:46.696388 | 2022-05-12T18:25:54 | 2022-05-12T18:25:54 | 74,035,459 | 0 | 1 | null | 2016-11-17T14:37:24 | 2016-11-17T14:37:24 | null | UTF-8 | R | false | false | 1,328 | r | vc_column_apply.R | #' Apply Column Map to Dataframe
#'
#' Apply a column map from \code{read_column_map_dir} to a
#' \code{\link[base]{data.frame}}.
#'
#' @param data A data frame to run column-wise tests on.
#' @param colmap A column map from \code{read_column_map_dir}.
vc_column_apply <- function(data, colmap){
nms_lookup <- dplyr... |
5a82c9d615ca7955c7090889d88b772ef3e025e9 | fed52643ad87ddd5e791fe6f249fa6b5a56a0785 | /plot2.R | 14fafc96e423e5e36d95f1cc65d0f0cbe5a879b9 | [] | no_license | Lcollins91/ExData_Plotting1 | 65f0756fc3134968a30d23f9816d34e93617b07f | 6cb4efdbfa6e78e28386c6a99052cdbe7ab160b6 | refs/heads/master | 2021-01-21T06:27:01.072011 | 2017-02-26T20:56:55 | 2017-02-26T20:56:55 | 83,234,648 | 0 | 0 | null | 2017-02-26T19:30:35 | 2017-02-26T19:30:35 | null | UTF-8 | R | false | false | 867 | r | plot2.R | ## First need to load the data.
if(!file.exists("./data")){dir.create("./data")}
download.file("https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip", destfile="./data/Power.zip")
# Get the names of the files in the zipped data folder
fileName <- unzip("./data/Power.zip")
library(lu... |
e6f84988f6b7def04893868bca3f1b90c3f1abd1 | 6d4c39ba65bac38347ac6d65eafcae8f5b69bfaa | /Plot3.R | c26c64fd5cad14aed266bbdcf185b90eef2a8a4a | [] | no_license | TAAH71/ExData_Plotting1 | 8d6c4fb761718beddbb132f9de9f71a110fe15dd | 89759e5d4f23a140ca882452be4091f5beab25d0 | refs/heads/master | 2021-07-15T12:29:42.635901 | 2017-10-17T21:26:31 | 2017-10-17T21:26:31 | 106,662,189 | 0 | 0 | null | 2017-10-12T07:55:09 | 2017-10-12T07:55:09 | null | UTF-8 | R | false | false | 1,522 | r | Plot3.R | # Get file
setwd("C:/Users/Andrew/Documents/Coursera/4_Exploratory_Data_Analysis")
unzip("C:/Users/Andrew/Documents/Coursera/4_Exploratory_Data_Analysis/data/exdata_data_household_power_consumption.zip", overwrite = TRUE, exdir = "C:/Users/Andrew/Documents/Coursera/4_Exploratory_Data_Analysis/data")
powerdata ... |
384b7505c90adc5b93eea9aeecf4470f1a08e024 | ea6469c85242a4df99d52823f96cff53078d3b86 | /congestion_metric.R | d324cb37afb349e1bda213cb13cd9d7885744d68 | [] | no_license | snohan/trafikkdata | 7ff2257467bd1425dbbbf5231542bd335019a7c7 | 1591b4ef847a9bf54fe5b1b3789bf3f1c4d11b52 | refs/heads/master | 2023-08-14T02:03:42.136163 | 2023-08-04T10:51:46 | 2023-08-04T10:51:46 | 159,170,326 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,674 | r | congestion_metric.R | # VbV data from Kibana
library(tidyverse)
library(hms)
base::Sys.setlocale(locale = "nb.utf8")
source("H:/Programmering/R/byindeks/get_from_trafficdata_api.R")
source("H:/Programmering/R/byindeks/split_road_system_reference.R")
# Literature
# A Survey of Methods and Technologies for Congestion Estimation Based on Mu... |
3fb510d60c696712f24ad95eec9c16e224d4c24c | 46099b44d50a2af496dce87234b923ee60541cc4 | /PedigreeNetwork/ui.R | 47f4c6340c10df76f086e76cf07a47ce84142abd | [] | no_license | jhgille2/SoybeanPedigreeApp | 0534ceec315beabc306a7192e7d5686bc591816a | f5ca7dd9c5f491796e1411809158ea78ad0aa620 | refs/heads/main | 2023-06-26T16:58:18.603937 | 2021-07-24T00:37:44 | 2021-07-24T00:37:44 | 360,652,905 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,412 | r | ui.R | #
# This is the user-interface definition of a Shiny web application. You can
# run the application by clicking 'Run App' above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(igraph)
library(visNetwork)
library(tidyverse)
# Define UI for appli... |
b60433d4d8c9311ae402eea6a8eded5f54a212de | f40d0763dd69945ac6c5726f820dd56a1c2e1c57 | /GrowthCurveAnalysis/R/gExport.r | f153ef2f33f42ce822a8ade744aeb69b11f8c007 | [] | no_license | KarlynB23/GCAF_git | 1b3b3f414f41b9e0e5eba1766df652cb268c9a17 | 3bb386657cc0cc13312d28ec71b5aa3855c9e2fd | refs/heads/master | 2020-12-24T14:52:58.822631 | 2011-07-27T23:47:32 | 2011-07-27T23:47:32 | 2,115,176 | 1 | 2 | null | null | null | null | UTF-8 | R | false | false | 2,534 | r | gExport.r | #BGN FUNCTION
gExport <- function(g.analysis, name="LastExport", control = gControl()){
# saves the parameters and meta information in a tab-delimited spreadsheet for use outside of gFunctions
# Args
# g.analysis - an object of class gAnalysis produced by gAnalysis or a list of such objects
# name - a name for... |
372107d398257f7c0cfe6bf31149f6ba68dbf387 | 1e9c9f2a9639db7cdb032aae69cb4d99aef1d3a5 | /dataCamp/introductionToR/6_lists/7_addingMoreMovieInformationToTheList.R | 1ac7f46759858e48d7dab5e8ebc33ecdafe74a4b | [
"MIT"
] | permissive | sagarnikam123/learnNPractice | f0da3f8acf653e56c591353ab342765a6831698c | 1b3b0cb2cff2f478006626a4c37a99102acbb628 | refs/heads/master | 2023-02-04T11:21:18.211654 | 2023-01-24T14:47:52 | 2023-01-24T14:47:52 | 61,184,927 | 2 | 1 | MIT | 2022-03-06T11:07:18 | 2016-06-15T06:57:19 | Python | UTF-8 | R | false | false | 1,259 | r | 7_addingMoreMovieInformationToTheList.R | # Adding more movie information to the list
#########################################################################################################################
#
# Being proud of your first list, you shared it with the members of your movie hobby club. However, one of the
# senior members, a guy named M. McDowel... |
c10a2d895adaccb0588d422c68927f6b2274843f | aba0008e63f77b56c8d437faa3d77677e5c8aa69 | /1-moderate/longest_lines.R | 34d303657b82096a82c526041d1606cc94858699 | [] | no_license | OehlR/codeeval | d690a11a5a1c2a5bbfaebd607452c953f78706a8 | b269b99d1d639ec17688dd9f7e66e23e6711fc67 | refs/heads/master | 2021-05-02T08:58:46.005968 | 2017-11-03T22:25:12 | 2017-11-03T22:25:12 | 28,037,547 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 287 | r | longest_lines.R | args <- commandArgs(trailingOnly=TRUE)
if(F) {
cat('2\nHello World\nCodeEval\nQuick Fox\nA\nSan Francisco\n',file=f<-tempfile())
args<-list(f)
#unlink(f)
}
l <- readLines(args[[1]], warn = FALSE)
odr <- l[order(nchar(l),decreasing=TRUE)]
cat(odr[1:as.numeric(l[1])],sep="\n")
|
b95202540e9de3f67ccc0502156789f5de28c825 | c2171eaf8201b9de995a5f6f5e1ff3eec8963374 | /R/breed.R | c27ea8d465dd48bb28002b0b01df4ec2049fafe5 | [] | no_license | SeemaShet/GA | a02b8ff0ae6e0689c0b039ede3a59d96bf4813b0 | 43cf7def2f5cb70555b95ff8225c7863994c1b8f | refs/heads/master | 2022-04-02T19:10:43.994843 | 2019-12-20T00:36:16 | 2019-12-20T00:36:16 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,301 | r | breed.R | #' Breed
#'
#' The function breed a new population given the current population by doing
#' cross-over and mutation of the individuals from current population. It uses
#' two helper functions, cross over and mutation. Two candidate parents
#' are selected everytime at random from the current population to be cross
#' o... |
11dd133feb28bd744a3054087f03e5169dad8c96 | 63f7a5e85c5322234589efad98cd996f505dd9c9 | /man/bootstrap.Rd | ef2755a861dfe266d5d2b2b3975d0b0363c99f6a | [] | no_license | EllaKaye/BLB | e9bc1ae3063bf3c5ac0a853dabfd1e08624a7930 | 4a8af58f13bd2f87c924b36c65f617737df50f02 | refs/heads/master | 2021-01-10T17:13:29.810703 | 2015-12-04T08:59:42 | 2015-12-04T08:59:42 | 46,873,538 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 491 | rd | bootstrap.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/multi_regr.R
\name{bootstrap}
\alias{bootstrap}
\title{Bootstrap}
\usage{
bootstrap(x, y, B, n)
}
\arguments{
\item{B}{the number of bootstrap replications}
\item{n}{the number of resamples to generate}
\item{data}{the original sample, as a... |
9ffd70328642ee8a881c12bcb8d7c699b7d1a0f3 | 4e5c61bf13f256bdcc689f8a7e7c1a410e75258e | /legacy/IR_plot_190207_v1.R | 88e538a226dc720e69a67392bdcd3b6a40600a4a | [
"Apache-2.0"
] | permissive | JureZmrzlikar/intron | 61d85b0297de986d1d0f56d1cd140a1ec8bc96e3 | a9850695846607f877d2795144e8cb9c2277a8c6 | refs/heads/master | 2020-07-29T03:36:59.257157 | 2020-01-20T11:21:43 | 2020-01-23T10:18:28 | 209,654,954 | 0 | 0 | null | 2019-09-19T21:53:39 | 2019-09-19T21:53:39 | null | UTF-8 | R | false | false | 13,640 | r | IR_plot_190207_v1.R | library(reshape2)
library(ggplot2)
library(gdata)
library(plyr)
library(readr)
get_bg_colors = function(bg_color){
if(bg_color=="white"){
front_color="black"
back_color="white"
}
if(bg_color=="black"){
front_color="white"
back_color="black"
}
return(c(front_color,back_color))
}
## SOURCE: ht... |
b154243581ae82cad58b6863780825f6041a81f6 | 9fa889c10187dff24aecc072949db196562da19b | /RScripts_Recession/RScript02_sipp08_disab.R | cd54e4180c753200a7d1eb663cd6fc06c059e1c2 | [] | no_license | snandi/Project_Recession | 098ef216939ec764cd9fef1b06fd2ee6ea640ac5 | 1bdbf170e4c9491def5af541f613b0846599e119 | refs/heads/master | 2020-04-12T09:41:40.357259 | 2017-08-21T05:55:17 | 2017-08-21T05:55:17 | 41,777,027 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,488 | r | RScript02_sipp08_disab.R | rm(list=ls(all.names=TRUE))
rm(list=objects(all.names=TRUE))
#dev.off()
########################################################################
## This script reads in sipp08_master & 2008_disability and merges them
## and conducts basic summary statistics
#############################################################... |
2f2428cf8a33496a57467c4547041bd3352f3cfb | c0e7ceea2ee949e24aeca3850011d54dc47e256c | /scripts/deprecated/filenames_hibench_hadoop_preprun.R | a2450a6af177baf9978529984ea8f4d44ab33f3e | [] | no_license | ananthnarayan/bpod2020 | b604b0cd79ac145cdb9115ea0df95c06bbdb806f | e2448e0d59ca7d891cb580776bc3de4a10e9637e | refs/heads/master | 2023-01-31T09:20:34.727555 | 2020-12-09T08:13:25 | 2020-12-09T08:13:25 | 233,527,509 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,576 | r | filenames_hibench_hadoop_preprun.R | library('hash')
#crono_files=c("apsp.csv","bc.csv","birch.csv","bfs.csv", "community.csv", "connected.csv", "tsp.csv", "pagerank.csv","sssp.csv","triangle.csv")
hibench_27_tiny_files=c(
"aggregation_prep.csv" , "bayes_run.csv" , "kmeans_prep.csv" , "scan_prep.csv" , "sort_run.csv" , "wordcount_prep.csv",
"ag... |
3812bc3604de2d33e8bced6d7a532c20c60599a0 | e63317e82a6bf9826efdd6c7b714e7599441fc21 | /man/bootLM.Rd | 65d2076c0fdce273394de1299680f663b03c09cb | [] | no_license | anspiess/reverseR | f21774d6ab629b7f91107d21fcf935dde4919214 | 3ec07fda74d8d9900b4926fe9e79ef3b17dae5d9 | refs/heads/master | 2022-06-19T00:55:54.050231 | 2022-05-11T18:04:09 | 2022-05-11T18:04:09 | 130,033,550 | 3 | 1 | null | 2018-04-18T20:29:13 | 2018-04-18T08:55:11 | R | UTF-8 | R | false | false | 1,991 | rd | bootLM.Rd | \name{bootLM}
\alias{bootLM}
\encoding{latin1}
\title{Nonparametric bootstrap linear model}
\description{
Nonparametric bootstrap (sampling cases with replacement) method for parameter estimation and confidence interval of a linear model.
}
\usage{
bootLM(formula, data = NULL, R = 10000, alpha = 0.05)
}
\argument... |
5970e840fab6c591e22514a0f6e7afc00a8916e0 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/plotrix/examples/sumbrk.Rd.R | f3f18e1418f2603d9bb86483dfec249a674f52e7 | [] | 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 | 188 | r | sumbrk.Rd.R | library(plotrix)
### Name: sumbrk
### Title: Count specified values in a vector
### Aliases: sumbrk
### Keywords: misc
### ** Examples
sumbrk(sample(LETTERS,100,TRUE),trueval="M")
|
a5f10ee5043a8d89446ee4d2aa5433b144693e9a | 3a04468a8440fe5d8d2c8665334b654a63f1af74 | /6_dataVisualization.R | 163cda224e6f7e9be5fb3151e1c3391ed0dd194f | [] | no_license | sukesh-reddy/rTutorials | b6c6e76538d8b66c897fb61a6d50c4ba497cf000 | cd6fd4e87d1c311361b13ef0c24379d45bb71384 | refs/heads/master | 2021-05-17T19:02:53.523434 | 2020-04-12T07:58:25 | 2020-04-12T07:58:25 | 250,930,313 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,058 | r | 6_dataVisualization.R | ##################################
# Data Visulization
# base package, ggplot2
# grid graphics, lattice graphic - optional
###################################
######### Base Package #####################
# -----------------------------Scatter Plot
# It helps in visulization data easily and find the linear relation... |
a6293c6cc23b529d0bf9521f18a258c83b7e5e12 | 56b0e1e55287425abd23e8c58840d4cc22802dd9 | /R/diss_rate_chg.R | 7cbe33429127f9eda4f2d0ea0ff0be76daff2f87 | [] | no_license | fawda123/pteropod_ts | 2a0749810fa051b8c52fdfc2cbf0dba8a94575f1 | 8accadd51bb4bff9863aa160b0722e662891aca8 | refs/heads/master | 2021-06-02T19:20:10.649781 | 2020-09-29T23:43:27 | 2020-09-29T23:43:27 | 135,618,117 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 373 | r | diss_rate_chg.R | # estimate dissolution rate of change
library(tidyverse)
data(biodat)
disrat <- biodat %>%
select(date, cohortyr, mo, station, typ3) %>%
arrange(station, date) %>%
group_by(station) %>%
mutate(
disavg = mean(typ3, na.rm = T),
disdel = c(NA, diff(typ3)) / disavg,
dtsdel = c(NA, (as.numeric(dif... |
34327f60c4bee6955659deceebbd0a47cb15f53c | 802d0666cfa220d2873060cbe0b44cfd68b3fc57 | /man/ettersonEq14v1.Rd | 53b897b3c0bc964e21b0c2340408de64949a9d79 | [] | no_license | fraenzi/carcass | 9e3f0f8d4355fc6f43623fee1262f932f2ab04c8 | d3aff9fdbc4322ec8ddcbe6dcd22d35b8b9fe614 | refs/heads/master | 2021-05-10T21:41:24.145988 | 2019-01-21T10:40:16 | 2019-01-21T10:40:16 | 118,236,258 | 0 | 1 | null | 2018-03-05T14:04:24 | 2018-01-20T11:22:52 | R | UTF-8 | R | false | false | 1,989 | rd | ettersonEq14v1.Rd | \name{ettersonEq14v1}
\alias{ettersonEq14v1}
\title{
Equation 14 of Etterson (2013) Ecological Applications 23, 1915-1925,
adapted so that persistence probability and searcher efficiency can vary
with calender date
}
\description{
Calculates the probability that a carcass that has fallen in the search area during
n ... |
75bb32c579425efe1d339a632fc5e785feb58a1a | 9790f2d332593b64955c312a2ac1f31768da7f1f | /demo/equations.R | 693b9d2da41fe477388282e52b8f1c036786f7e5 | [] | no_license | nalimilan/R2HTML | 5a4d0ab514cc30f1f33d7752c6c1eabc1fd0b070 | 108a16184890a75a8ef08567843c43e86afd06a8 | refs/heads/master | 2022-05-29T15:31:00.000106 | 2022-05-23T09:21:27 | 2022-05-23T09:21:27 | 23,266,035 | 4 | 6 | null | 2022-05-14T21:03:38 | 2014-08-23T20:52:10 | R | UTF-8 | R | false | false | 609 | r | equations.R | .HTML.file = HTMLInitFile()
HTML.title("sample page",1,file=.HTML.file)
HTML(as.title("Sample equation"),HR=3)
cat("Some text and then a math mode:",file=.HTML.file,append=TRUE)
HTML(as.latex("[[a,b],[c,d]]((n),(k))") ,file=.HTML.file)
cat(". Nice isn't it?",file=.HTML.file,append=TRUE)
HTML(as.latex("\\int_{-\\... |
e7681737c71a06314d1a5cba3a46d6179a4d9b39 | d1675379757820d2a27d517bccfca93143cb88de | /R/zzz.R | c7a087a2a175c43676a771382d6f44912a8f6a8e | [] | no_license | svd09/ckbplotr | 7b949e185b3aa217f52db7a6cbbd0c26635265b6 | d08e8bf82df6143d5d56c5ffb5a6f3901309ecc5 | refs/heads/main | 2023-04-03T17:31:45.184461 | 2021-04-14T19:09:04 | 2021-04-14T19:09:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 139 | r | zzz.R | .onAttach <- function(...) {
packageStartupMessage("Please check NEWS.md, help files and vignettes for latest changes to the package.")
}
|
0763c95f91686fa632298ce3be629481e39796c5 | fdae9375a71c1ec06db96b5ce96e7897219e6c58 | /man/company_information.Rd | 6a5dd3a2700d87b5decfbc21892ce192eb5442cf | [
"MIT"
] | permissive | Feihelan/edgarWebR | f7bb8e82a0a21ca56b87b6b9b70da065ba95312d | 18ef6c27d17a80f5e29c413cc69c3281b0806130 | refs/heads/master | 2020-04-16T20:35:03.564129 | 2018-08-24T12:32:43 | 2018-08-24T12:32:43 | 165,901,956 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 481 | rd | company_information.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/company_information.R
\name{company_information}
\alias{company_information}
\title{SEC Company Info}
\usage{
company_information(x)
}
\arguments{
\item{x}{Either a stock symbol (for the 10,000 largest companies) or CIK
code}
}
\value{
a data... |
217d12161d8a336aebb7b25df5d101a85a5a4ed5 | 0d03305dc8edc133003ec5b2cdb70b0521513cc7 | /comparativeGenomics/chainScripts/hotspotIndel.R | 0ff30ad8e40ae0304d2772a2e103327893bdb933 | [] | no_license | ReubenBuck/RTN_domains_scripts | e3d5c222a2182ed21fc609dedfd660c25a28dbd1 | 745c2b3f71924b3897cb58f7463a88fd4d9eab98 | refs/heads/master | 2020-07-04T06:33:52.525113 | 2018-01-09T03:09:05 | 2018-01-09T03:09:05 | 67,857,570 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,553 | r | hotspotIndel.R | ## Produce all our plots across one script
## so lets go back a couple of steps
## what are we actually measuring with our 4 stats
## human bases that have been lost since divergence with mouse
## human bases that have been gained since divergence with mouse
## mouse bases that have been gaines since divergence w... |
fb8b6e1376b1a93ca75abda1364a90b87b6b32f6 | a6bb9d8d9c9c7be92ef7a5e6da6a0c426b66134b | /ui.R | 6a4f5fd47653c7e735064f36f276519d7526d7ed | [] | no_license | nahfa911/shinyweather | 616ed878d7abff5c810a5b0665dc5c5f73435244 | 302016621e8e734a0c8dd6253aee7922fa2a4789 | refs/heads/master | 2020-03-30T08:03:45.995237 | 2018-10-27T13:51:41 | 2018-10-27T13:51:41 | 150,971,885 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 476 | r | ui.R | shiny::fluidPage(
shiny::titlePanel(div("Weather forecast",style="background-color:aliceblue;text-align:center;
font-family:Calibri;height:35px;border-radius:6px;"
)
)
, shiny::sidebarLayout(
shiny::sidebarPanel(shiny::textInput(inputId = "cityName",label = "City Name",value = "Linko... |
a8510ee9325b05b41e0d761c27c2aa3f097dd43c | 8b5e1c11d8a66b943ed5b4d0f7c905bb4398f709 | /caminata raul zacatelco.R | ced8d87f645da1eeed482ff2238ba3968f13d641 | [] | no_license | sherlockcubing/Programacion_Actuarial_III_OT2016 | e9d0107e30dd9d89aa5f8a18e444ca553b426b9b | be74969a73a1908fe2fa21be15fb080e08b16ba6 | refs/heads/master | 2020-04-18T12:43:04.018262 | 2016-11-09T11:21:11 | 2016-11-09T11:21:11 | 65,914,634 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 460 | r | caminata raul zacatelco.R | n <- 0
y <- 0
z <- 5
salida <- vector("numeric")
caminata <- vector("numeric")
for (i in 1:100) {
caminata <- vector("numeric")
z <- 5
while(z>=3 && z<=10){
caminata <- c(caminata,z)
print(z)
moneda <- rbinom(1,1,0.5)
if(moneda==1){
z <- z + 0.5
} else {
z <- z - 0.5
}
}
salida <- c(salida,z)
... |
a39abef37947208d98785b3f5c6c897de427cc38 | c4885558962de723db5a1331cdc0158bffef73fd | /R/geom_pushpin.R | b1814dcfa72b5069167c01a287c5e4962c9b7393 | [
"MIT"
] | permissive | R-CoderDotCom/chinchet | 3d1042ce51af8beb831f3f12da4244bc6563c66c | 76428786bd75f5ae7b3f9aeb77522fb05db0ced9 | refs/heads/main | 2023-02-19T02:07:44.426882 | 2021-01-17T19:08:55 | 2021-01-17T19:08:55 | 330,424,890 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,434 | r | geom_pushpin.R | # pushpinGrob
pushpinGrob <- function(x, y, size, pushpin, geom_key = list(red = "red.png",
blue = "blue.png",
green = "green.png",
yello... |
3368bf1e166c45b2796dcc114c03e22fa777ddf1 | c593a8dfa39cf6f137e86242fcb2218d0b68ab1f | /NBR/02-Run_NBR/find_noncoding_drivers_precomp_correctoverlaps_EEWmod_noindels.R | b1eb05f71386f7b4e7c1d1f13ba095c71016659c | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | BioAmelie/2020-hrPC-landscape | 3f188c95a480b098ea9394ae8de75a1654d98e72 | f3fd52f8dd7af980fcf562bceb689fd2db54433f | refs/heads/master | 2022-11-26T21:12:50.820683 | 2020-08-13T02:09:45 | 2020-08-13T02:09:45 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 25,890 | r | find_noncoding_drivers_precomp_correctoverlaps_EEWmod_noindels.R | # Inigo Martincorena - 2014
# Non-coding driver detection with precomputed trinucleotide composition and using the
# local density of putatively neutral mutations as covariates ("t") in the framework of a
# negative binomial regression.
#
#
###############################################################################... |
80138efbf2dbb60bc0302daa486089c58717c125 | 093dacede7c431ab1cbef672830f76920942b801 | /man/IRB.Rd | 7d70fbd820c02eb1ffc07e1df2acb258c1cb0c1b | [
"Apache-2.0"
] | permissive | bhklab/MetaGxBreast | a30cee29007ededf0fbeb64524f18b3a3b8128b8 | 3ba8f39928a20dffb799c338622a1461d2e9ef98 | refs/heads/master | 2021-06-03T09:54:44.555453 | 2021-04-23T18:54:53 | 2021-04-23T18:54:53 | 100,535,452 | 4 | 2 | null | null | null | null | UTF-8 | R | false | false | 1,653 | rd | IRB.Rd | \name{ IRB }
\alias{ IRB }
\docType{data}
\title{ IRB }
\description{ ExpressionSet for the IRB Dataset}
\format{
\preformatted{
experimentData(eset):
Experiment data
Experimenter name:
Laboratory:
Contact information: http://www.ncbi.nlm.nih.gov/pubmed/18297396
Title:
URL: http://www.ncbi.nlm.nih.go... |
fca2bd4c784b99bb75920c8551f6f7fe6302f69b | 2e8a0f83c5a27cfd1977eb7b94863d12bee7bc5f | /CorInteractVSneighbour.R | dac13259e9ee5c833fcb0074b32328077b66d1e0 | [] | no_license | ABorrel/saltbridges | 611036cfa101da4c0e390de3c12b9cae04e3b5b0 | 5b8a0bb15ab6876082891f2afc2d3ce0b4c03c7a | refs/heads/master | 2020-06-17T21:51:16.843534 | 2016-11-28T10:54:37 | 2016-11-28T10:54:37 | 74,966,556 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,547 | r | CorInteractVSneighbour.R | #!/usr/bin/env Rscript
source("tool.R")
############
# MAIN #
############
args <- commandArgs(TRUE)
p_interact = args[1]
p_nb_neighbor = args[2]
pr_result = args[3]
d_interact = read.table(p_interact, header = TRUE)
d_neighbor = read.table(p_nb_neighbor, header = TRUE)
print (d_interact)
print (d_neighbor)
... |
a71060856bb9ed84735d6bece2bf1b6a1fd855f4 | ed2530b7c73ad80b86a0e60db075aaacdf53dbea | /QTL_genes.R | 3c58a6c55ed4eb8f9bd9de2745616e6b046d9a2b | [] | no_license | BrianRitchey/qtl | 7444a409d4d07abda3f13b5cfa2794113f93c0e9 | 9792fef3dfa7ecdd62857d58ca3f9966456ae6b8 | refs/heads/master | 2023-07-08T01:38:25.485945 | 2017-09-11T18:44:29 | 2017-09-11T18:44:29 | 98,877,595 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,303 | r | QTL_genes.R | # QTL_genes function
#
# written by Brian Ritchey.
# Used in conjunction with R/qtl package.
# Returns genes in a QTL interval based on "Mouse_Genome", which is Mouse Genome Build 37 available from BioMart.
# Utilizes R/qtl's "find.flanking" funciton.
#
# Aguments: Can either supply a bayesint object as the only argum... |
37ff9f39d7ed8b5387550bbf870906c011d09c3b | 80b3a24b6fece4d67c654a1c897ad479d5447a64 | /Analysis.R | deaaadc63f98c57d00775b364c3e66fcaa1f4ecc | [] | no_license | rholdo/Holdo_et_al_2021_EcolMon | 22463945ed282523aef9b540ded89ccab6c3e17b | 786b684a3f1c332a8670dea048811ceb0b711907 | refs/heads/main | 2023-04-11T11:47:11.028423 | 2022-01-10T15:19:38 | 2022-01-10T15:19:38 | 366,747,777 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 68,532 | r | Analysis.R | # Seedling growth gradients interact with homogeneous disturbance regimes
# to explain tree cover discontinuities in savannas
# Code author: R. Holdo (rholdo@uga.edu)
# Nov 11, 2021
library(dplyr)
library(ggplot2)
library(nlme)
library(lme4)
library(reshape2)
library(grid)
library(gridExtra)
library(cowplo... |
cd352b74ae8c209c5c6781efc5b3ee0ec2823981 | 3ca04a6bce47b2bed1942e79d35ef47a2460a3c0 | /man/packs.go.Rd | e1a1e66cc7aadd8b9d84b85ddf6004c05d8fc3c2 | [] | no_license | Rterial/Rtbase | d863c743f7ed5ac63afb2188b08643c2cd17e504 | cdb784fb75a04718973852c4803067bbdc92dd2f | refs/heads/master | 2021-01-10T15:32:10.379629 | 2016-05-13T07:04:38 | 2016-05-13T07:04:38 | 53,450,341 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 202 | rd | packs.go.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/startup_utils.R
\name{packs.go}
\alias{packs.go}
\title{Startup Load}
\usage{
packs.go()
}
\description{
\code{packs.go}
}
|
7b791a693ed903b5480d5ae004f6bc4cccbcecc2 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/apdesign/examples/apdesign_i.Rd.R | e586c192563f15e50d82d2e8b68a6c9df413d561 | [] | 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 | 464 | r | apdesign_i.Rd.R | library(apdesign)
### Name: apdesign_i
### Title: apdesign_i: AP coding for a single subject
### Aliases: apdesign_i
### ** Examples
y <- c(10, 15, 21, 20, 23, 25, 27, 25, 28, 29)
time <- c(c(0.2, 0.5, 0.7), c(0.3, 0.6, 0.75, 0.89), c(0.1, 0.3, 0.8))
cycle <- c(rep(1, 3), rep(2, 4), rep(3, 3))
df <- data.frame(y, t... |
334676fefaf7dcc0634f2ef7f07f073241092392 | 93edbaaae57c83fb12869e46b645c31075af94aa | /wikidata2R2postGIS.R | c857740d71ff4d2cf79f3554c4fb10345869d542 | [] | no_license | cbittner/wikidatanalysis | c1aa273b843c8268376909da43b9c17fbd7d50cb | 5dc2f3e980f3dd7d12449cc64ad1d5abce5dcde8 | refs/heads/master | 2021-09-16T01:45:50.643448 | 2018-06-14T16:57:30 | 2018-06-14T16:57:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,887 | r | wikidata2R2postGIS.R | #required packages
#postgres connection parameters
{
pg_dbname="[DBNAME]"
pg_host="[HOST]"
pg_port=[PORT]
pg_user="[USERNAME]"
pg_password="[PASSWORD]"
}
#install.packages("RPostgreSQL")
require(RPostgreSQL)
drv <- dbDriver("PostgreSQL")
con <- dbConnect(drv,
d... |
108e1d1399aa343ad313a4b46ced072a287c0d73 | 72d9009d19e92b721d5cc0e8f8045e1145921130 | /LongMemoryTS/man/fdiff.Rd | b198148fc344516d4c5585df1ac7c4e8c4c35049 | [] | no_license | akhikolla/TestedPackages-NoIssues | be46c49c0836b3f0cf60e247087089868adf7a62 | eb8d498cc132def615c090941bc172e17fdce267 | refs/heads/master | 2023-03-01T09:10:17.227119 | 2021-01-25T19:44:44 | 2021-01-25T19:44:44 | 332,027,727 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 860 | rd | fdiff.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fdiff.R
\name{fdiff}
\alias{fdiff}
\title{Fast fractional differencing procedure of Jensen and Nielsen (2014).}
\usage{
fdiff(x, d)
}
\arguments{
\item{x}{series to be differenced}
\item{d}{memory parameter indicating order of the... |
613e8e7a74d1cc115d7235d8f044ac843c2ce885 | 90c8e41885c3259949f63b3aa9fe16d7763e02d9 | /Scripts/create_blood_date.R | 660931dbf33233de744ae687aae1024c18ea3721 | [] | no_license | CPRyan/Cebu_reproductive_histories | 67a95f979cb3c78f65b395913b490190d70cd110 | c2beee496bb297a383f3a3275681ade6d1bd9a89 | refs/heads/master | 2020-03-27T10:06:56.494721 | 2019-06-19T02:44:17 | 2019-06-19T02:44:17 | 146,392,851 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 688 | r | create_blood_date.R | # Create Blood date
# Load the full data
date <- read_dta("~/Academic/PhD/Projects/Cebu/Methylation/Fall 2015/Full_cohort_for_Meaghan.dta")
labels <- lapply(date, attr, "label")
str(labels, list.len=ncol(date))
blood.date <-date %>%
select(uncchdid, icsex, dayblood, monthblood, yearblood)
blood.date$yearblood... |
f4b3a30ffcdc4cd40ed1e735decd6ad92d0eafc3 | eb53a9516cdc7f846e4c07ac4c0cdffcaa561a2c | /plo1.R | e8bb03bcf8e13c1544404e6af44dc6e0ce257cd5 | [] | no_license | hwyan0220/ExData_Plotting1 | 1961f253440dcd042165d34bfafaccf5892f31e4 | 43dc05db44d6e75fc7c413ddf073fcad00c442fa | refs/heads/master | 2021-05-03T22:53:32.258636 | 2016-10-23T14:35:55 | 2016-10-23T14:35:55 | 71,701,681 | 0 | 0 | null | 2016-10-23T12:34:23 | 2016-10-23T12:34:22 | null | UTF-8 | R | false | false | 590 | r | plo1.R | setwd('H:/exploratory/assignment')
elec <- read.table('household_power_consumption.txt', header = T, sep = ';', na.strings = '?')
elec1 <- elec
elec1 <- subset(elec1, elec1$Date == '1/2/2007'|elec1$Date == '2/2/2007')
elec1$Time <- strptime(paste(elec1$Date, elec1$Time), '%e/%m/%Y %H:%M:%S')
elec1$Date <- as.Date(ele... |
d179814a20b26589d141c66b30b2b2e5e720538c | bf74cef0ed028929d29eae883d9008c258130f62 | /man/cotan_analysis.Rd | 10f3d89b9f64296c2dbbd1240bd4c4284e3cb761 | [] | no_license | seriph78/COTAN_stable | 039ff813d7ec5c4f2c41e57b563deea0950ab211 | 480f76b881ae99e3605229524c1412933f3d4146 | refs/heads/main | 2023-05-10T05:01:05.837838 | 2021-06-06T17:01:29 | 2021-06-06T17:01:29 | 374,412,971 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 661 | rd | cotan_analysis.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/COTAN_main.R
\name{cotan_analysis}
\alias{cotan_analysis}
\alias{cotan_analysis,scCOTAN-method}
\title{cotan_analysis}
\usage{
cotan_analysis(object, cores = 1)
\S4method{cotan_analysis}{scCOTAN}(object, cores = 1)
}
\arguments{
\item{object... |
6d8de9079d992ff38ba0d5ec1673a48615d5d6ab | afb10b7c49c7e2f86ba319dbd55083ec6672ea20 | /scripts/path_sampling_plotting.R | b8a843bbaa921a3dbabb4e92b72f2d27083fd300 | [] | no_license | ahmedmagds/TreePrior-ClockRate | ced3522da37f9b3ba50a7953e7028b4c2675bfd3 | 4d178e531848f91cbc9b55894bfad7a692f8d592 | refs/heads/master | 2021-09-09T17:55:27.710604 | 2018-03-18T19:34:52 | 2018-03-18T19:34:52 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,511 | r | path_sampling_plotting.R | library(ggplot2)
library(xtable)
expand_model_names = function(df) {
models = vector(mode = "list", length = 6)
names(models) = c('bd', 'bdsky', 'const_coal', 'exp_coal', 'sky_coal', 'struct_coal')
models[['bd']] = 'Birth death'
models[['bdsky']] = 'Birth death skyline'
models[['const_coal']] = 'Constant coa... |
fae6c3ac6971349e6e5be877eb5ee9aa1e1543b6 | f8f93db15f8f366fffb4728e209f42d12007bac9 | /12/notes12.R | 57fc444d285cf650069d0ad5c0af9ad42d3e75dd | [] | no_license | ionides/531w18 | 065c45797e61554339d1735753debeead6a37b86 | 331ad8309f2514191f649b18f637be264292ba8e | refs/heads/master | 2023-01-02T14:09:43.496031 | 2020-10-22T17:46:35 | 2020-10-22T17:46:35 | 113,875,595 | 7 | 87 | null | 2018-02-20T22:39:46 | 2017-12-11T15:27:32 | HTML | UTF-8 | R | false | false | 10,809 | r | notes12.R | ## ----opts,include=FALSE,cache=FALSE--------------------------------------
options(
keep.source=TRUE,
stringsAsFactors=FALSE,
encoding="UTF-8"
)
## ----prelims,echo=F,cache=F----------------------------------------------
set.seed(594709947L)
require(ggplot2)
theme_set(theme_bw())
require(plyr)
require(reshape... |
52f29dbf793d91071929f038dd8f28eb8686bfbd | 3eab62651715a8a416ce8a5cc0cb370dfc8d4e8a | /Distance_Script.R | 664fedd218533ecaba818e1531909e381cbe8314 | [] | no_license | capstone-pilot/DistanceMatrixScript | 10c81df7ce045db0d87f14d90707298c468cb55b | 1f354970b9d956724924f3245adf2a9212e99fa7 | refs/heads/master | 2020-07-23T11:00:49.908959 | 2019-09-19T10:39:59 | 2019-09-19T10:39:59 | 207,536,872 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,739 | r | Distance_Script.R | #Package for geospatial distance between two points
if(!require(geosphere)){
install.packages("geosphere")
require(geosphere)
}
if(!require(stringr)){
install.packages("stringr")
require(stringr)
}
#Set working directory where files exist
setwd("~/Desktop/Pilot/Data")
#Main locations file
PFJ <- read.csv("./P... |
b1b6b8d15a5a4e31661c3fd3e385736e24c2d536 | cb66ae3bf5bd2422e70df574340e0d5f5388eb8e | /functions.r | 5474855703a0a3069975b378844b75c2cdbb90ca | [] | no_license | jvoorheis/MSA_Ineq | 779f28947f243495d4c28b6841b56d2c51dc97e6 | 3dbec52e82d0ae86d6d88c6550aadba4b43cb81a | refs/heads/master | 2016-08-02T22:44:29.331869 | 2013-12-28T07:50:20 | 2013-12-28T07:50:20 | 11,228,792 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 18,173 | r | functions.r | library(ggplot2)
library(GB2)
ratio9010f<-function(inc){
return(quantile(inc, probs=0.9)/(quantile(inc,probs=0.1)+0.000001))
}
ratio95medf<-function(inc){
return(quantile(inc, probs=0.95)/(quantile(inc,probs=0.5)+0.000001))
}
ratio99medf<-function(inc){
return(quantile(inc, probs=0.99)/(quantile(inc,probs=0.5)+0.... |
db8b0c88af9702389563c74d74c958e21b443426 | 94b3ae0be487a1824ee98c5bf6c8cd81e9f0bd18 | /tests/test-all.R | cd055b97466f0f46e8910dcbb231802afc6af603 | [] | no_license | cran/rticles | 4e50100f04289440b1ef12544b393ecb74e5a8f2 | 2cd04a5ef4698a9ae352b97250b55ac220cb2741 | refs/heads/master | 2023-06-22T06:23:58.674846 | 2023-05-15T12:30:02 | 2023-05-15T12:30:02 | 54,406,556 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 40 | r | test-all.R | library(testit)
test_pkg("rticles")
|
d7763edd041a928fcf25f75c53ec8879f3104ff4 | d4918568929a592a40ee705dc91614be17603c2c | /man/num2imp.Rd | 4dc03a5eab05998db518dffc8a7c6a3087c2052d | [] | no_license | kevin05jan/iop | d722f6c8520cd457872f9a4f2d83294e1a3dc675 | 8a8b391976982985f1cfe66535d58a1606d4099b | refs/heads/master | 2020-08-02T14:25:27.256169 | 2019-10-19T09:43:06 | 2019-10-19T09:43:06 | 211,387,761 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 625 | rd | num2imp.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tmp.R
\name{num2imp}
\alias{num2imp}
\title{Feature selection using randomForest}
\usage{
num2imp(x, y, thresh = 0.5, ntree = 10)
}
\arguments{
\item{x}{: data.frame with numerical variables and class label}
\item{thresh}{: numeri... |
e3c71d1c2a0a635d0e0aecdcfebd5ec84459e868 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/queueing/examples/Inputs.o_MMInf.Rd.R | 2d9edaaaff07e953c574de50bd117ed8bfb60c45 | [] | 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 | 364 | r | Inputs.o_MMInf.Rd.R | library(queueing)
### Name: Inputs.o_MMInf
### Title: Returns the input parameters of a M/M/Infinite queueing model
### Aliases: Inputs.o_MMInf
### Keywords: M/M/Infinite
### ** Examples
## create input parameters
i_mminf <- NewInput.MMInf(lambda=0.25, mu=4, n=0)
## Build the model
o_mminf <- QueueingModel(i_mminf... |
d2fe920bab89262766748d07695d1c10448df27b | d60a4a66919a8c54d29a4677574b418107b4131d | /man/perwinba.Rd | 7bf32ab0f33c76e0b648614649ca761f0f8f59fe | [] | no_license | cran/tsapp | 65203e21a255e832f0ad9471f9ee308793eb7983 | f2679a3d5ee0e3956a4ba013b7879324f77cf95f | refs/heads/master | 2021-11-12T21:18:18.835475 | 2021-10-30T10:30:02 | 2021-10-30T10:30:02 | 248,760,597 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 540 | rd | perwinba.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/frequdom.r
\name{perwinba}
\alias{perwinba}
\title{\code{perwinba} Bartlett-Priestley window for direct spectral estimation}
\usage{
perwinba(e, n)
}
\arguments{
\item{e}{equal bandwidth (at most n frequencies are used for averaging)}
\ite... |
924992d1e101c40e659e758d35135b1d4ad643b6 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/ade4/examples/fruits.Rd.R | fefc9bd40c4e3a04577a9d0eec9089759e903021 | [] | 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 | 815 | r | fruits.Rd.R | library(ade4)
### Name: fruits
### Title: Pair of Tables
### Aliases: fruits
### Keywords: datasets
### ** Examples
data(fruits)
pcajug <- dudi.pca(fruits$jug, scann = FALSE)
pcavar <- dudi.pca(fruits$var, scann = FALSE)
if(adegraphicsLoaded()) {
g1 <- s.corcircle(pcajug$co, plot = FALSE)
g2 <- s.class(pcajug... |
03a4a11bebdc9c6944abd9ff0b088ba3b101847c | fb2136663e6986a9e04abea2891863888bd27c57 | /man/dummy.code.lab.Rd | 3a5aaf6f2b177bee021399e8b766b362d229b04f | [] | no_license | stevepowell99/omnivr | 192f1b0660a711bfa42e85259e7bb53ba090f3a3 | 122404abef49a6588d07adbf33cf31eaa110e8b9 | refs/heads/master | 2016-08-06T22:50:20.472001 | 2014-11-13T12:49:55 | 2014-11-13T12:49:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 568 | rd | dummy.code.lab.Rd | \name{dummy.code.lab}
\alias{dummy.code.lab}
\title{Same as psych::dummy.code but with labels}
\usage{
dummy.code.lab(x)
}
\arguments{
\item{x}{nominal dataset}
}
\value{
labelled dataset
}
\description{
Same as psych::dummy.code but with labels
}
\examples{
Here are some examples
}
\seealso{
Other experimental: \cod... |
279ba1e348fd8903b150fa69feff090109d0c1a1 | d837a6b0beaede292aa430adbeb38d7ccc1a3363 | /man/ftpDownload.Rd | 85a5d61963878553b6ccd91912bf2b24d7b7cc84 | [] | no_license | jameslhao/dbgapr_dev | 0503d740e4ffb394426638be31da609fb8f7f950 | 4d67dff0b4bd8dbda0bc74c6ca26362e93619f55 | refs/heads/master | 2020-12-30T13:09:21.487245 | 2017-08-15T12:20:00 | 2017-08-15T12:20:00 | 91,335,051 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,864 | rd | ftpDownload.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/commons_public.R
\docType{methods}
\name{ftpDownload}
\alias{ftpDownload}
\alias{ftpDownload,Commons-method}
\title{Download supplemental data files from dbGaP ftp}
\usage{
ftpDownload(object, ...)
\S4method{ftpDownload}{Commons}(o... |
aa37634523710960b6ea9e6495301adaa23eb510 | 1c5f4e06ec247883606011e82cee318be87112fc | /man/search_seed.Rd | ecf79e374984930187647fa15dbbd5e3edb4e201 | [
"MIT"
] | permissive | Hide-Fun/metabarcode | 888228f867fcc905446ed77e042c06e966b748d2 | a9866d300dae4796188e6ea5fb3b5ea9e47eb717 | refs/heads/master | 2023-03-06T12:05:25.724825 | 2021-02-22T01:33:22 | 2021-02-22T01:33:22 | 237,951,173 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 407 | rd | search_seed.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/search_seed.R
\name{search_seed}
\alias{search_seed}
\title{search seed}
\usage{
search_seed(n = 100, .data, k = 2, trymax = 1000, maxit = 1000, ...)
}
\arguments{
\item{n}{number of seed}
\item{.data}{data}
\item{k}{dimention}
\item{tryma... |
9666461759e3a249d0e4a83dd00bd40f74c0e918 | c2ace3da6f7d0d46ada5b8e3a13e236f8dd83ec3 | /unsupervised_modeling/watershed_score.R | ec4db3f5e917ee91999aa03d20b830c39033caf3 | [] | no_license | BennyStrobes/gtex_v8_rare_splice | 9c028d5cec442f7180d5c442be67ae9100a175d1 | c1d77b6a367cadc5d0020c55b868dd9b4961cf69 | refs/heads/master | 2020-04-08T13:37:04.811893 | 2020-02-28T14:04:06 | 2020-02-28T14:04:06 | 159,398,828 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 56,405 | r | watershed_score.R | args = commandArgs(trailingOnly=TRUE)
source("watershed.R")
library(cowplot)
library(RColorBrewer)
library(ggplot2)
library(Biobase)
initialize_phi<- function(num_bins,dim) {
phi_outlier <- matrix(1,dim,num_bins)
phi_inlier <- matrix(1,dim,num_bins)
phi_inlier[,1] = .8
phi_inlier[,2] = .1
phi_inlier[,3] = .1... |
1fdffd7bb45b293506be1c2a360dfe2ff42127c2 | 69a0b504229a3ad9002e72612f4528fcc0baef0b | /R/index.R | bed433715a511040c56da49545c276a2544ca59a | [] | no_license | seaman248/An.-atroparvus-genome-comparison | 91b37184f22848cbc55a351e2fb178efd283093a | d04b6672b335003b1a4aed21b0098e9feb688cf7 | refs/heads/master | 2021-07-03T18:57:47.445050 | 2017-03-07T06:33:01 | 2017-03-07T06:33:01 | 80,265,913 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 777 | r | index.R | ### Query data
## Get table of orthologs sp1_gene_id / sp2_gene_id ... / ... spX_gene_id
source('./R/Query/getOrthologs.R')
## Get coorinates for every gene of every species sp1: gene_id / chr / start / stop / strand
source("./R/Query/getCoords.R")
## All data saved in ./R/Query/output_data
### Clean... |
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