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867fef54f480b93efb1adf1b4583d9475837a044 | e17f3877ad5e350e63d8dc785df6ef6773e087f2 | /Rcommands.R | 4c79bca83dc07a8f9189eef1c4230b7576a44614 | [] | no_license | stillme/altmetrics | 241c02ae5476964561c8c210548edf6dbef06cd4 | 4c52ea324b22ae467f9ca49b2c070393c7dec3e7 | refs/heads/master | 2021-01-01T19:06:43.927717 | 2015-09-16T18:17:59 | 2015-09-16T18:17:59 | 42,600,064 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,380 | r | Rcommands.R | counts_raw <- read.delim("data/counts-raw.txt.gz")
dim(counts_raw)
head(counts_raw)
tail(counts_raw)
counts_raw[1, 10]
counts_raw[1:3, 10:12]
counts_raw[1:3, ]
counts_raw[1:10, "pmid"]
str(counts_raw$daysSincePublished)
head(counts_raw$daysSincePublished / 7)
is.numeric(counts_raw$daysSincePublished)
str(counts_raw$jou... |
de5c1e2e9234dd5826e990f20559264a00e4d682 | 0f5fc517c7beb08b4a11fd85749d0d1a50c28f5b | /man/zi_fit_pms.Rd | 43cdda845185aee96f8a896245f039ca7a7f6aaa | [] | no_license | sqyu/ZiDAG | 544de482c6e7a3e35968408826c6136e57d2cb25 | d893be61690031b13ced18b18a7e7c98d4b78804 | refs/heads/master | 2023-02-13T19:04:25.840259 | 2021-01-13T08:16:53 | 2021-01-13T08:16:53 | 239,381,238 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 8,584 | rd | zi_fit_pms.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/zero_fit_pms.R
\name{zi_fit_pms}
\alias{zi_fit_pms}
\title{Fits a Hurdle conditional model with pms parametrization of specified degree.}
\usage{
zi_fit_pms(
V,
Y,
left,
right,
extra_regressors = NULL,
extra_reg_pen_factors = NULL... |
35bf60fca3b79205db54d94c97d1b656b42eb8be | 38c720a2af6d3d1bd8df15eaa42e87e88f1973e5 | /man/as_TSP.Rd | a1c89645b35e473a16b5fa8f7b8c86023f5fba83 | [] | no_license | mllg/tspmeta | a5c2cc6570342ab2e5790f5834a839e34ddd24d4 | db6a458781268a835203e07af9f1b9ece7bcc78c | refs/heads/master | 2020-12-24T23:18:30.852333 | 2016-06-15T08:32:43 | 2016-06-15T08:32:43 | 61,191,420 | 0 | 0 | null | 2016-06-15T08:33:05 | 2016-06-15T08:33:05 | null | UTF-8 | R | false | false | 375 | rd | as_TSP.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/tsp_instance.R
\name{as_TSP}
\alias{as_TSP}
\title{Convert to TSP instance object of package TSP.}
\usage{
as_TSP(x)
}
\arguments{
\item{x}{[\code{\link{tsp_instance}}]\cr
TSP instance.}
}
\value{
[\code{\link[TSP]{TSP}}].
}
\descript... |
d41dd1876b312043ea6e91a0ac2300ddba41a9f3 | 36e610c417776307c63228a461cdffd9dda8cc20 | /man/annual.precipitation.totals.Madison.Rd | 2b9899e9e403f50414ca862ac5368c7396e3fcff | [] | no_license | cran/climtrends | 79ee1153c09144ed0b575a11e0182ec6f29ab8df | d588ac8e4a1883cfead7579068226b6d1e9afab2 | refs/heads/master | 2021-01-21T14:04:48.389588 | 2016-05-26T17:56:25 | 2016-05-26T17:56:25 | 48,078,006 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 979 | rd | annual.precipitation.totals.Madison.Rd | \name{annual.precipitation.totals.Madison}
\alias{annual.precipitation.totals.Madison}
\title{Annual precipitation totals in inches Madison (Wisconsin) }
\usage{annual.precipitation.totals.Madison}
\description{\code{annual.precipitation.totals.Madison} contains the annual precipitation totals in inches from Madison (W... |
69c35f13b4d400f7ee393dc09b59928cb781dbd9 | b9ed9dfe570c8f7e9baedd176886c9aee8868bca | /Linear_Model.R | b7feaaccdb987b3b8266d6128d3b0242090b3062 | [
"MIT"
] | permissive | Jun4871/R_programing | 2b7b182ef2b2b5594356ca76f7870c881b030443 | 147dba41a62c0523f5aadd1240c5b67bab303576 | refs/heads/master | 2020-12-10T11:53:14.106811 | 2020-04-25T10:14:49 | 2020-04-25T10:14:49 | 233,586,246 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 166 | r | Linear_Model.R | head(diamonds)
lmDiamond <- lm(price ~ carat, data = diamonds)
summary(lmDiamond)
par(mfrow <- c(2,2))
plot(lmDiamond)
|
9bc4dcbdbcde9e56d964efe2ea1eda4138a13c8b | 411ab0a304cf6445f9189e3e1cd9a760f545ea1a | /man/str_entre.Rd | 07398ca685dbd35a121ba0fe104d593d9d33b07f | [
"MIT"
] | permissive | caayala/desuctools | ea059f0f0673eab4ba2c17f10a00f8d008881b43 | 7200f6d0a392967ce6eb7399690c94c66954e5b1 | refs/heads/master | 2023-08-29T04:46:53.667717 | 2023-08-07T21:26:01 | 2023-08-07T21:26:01 | 291,334,718 | 0 | 0 | NOASSERTION | 2020-08-29T19:20:58 | 2020-08-29T19:20:57 | null | UTF-8 | R | false | true | 520 | rd | str_entre.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/helpers_variables.R
\name{str_entre}
\alias{str_entre}
\title{Extrae string entre dos textos}
\usage{
str_entre(text, ini = "", fin = "")
}
\arguments{
\item{text}{string. Puede ser un named string.}
\item{ini}{string, desde donde se extrae ... |
b63eb799112fa0640ca83d02cced9fa33f24ea89 | bdbfe5e0501ccf1dc6bf26d6939d8cddf353160f | /NewRScript.R | 57a4054c335cb3b5fd585f944a2bf51eec02dd65 | [] | no_license | MickeyGitHub/Rcollaboration | acf5ec99fa000f1567f42e1c91d6673a8da564aa | 647c9d43d5ea61eab7eb6e1699f485310df053df | refs/heads/master | 2020-04-01T21:54:25.016602 | 2018-10-18T20:21:48 | 2018-10-18T20:21:48 | 153,681,262 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 106 | r | NewRScript.R | # this is a new test script
myfucition <- function(x,y)
if(x>y) {
print("x is bigger")
}
|
9bbd85dc2a66652e4d333f41320df03b9e85d503 | f70a41e996e76adbe3bb29f40c47fe7046e9b7d3 | /Interns/ClaireMarie/slope_aspect_elevation.R | c9962eea86f012dd68c4cd3c0304a34849210f27 | [] | no_license | DrJonYearsley/Phenograss | 5c541e25fafff1ee6d1f746f5a4e40129b1abd2a | d3cce1fa799939f6f84201561a7b08907c56ea7f | refs/heads/master | 2022-08-12T10:50:32.685141 | 2022-07-15T14:37:31 | 2022-07-15T14:37:31 | 221,275,083 | 2 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 3,082 | r | slope_aspect_elevation.R | # Slope aspect of SRTM elevation
#
# Claire-Marie Alla
# 29/06/2021
# ++++++++++++++++++++++++++++++++++++++++++++++
rm(list=ls())
library(sf)
library(stars)
library(raster)
library(ggplot2)
library(dplyr)
library(biwavelet)
library(grid)
elevation_dir = '~/Stage/Data_created/elevation_SRTM3_square'
... |
b5650e57a0c367c088efe0da8562fbb2716ab1a3 | 423e53b3ca3e81220813d88be963cb4b8b3fd9b2 | /man/print.survFitCstExp.Rd | 91fcadd7a12d75fa8c61cb61ef905b1392d99f5d | [] | no_license | cran/morse | 9715ca0a55cdf7c42ecfd13039065a88a273f6dd | 262ed591e1b80190e1cea7a3ae93164b0d030df2 | refs/heads/master | 2022-11-08T06:29:36.523446 | 2022-10-28T10:45:09 | 2022-10-28T10:45:09 | 20,999,880 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 942 | rd | print.survFitCstExp.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/print.survFitCstExp.R
\name{print.survFitCstExp}
\alias{print.survFitCstExp}
\title{Print of \code{survFit} object}
\usage{
\method{print}{survFitCstExp}(x, ...)
}
\arguments{
\item{x}{An object of class \code{survFitCstExp}}
\item{\dots}{Fu... |
69378e7b7d30a833bb5bf624028b7ee1f8f8cd0f | ad522819f54aa659c951ff39fff1dda0fff0f89f | /R/tranforms.R | 3180108ff48d864f1347af79f697e475b0c896fe | [
"MIT"
] | permissive | davidbrae/torchaudio | 4dbc4e12067b14dedd8fa785a6b753719e39b0d3 | d20ccc237a8eff58e77bb8e3f08ef24150a4fc4e | refs/heads/master | 2023-07-20T16:06:59.791249 | 2021-08-29T19:16:50 | 2021-08-29T19:16:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 36,364 | r | tranforms.R | #' Spectrogram
#'
#' Create a spectrogram or a batch of spectrograms from a raw audio signal.
#' The spectrogram can be either magnitude-only or complex.
#'
#' @param pad (integer): Two sided padding of signal
#' @param window_fn (tensor or function): Window tensor that is applied/multiplied to each
#' frame/window or ... |
a3eb9b63b553488218dfe4e96c8c9ddadec33c82 | fa44e7a7a231c54078a56ead85da8cd26eef2e64 | /Codici/04 - Veneto/01.1 - Creazione frontiera/Codice/Functions.R | 9f2f9d358c6eb1e418ee816b604247d1fb3fbe5a | [] | no_license | GabrieleMazza/TesiDiLaurea | 1018d2d7aeaba3894f4042488a04f8923bb0a759 | 952e34355c2e718f180c4b79b55f1e48af33c887 | refs/heads/master | 2021-01-23T07:21:28.876038 | 2015-04-24T13:38:10 | 2015-04-24T13:38:10 | 26,230,512 | 0 | 0 | null | null | null | null | WINDOWS-1252 | R | false | false | 13,332 | r | Functions.R | # FUNZIONI DI APPOGGIO
SquareEuclideanDistance = function (p1,p2)
{
dist=sqrt((p1[1]+p2[1])^2+(p1[1]+p2[1])^2)
return(dist)
}
CleanPoints = function (Triang_old, IDDelete, x_old, y_old)
{
Triang<-Triang_old[-IDDelete,]
N=length(x_old)
#Creo un vettore di FALSE
#Se un punto è ritrovato nella tr... |
f22d2ce77413d0d01308b67dfb9e9d2813d4140b | 9b97439cf690d1ee155625b954984115ea2d30d6 | /Exploratory DA/plot2.R | 59f74cd9acf86006c0709311866f9c8534a7baf5 | [] | no_license | skdery/datasciencecoursera | b2dfc405bb360fff84833dd12e2fb0e7ac4f0531 | f33c711ad1b671bf0e0df319b3605b67fe4a1b38 | refs/heads/master | 2020-05-31T15:07:18.769269 | 2015-01-25T17:45:22 | 2015-01-25T17:45:22 | 27,982,522 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,133 | r | plot2.R | ## This program uses data from the National Emissions Inventory (NEI) to answer the question:
## Have total emissions from PM2.5 decreased in the Baltimore City, Maryland (fips == "24510") from 1999 to 2008?
## Use the base plotting system to make a plot answering this question.
##
## set working directory
setwd("~/... |
6fa73cd5d2f1b2896bf4a5eff942931c12c38f97 | 91a3c67cf3ffb822d6978c36eda17b9df6b602dc | /RCode/plotDiffCombinedResults.R | 3cf0a56caf0085804e3ea82dea90c0dd816d2c43 | [] | no_license | bhklab/SkinFibrosis | eab2a6d355923c18067f391cb4be95857b832f72 | 05bc8b8d2f345214daf8b4c0602fdeb4912af2eb | refs/heads/master | 2021-03-27T10:11:01.847777 | 2020-04-24T18:11:17 | 2020-04-24T18:11:17 | 76,301,956 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 958 | r | plotDiffCombinedResults.R |
plotDiffCombinedResults <- function() {
load("../Output/qSig850-diffExpAnalysis.RData")
iix <- which(rownames(res)=="caffeic acid")
resdiff <- res
load("../Output/qSig-KEGG.RData")
which(rownames(res)=="caffeic acid")
# # #[1] 307
resCombined <- res
#
ii <- match(rownames(resdiff), rownames(resCombined))
all(ro... |
3a8f00213e358d5576d98064560c5bb31fa779ed | d2753667d25bd6a6052c56227aea3fc0dcdbed04 | /randomization/Block Randomization - Stratified and assigned to dataset.R | 89bcad0f88ce079c099efd5f88ab1521da5d4d28 | [] | no_license | tkappen/MiscCodeR | e73f47aaab7e6c81f7f1e7851f736ccd036cc6bc | 614a93852f1d0c3be4a0c33475eaafe484527ae4 | refs/heads/master | 2021-01-20T19:40:23.919224 | 2020-06-30T15:31:53 | 2020-06-30T15:31:53 | 60,108,458 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 969 | r | Block Randomization - Stratified and assigned to dataset.R | #############################################################################
# Randomize cohort per stratum as blocks and assign the value to the dataset
#############################################################################
library(blockrand)
library(dplyr)
library(tidyr)
# Creat function that has a set of r... |
03f2e9ae2f864415aba86a441f4d29454d1d089f | 519de33eed25dab10c39472442dc733cc63e4dd5 | /plot4.R | fb077aabbe1a630ec4c8ca20db95540d291f8c9e | [] | no_license | gdaliva/ExData_Plotting1 | 2dd45192f63cd567372b158e03207028a80e7716 | bb16102037fd090270faa5dbb28f6e75b78e5e50 | refs/heads/master | 2021-08-07T19:13:30.497183 | 2017-11-08T20:11:56 | 2017-11-08T20:11:56 | 108,753,201 | 0 | 0 | null | 2017-10-29T16:58:44 | 2017-10-29T16:58:44 | null | UTF-8 | R | false | false | 804 | r | plot4.R | par(mfcol=c(2,2))
plot(data2$DateTime, as.numeric(as.character(data2$Global_active_power)),type='l',ylab="Global Active Power", xlab="")
plot(data2$DateTime, as.numeric(as.character(data2$Sub_metering_1)),type='l', xlab="",ylab ="Energy sub metering")
lines(data2$DateTime, as.numeric(as.character(data2$Sub_metering_2))... |
d1b337def185c03f412ac2863aeffe98a84bb997 | 9333d3d6013f8745635590278330e899feaca70e | /plot2.R | 626502b3813f6f704ba8fd878e68555e3348a1b1 | [] | no_license | jasanglay/ExData_Plotting1 | 11cb8744a3ce19f908912f1a2cdf0bc332d28df5 | 6a73056fd41140625550a43c0be140e6177d372e | refs/heads/master | 2021-03-19T15:31:41.519632 | 2018-02-27T14:59:13 | 2018-02-27T14:59:13 | 123,110,865 | 0 | 0 | null | 2018-02-27T10:09:54 | 2018-02-27T10:09:53 | null | UTF-8 | R | false | false | 706 | r | plot2.R | fileUrl <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
zipfile <- "./Data.zip"
txtfile <- "./Data/household_power_consumption.txt"
download.file(fileUrl,zipfile)
unzip(zipfile,overwrite = TRUE,exdir = "./Data")
alldata <- read.table(txtfile,sep = ";",header = TRUE)
pdat... |
e0f8018bf7ae8825257f43bc7352cd460ac5972d | c3352c6e4471c5e7c8682825b84dd8270b31507d | /R/mesh-plot.R | 07437ed2fb5315381ad195e078035265000fd668 | [] | no_license | MilesMcBain/quadmesh | 2f6f7a17276a55ffb74fc2fdfa39d12a41dd54b3 | 712dfa1d9c05d936222c0e5768866ed118690623 | refs/heads/master | 2020-04-07T04:44:14.081500 | 2018-11-18T09:57:59 | 2018-11-18T09:57:59 | 158,069,412 | 1 | 0 | null | 2018-11-18T09:49:24 | 2018-11-18T09:49:24 | null | UTF-8 | R | false | false | 7,126 | r | mesh-plot.R | scl <- function(x) {
rg <- range(x, na.rm = TRUE);
(x - rg[1])/diff(rg)
}
#' Plot as a mesh
#'
#' Convert to a quadmesh and plot in efficient vectorized form using 'grid'.
#'
#' The mesh may be reprojected prior to plotting using the 'crs' argument to
#' define the target map projection in 'PROJ string' format. (T... |
a71c1d08cf4c87feb1aafa974c5f5d2d1c4f196c | 0e84ee8922b96bd526883e3b7dcab258c278d84e | /R/data_consumption_income.R | a647f93b2f895f56a09b1d9ba2ef246bbceef1f6 | [] | no_license | zhaoxue-xmu/RDA | 8f9f68620d9c1393c66e0efd1c9ccda7e1008ad6 | ea8ed94680c1964f491bbbe17e22c9a52659f39c | refs/heads/master | 2021-01-17T16:00:27.495392 | 2017-03-24T15:42:06 | 2017-03-24T15:42:06 | 82,945,310 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 287 | r | data_consumption_income.R | #'Dataset of income and consumption in chapter12
#'
#'A dataset containing year,consumption and income 2 variables of 36 objects
#'
#'@format a dataframe with 36 rows and 3 variables
#'\describe{
#' \item{Y}{year}
#' \item{C}{consumption}
#' \item{Y}{income}
#'}
"consumption_income"
|
a24e1d0c083503c9a7628dc3cea570a412888dc4 | b735abf24f9d9f86f2b00041b860674a888ca69f | /model/predict_returns.R | 441b4db37e19f84949d458ff76ed589229fd8f4f | [] | no_license | hanlin891016/trade-the-tweet | 1a7c30afd2cb57dd95097f34ecdcbc629cc94a85 | 9beebd74530f049220da02a2fc81c6b5e2ffbbd0 | refs/heads/master | 2021-06-03T03:56:42.057528 | 2016-08-20T03:42:04 | 2016-08-20T03:42:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 678 | r | predict_returns.R | predict_returns <- function(Y, returns, y) {
# Given historical matrix of word frequencies and historical returns, computes
# the predicted return
#
# Args:
# Y: weighted term-document matrix
# returns: the matrix of historical returns
# y: the vector of term frequencies we'd like to predict
# ... |
7c149f195e310396aea0f3a1af648d352c537710 | 8cf4416f7e4c9016d85a616aaae3fbf0d48cf9a4 | /r/Old/Sparrow20090803.r | e6b72021ed576380c2c3243ae87a2eec57b15b5a | [] | no_license | willbmisled/MRB1 | 35f9bb4ef9279f55b1348b8b3fbda6543ddbc70d | af39fb697255df15ae41131d76c6fcf552a55a70 | refs/heads/master | 2020-07-20T08:43:00.460675 | 2017-06-14T14:09:38 | 2017-06-14T14:09:38 | 94,337,564 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,229 | r | Sparrow20090803.r | rm(list=ls(all=T)) #clear workspace
# Read data-****Make Sure the Path Is Correct****
require(RODBC) #Package RODBC must be installed
con <- odbcConnectAccess("//AA.AD.EPA.GOV/ORD/NAR/USERS/EC2/wmilstea/Net MyDocuments/EPA/Data/Sparrow/MRB1Sparrow/MRB1Sparrow.mdb")
get <- sqlQuery(con, "
SELECT MRB1_WBIDLakes.WB_... |
b04335b96a052245f845d9a3c3c2d70c3fd2adbf | 29eb088d0563d95616a53ba6984882c70671fb7c | /man/allDags.Rd | e22063095344e6c9a979576360520ca871e65749 | [] | no_license | SharonLutz/DisentangleSNP | 6936f3a23d494db342fd48ea7f716071867c5dea | 95f911e86760f7c9973587bd110343406423adfb | refs/heads/master | 2021-09-14T20:06:00.996421 | 2018-05-18T16:04:03 | 2018-05-18T16:04:03 | 103,295,591 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 502 | rd | allDags.Rd | \name{allDags}
\alias{allDags}
\docType{data}
\title{
allDags
}
\description{
%% ~~ A concise (1-5 lines) description of the dataset. ~~
}
\usage{data("allDags")}
\format{
The format is:
logi [1:25, 1:9] FALSE FALSE FALSE FALSE FALSE FALSE ...
}
\details{
%% ~~ If necessary, more details than the __description__ a... |
812701adf10370e6adbe1f26501aef85a6cd7adc | 3ea8066910a8b32d9a4b3204e720a45f06405efb | /R/LDTFPsurvival.R | f9a27d0092eb63ba53b8e9e2cde15bed030a5af5 | [] | no_license | cran/DPpackage | ae76a06a3f35dc88d1f18476e2470473a67e2277 | 33af05b258c49ae4826655dd196d0ecbf5a008b1 | refs/heads/master | 2020-05-16T23:58:39.158728 | 2018-01-06T07:39:08 | 2018-01-06T07:39:08 | 17,678,687 | 3 | 7 | null | null | null | null | UTF-8 | R | false | false | 26,145 | r | LDTFPsurvival.R | ### LDTFPsurvival.R
### Fit a linear dependent TF process for survival data.
###
### Copyright: Alejandro Jara, 2011-2012.
### Last modification: 11-11-2011.
###
### This program is free software; you can redistribute it and/or modify
### it under the terms of the GNU General Public License as publi... |
d7e9cd840078b6f15c23eb16cb709dfb994bdb0b | dd1af48ab0f0e40b531c8f4d55c2b1ddebbef887 | /R/RcppExports.R | 3fdbd1e8c04d05fe700259c64d65d667a5c17d24 | [] | no_license | dfalbel/testerror | b295947b132e8d8e86608146ed1fd3a2aaf4cea6 | 8ee827bd80239b836e0f78ca704320b46fec1bf1 | refs/heads/master | 2020-04-20T11:43:52.669750 | 2019-02-02T11:28:47 | 2019-02-02T11:28:47 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 327 | r | RcppExports.R | # Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
test_error <- function() {
invisible(.Call('_testerror_test_error', PACKAGE = 'testerror'))
}
test_error2 <- function() {
invisible(.Call('_testerror_test_error2', PACKAGE = 'testerror... |
fffe992ead267222d7695a5e1527fc9b961f3b2c | fb509a77664ed87f5a0d1c7114154cc181411757 | /C_country_pred.r | bd40d560f257c25fb50ed750bdba7b3a72221818 | [] | no_license | wbickelmann/MLProjects | e91fefb5af33544fd91829087320e796b4233694 | 9c2acb40d247591510ec2f11e45d06c6598c7623 | refs/heads/master | 2020-03-11T05:50:48.711112 | 2018-05-01T05:07:15 | 2018-05-01T05:07:15 | 129,814,262 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,397 | r | C_country_pred.r | library(caret)
library(tidyverse)
library(xgboost)
setwd('C:/Users/Willi/OneDrive/Documents/MLProjects')
combi_c<-read.csv("C_hhold_train.csv",stringsAsFactors = TRUE, header = TRUE)
combi_c_indiv <- read.csv("C_indiv_train.csv", stringsAsFactors = TRUE, header = TRUE)
combi_c_indiv <- subset( combi_c_indiv, select = ... |
c65fba069704a6aa67913bb7fdd1212846250421 | 3df087ccb93de55ddde9fc02a1805432a9a21343 | /man-roxygen/variable-rf.R | d61aec9905da57cf0dbae193183078e3f34b312a | [] | no_license | thismely/ExpectedReturns | efc587e92f60cc2bf966a6e477b68025ed5c7806 | ba2507aa1572b2a27d2f6639d45f98e5b2533ece | refs/heads/master | 2023-07-06T20:13:46.863687 | 2021-07-11T17:33:30 | 2021-07-11T17:33:30 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 381 | r | variable-rf.R | #' @section RF variable:
#'
#' The `RF` variable refers to the *risk-free rate*. It depends on the period been
#' considered and on the country. For example, for U.S. monthly data series is the
#' one month *T-Bill* return.
#' The `RF` data series distributed by K. R. French with the Fama-French factors
#' data are usu... |
588cea514132aad23d5434b0ef2dee865fc169f1 | 4de2f9cdcd44de1e2b323b2d640c2231c4bf6010 | /main.R | 2440592ab205be9921a9edbfef812fb1a854ef13 | [] | no_license | mjenniferli02/shiny_health_tracker | 9c9a5a5d1a87d8174d95239ea2df3a039fccaeca | 759280f632c4e5be32bfa9b162f95f6f78563ca0 | refs/heads/master | 2021-04-16T00:45:12.149802 | 2020-03-27T00:24:15 | 2020-03-27T00:24:15 | 249,313,561 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 272 | r | main.R | library(data.table)
library(ggplot2)
library(lubridate)
library(tidyverse)
data <- fread("data/sleep-score/sleep_score.csv")
head(data)
data <- data %>% mutate(timestamp=ymd(substr(timestamp, 1, 10)))
ggplot(data)+geom_line(aes(x=timestamp, y=overall_score))
str(data)
|
3a7af803b21352483b76397b50b26dd0039181e6 | aa7618d72787ca663c3dc461df3cfb111b7fde2f | /ReadingData.R | 66bb2a4ff40041859b42173b87649c7c53737b65 | [] | no_license | PelzKo/VisMetabo | 57105af244ca56a06794738db1e1a5a20b6433c3 | 0c3061c93eeeca9cd732bf86e48843bb7417bb2d | refs/heads/master | 2023-03-28T04:03:00.473836 | 2021-03-25T03:00:43 | 2021-03-25T03:00:43 | 276,921,411 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,539 | r | ReadingData.R | library("openxlsx")
#dftest <- "C:/Users/Konstantin/Desktop/Uni/6Semester/BachelorArbeit/BeispielDaten/metabExampleMaleFemale.xlsx"
#df <- read.xlsx("C:/Users/Konstantin/Desktop/Uni/6Semester/BachelorArbeit/BeispielDaten/QMDiab_metabolomics_Preprocessed.xlsx", sheet = 1)
readFile <- function(filePath, fileSheet = 1){... |
a437434a3a501eb1afe88bdfc51500055c3937d6 | 67dcbff196434716013f8dfcf7a18e28b8db65d1 | /625-2-MLE.R | 51bf656ddc95a929d6fb988bfe70e96ea132399b | [] | no_license | clabornd/survival_MLE | 0b85e6bec85239412502baa5ab84ddb7b3879068 | f311c965bacc56d21d69718ef3d8e4c3b29cb5e3 | refs/heads/master | 2021-08-20T10:18:50.721266 | 2017-11-28T21:48:14 | 2017-11-28T21:48:14 | 111,720,399 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,526 | r | 625-2-MLE.R | library(ggplot2)
library(purrr)
#############Plot Likelihood functions###########
l_true <- function(lambda, x){(lambda^length(x)*exp(-lambda*sum(x)))/max(lambda^length(x)*exp(-lambda*sum(x)))}
l_censored <- function(lambda, x, censor_time){
if(length(censor_time) == 1) {censor_time = rep(censor_time, length(x))}
... |
9d3421c63d13de3fb247fa598d5fb39ac454c762 | 8f549e33631a13e2b3c05fd02605f31a6f5c079c | /R/EstimateInHospitalMortality.R | a4e3a78d110af8cd13567010f1cb9bbcaa4c6a30 | [
"MIT"
] | permissive | martingerdin/bengaltiger | 07e60275560af5ed3c6df090f94a8d427796e29e | 2662bb36540699a51e6558b542008d07035a98e1 | refs/heads/master | 2021-07-03T12:29:20.911428 | 2020-02-25T11:45:47 | 2020-02-25T11:45:47 | 144,838,020 | 3 | 4 | MIT | 2020-09-02T10:24:17 | 2018-08-15T10:12:31 | R | UTF-8 | R | false | false | 8,237 | r | EstimateInHospitalMortality.R | #' Estimate in hospital mortality
#'
#' Estimates the proportion of patients who died in hospital with a bootstrap
#' confidence interval if requested.
#' @param study.sample Data frame. The study sample. No default.
#' @param variable.name Character vector of length 1. The name of the in
#' hospital mortality vari... |
926559f3e361d500a4ee03c36d95667f655025a7 | a3a59ebe1a41f1bc23d641e0f26673c684ecf72b | /tests/testthat.R | 5cd0178e157a78a638ba1f43394cc8f8059ea27a | [] | no_license | gabrielodom/pathwayPCA | 78c801aaf51c6f16eaac1e2bbbd7c7bb743492c8 | 552e1f378040e6080aa3ac13a7f8a302e579532d | refs/heads/master | 2023-07-08T14:17:13.486479 | 2023-06-28T17:29:22 | 2023-06-28T17:29:22 | 107,602,989 | 12 | 2 | null | 2019-03-28T19:43:40 | 2017-10-19T21:57:30 | R | UTF-8 | R | false | false | 64 | r | testthat.R | library(testthat)
library(pathwayPCA)
test_check("pathwayPCA")
|
0e685dfc3bce332bdeac302c5a726be2cf67bd4c | 9b57bf7e2fb3f68221875091db1bd3e93cc85e41 | /old/full_1_5_2nd/create_main_files.R | 1f1f883976e4ecef9cab0030e0537e953c52b3ae | [] | no_license | mastoffel/imputation_eddie | 7d617ee7f1badf5c69e91cc53161d6ff2b9fb760 | 8945fab33ec30a8b7c317d9ae7f8243ea77537c6 | refs/heads/master | 2020-05-31T15:38:51.923234 | 2020-05-25T15:13:24 | 2020-05-25T15:13:24 | 190,361,962 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,988 | r | create_main_files.R | # Creating the genotype files and other files for AlphaImpute
# this script outputs three files:
# (1) Genotypes.txt: complete genotype data, can be filter for chromosomes
# (2) to_be_imputed_index.txt: index of SNPs which have to be masked and imputed
# (3) to_be_imputed.txt: names of SNPs
# (4) AlphaImputeLinux
# (5)... |
7f56078375522854e267cd3c43af38d0d8a1ab00 | 16b3a68ca34ca6eaf6b5e5264a8944355ff9fef2 | /TestingFile2.R | 5b03b732a13ce740b46e2dd1187ebca445ae354f | [] | no_license | sanjayram77003/Testing | 78a2d4ba41d234f1984bfce03ae32af6f15b1a7d | 73442ec6f2b03b8370f2c867365ccf7eea9e90d3 | refs/heads/master | 2022-12-04T17:38:30.910883 | 2020-08-26T06:04:53 | 2020-08-26T06:04:53 | 290,405,858 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 19 | r | TestingFile2.R | Print("Successful") |
e433de97facaf7eef0efe9ec68204ec7241ea3f2 | 4fb31dff9ccd46ff6c0020c208a5d204cea619c1 | /data_validation.R | 85f00e2664f48f2b8a4d039a06ebd294f6cac679 | [
"Apache-2.0"
] | permissive | ctsit/nSOFA_calculation | 4e99784fb75ac86e3461c51972815d10e86da55a | c433d743be2a52930735283ef7d63dd9b59c5df6 | refs/heads/master | 2023-04-18T22:50:48.275326 | 2020-09-28T16:34:33 | 2020-09-28T16:34:33 | 259,997,057 | 0 | 2 | Apache-2.0 | 2020-07-10T17:53:36 | 2020-04-29T17:37:39 | R | UTF-8 | R | false | false | 2,625 | r | data_validation.R | # IMPORTANT: make_nsofa_dataset.R must first be run to create the nsofa_scores dataset
source("functions.R")
load_libraries()
# compare to nsofa data provided by irb ---------------------------------------
# data from 2018 onwards
read_irb_nsofa <- get_data("nsofa_scores.csv") %>%
mutate(q1hr = floor_date(record... |
bed951cb1215acea62368848b1b2fdf72ca3f5e7 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/rbokeh/examples/tool_wheel_zoom.Rd.R | 579392e789bc7564b377cc84895e1fc4feff7dd3 | [] | 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 | 269 | r | tool_wheel_zoom.Rd.R | library(rbokeh)
### Name: tool_wheel_zoom
### Title: Add "wheel_zoom" tool to a Bokeh figure
### Aliases: tool_wheel_zoom
### ** Examples
## No test:
# only zoom on x axis
figure() %>% ly_points(1:10) %>%
tool_wheel_zoom(dimensions = "height")
## End(No test)
|
5904e08326347db541f75014d4bc0b05ac97bb25 | e0b165551ab06067e6eb33199a058a54922e6471 | /dom.R | 80c2bfedc2dbddc153c571429188dd519c74aadc | [] | no_license | brunocarlin/R_Faculdade | 62b2a8e08201c4e4bed26bf3b16234dbfc8ed202 | 649df8cb1470a6347ac049bff040b75d70c558dc | refs/heads/master | 2020-03-25T11:19:42.240008 | 2018-10-25T12:35:18 | 2018-10-25T12:35:18 | 143,727,900 | 0 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 2,463 | r | dom.R | # PNAD 2015 domicílios
rm(list = ls())
library(tidyverse)
# cuidado com o tamanho do terceiro campo
col_sizes <- c(4, 2, 6, 3, 2, 2, 2, 1, 1, 1, 1, 2, 2, 1, 12, 12, 1, 1, 1, 1, 1, 1, 1, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 4, 2, 12, 3, 1... |
c9f740a0db3e87e01e1ef44ecb36eba7f4e84bad | 31ea8595b1b023988c18875d71ce2a5202c5f3ea | /exdata/PA1/plot2.R | 5ce22173132c20e5a19003596ff3e18b8d2bcab7 | [] | no_license | datawrecker/datasciencecoursera | 3fef8322c062442e2a8222e36bdf187462c295b3 | ce1d0940fec6c0f4123d48b51a30598c24bbf074 | refs/heads/master | 2020-04-05T15:20:08.066152 | 2015-03-21T15:10:58 | 2015-03-21T15:10:58 | 31,636,947 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 819 | r | plot2.R | epc <- read.table("household_power_consumption.txt",
header=T, sep=";", colClasses=
c("character", "character", "numeric",
"numeric", "numeric", "numeric",
"numeric", "numeric", "numeric"),
na.strings="?"
)[66637:(66637... |
bd87fb2a8f4c0ddd32406de327ee9cd99fff32c5 | a2401f4ec2060730abf0f8ce3d98dd1f19800e1f | /Annotation/UCSC_hg19_sequences.R | c6d092de11816236a9798daa3392379bce73cac4 | [
"CC0-1.0"
] | permissive | ahalfpen727/Bioconductor-Resources | a7705d4d66dedf01a4359cf1c27fe93b0083ed5c | de405694e31b4da5f8709f61bd57ab8d518f9318 | refs/heads/master | 2021-07-04T01:30:32.430821 | 2020-10-20T01:55:51 | 2020-10-20T01:55:51 | 190,797,935 | 1 | 0 | null | 2019-10-09T04:36:10 | 2019-06-07T19:27:29 | R | UTF-8 | R | false | false | 32,176 | r | UCSC_hg19_sequences.R | Full genome sequences for Homo sapiens (UCSC version hg38)
Description
Full genome sequences for Homo sapiens (Human) as provided by UCSC (hg38, Dec. 2013) and stored in Biostrings objects.
Note
This BSgenome data package was made from the following source data files:
hg38.2bit from http://hgdownload.cse.ucsc.edu/go... |
04f31a603a0ddd9cf4198ec5f99d021a05f5f910 | fdfc22afa8f51ac83096fc8dbb145909d9c61edc | /man/refresh_covidregionaldata_canada.Rd | fdf667b8f0f34af730c374c6011ccd46e1eaa74c | [
"MIT"
] | permissive | GuilhermeShinobe/covidregionaldata | 1581cc8fbc92123646f934854a25e5452710bfe0 | c1f0b5c6ab5284ac6cf9608b64e002c757bd1da7 | refs/heads/master | 2022-12-05T20:36:09.681272 | 2020-09-02T12:41:17 | 2020-09-02T12:41:17 | 292,276,446 | 0 | 0 | NOASSERTION | 2020-09-02T12:27:20 | 2020-09-02T12:27:19 | null | UTF-8 | R | false | true | 510 | rd | refresh_covidregionaldata_canada.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/covid19R_wrappers.R
\name{refresh_covidregionaldata_canada}
\alias{refresh_covidregionaldata_canada}
\title{Get daily Canada COVID-19 count data by Province/Territory}
\usage{
refresh_covidregionaldata_canada()
}
\value{
A tibble of COVID cas... |
46288819c26c216d860b65ece688d787b6f16171 | 248f9e3cb1784c975b34229f9aa48a01dfadc0bc | /project1/plot3.R | 6800cf5a9814aadccf04e142dff095977ecc635b | [] | no_license | shengbing/ExData_Plotting1 | bc9d9da56fb30be8bd1e70fb3f89d4eb3dfd5bcb | 32557019b4ae7c6065be4564b728d886420ca9c5 | refs/heads/master | 2021-01-19T06:55:35.236228 | 2014-09-04T04:10:32 | 2014-09-04T04:10:32 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,318 | r | plot3.R | #project1
#download dataset mannually
setwd("C:/Users/Shengbing/Documents/R/expl_data_ana")
#loadint the data. It is important to specify that sep=';'; missing data are automatically converted to 'NA'
raw.data = read.csv(file = 'household_power_consumption.txt', sep = ';')
##convert Date and Time variables
raw.data$Dat... |
2875824faf0f7ac71e6ab54c1ed17aa8686dc230 | c6a6b77f3b71ea68f1281b043dd60f17dd85381c | /R/methods-SnpSet.R | 67f373cbed55d030ce10688d650de77b1d13bd82 | [] | no_license | benilton/oligoClasses | df76a4ee4d755342ae32b07c9acb5355153e3f4f | be0e1088c52ee8827c86f061e80ffe9b44982a88 | refs/heads/master | 2021-01-10T21:40:35.903511 | 2019-11-23T12:22:08 | 2019-11-23T12:22:08 | 1,779,156 | 3 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,595 | r | methods-SnpSet.R | ##
## Directly from Biobase
##
setMethod("initialize", "SnpSet2",
function(.Object,
assayData = assayDataNew(call = call,
callProbability = callProbability, ...),
phenoData = annotatedDataFrameFrom(assayData, byrow=FALSE),
... |
923acdb1feb491c001234061ee2a6c7bbdb53f68 | 0f75e8fa0c7c8d700245f66e8434d67f52e1ae54 | /man/bvarpost.Rd | 0ee6a5581d47086c156d7f5f5d0707cecc095119 | [] | no_license | franzmohr/bvartools | a7ff34088268911d00e398afc24b054ed85d4c5d | ea828293eaabe2895357bb4302842427ff3e95de | refs/heads/master | 2023-08-31T01:48:14.192410 | 2023-08-30T18:54:10 | 2023-08-30T18:54:10 | 155,453,026 | 23 | 14 | null | null | null | null | UTF-8 | R | false | true | 2,613 | rd | bvarpost.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bvarpost.R
\name{bvarpost}
\alias{bvarpost}
\title{Posterior Simulation for BVAR Models}
\usage{
bvarpost(object)
}
\arguments{
\item{object}{an object of class \code{"bvarmodel"}, usually, a result of a call to \code{\link{gen_var}}
in combi... |
a17d5a40974e568a938a19f167a10a5d861952ab | 62b54d124457474124c5fe950e66619a068c33e9 | /scripts/run_archr.R | 1876fd5fe1684ca823757e41d5332e43cf2c8cbb | [] | no_license | juliabelk/brioschi_2023 | aeb90f3114fa6a6bf4c7689c2287627f77564711 | 9a10d8d4ba95d0d73892288c28607c7f6089de1b | refs/heads/main | 2023-04-15T17:50:31.514310 | 2022-11-26T03:38:40 | 2022-11-26T03:38:40 | 565,594,368 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,216 | r | run_archr.R | suppressMessages({
library(ArchR)
library(dplyr)
library(parallel)
library(hexbin)
library(BSgenome.Hsapiens.UCSC.hg19)
library(BSgenome.Hsapiens.UCSC.hg38)
library(BSgenome.Mmusculus.UCSC.mm10)
})
getGenomeInfo <- function(genome_id) {
if (genome_id == "mm10") {
data("geneAnnoMm10")
data("ge... |
4d24dd6cc36cdfa7d4485d8ffcdf59e0be78b5a5 | 43590cd9ec1bfa7d9b5fa1b066c0b17c7811de06 | /man/getACHO.Rd | 927014be18041a062ed3921a5eb3b440b7496f5c | [] | no_license | Tr1n0m/acho | bc713f145e5c74ded22b9d04449ccef07b7916f0 | 8359b2ecd28019776afe1052f9990fbe040e0431 | refs/heads/main | 2022-12-25T20:07:44.898144 | 2020-10-01T02:16:04 | 2020-10-01T02:16:04 | 300,114,680 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 832 | rd | getACHO.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/getAcho.R
\name{getACHO}
\alias{getACHO}
\title{The base ACHO function}
\usage{
getACHO(data1, data2, acho_plot = FALSE)
}
\arguments{
\item{data1}{first dataset (1D/2D).}
\item{data2}{second dataset (1D/2D).}
\item{acho_plot}{Determines if... |
7a27279d9dc4e072ade56b7d80a9e8ca7019c4f1 | e7118b8251f67f440b8ba4634ba6c40440dd43e8 | /instagram_get.R | d89aee043fadd3a4d053cf82f513d9505856b58f | [] | no_license | furukama/instagram | f27c3de6471ccbec5d445ae45e358526263cccc7 | bfb8147a9d3f49c41f65a5f82bcf2a200e559906 | refs/heads/master | 2021-01-19T14:10:07.359934 | 2014-01-02T11:39:49 | 2014-01-02T11:39:49 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,322 | r | instagram_get.R | #-------------------------------------------------------------------
# Downloading Instagram pictures for a hashtag or location
# Benedikt Koehler, 2013
# @furukama
#-------------------------------------------------------------------
library(RCurl)
library(RJSONIO)
# Login credentials
token <- "" # API key for Instag... |
3c219a5e172c4160b9fb9aff350698988e3b739c | a65a5ed2eef4df4551df848938bc375198e2054c | /wnt_pathway/align_network.R | db748755f3d71c2de37d3fb1884b309dcea79999 | [] | no_license | wenrurumon/directed_network | b7e103f71c14e9f2c253f02547428dd871c1f733 | 1ea8489bb8587be2cf007964abfe68fc469289f4 | refs/heads/master | 2020-07-16T20:03:46.237202 | 2019-11-27T09:31:41 | 2019-11-27T09:31:41 | 73,941,622 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 417 | r | align_network.R |
ref <- read.table('clipboard',header=T)
g.ref <- graph_from_data_frame(ref)
from <- sem[1,1]
to <- sem[1,2]
valii <- function(from,to,g.ref){
ifrom <- which(names(V(g.ref))==from)
ito <- which(names(V(g.ref))==to)
shortest_paths(g.ref,V(g.ref)[ifrom],V(g.ref)[ito])
}
test <- lapply(1:nrow(sem),function(i){
fr... |
a8a757fdf2ee26587058096ff18b5eb1ee91de4b | 5e9de5406a07f31bac45f88dd7335b37051cb780 | /scripts/paper1/drought experiment models.R | c2275b04c498a2c959758b1a33451e431df80074 | [] | no_license | alanaroseo/fogdata | 1887323215c6a5ccaced85279299ee4e560aea54 | 3d961adab6a1d2da2983f599a8964ebf9b132059 | refs/heads/master | 2021-07-02T21:19:29.623811 | 2020-08-25T02:04:08 | 2020-08-25T02:04:08 | 144,756,073 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,221 | r | drought experiment models.R | #write.csv(data.frame(summary(mod)$coefficients), file="model_table.csv")
library("stargazer")
library(gridExtra)
library(grid)
library(investr)
library(AICcmodavg)
library(nlme)
library(lme4)
library(lmerTest)
library(lattice)
#coefficients(mod) # model coefficients
#confint(mod, level=0.95) # CIs for model paramete... |
01cb62de8aea90dd1aac97581696243bd84a3118 | eae783ecfcdeb9a969ec6b2087ecb1772f682f38 | /UserInterface_InputData/ui.R | 76f253f265cb919da8d641b253f643524ad80e22 | [] | no_license | Assemi/MAGMA | 2963fe28190318176180c4855e23566db99e4894 | 35e50cf8e9cb57f4524fcac68fb908a43fe85955 | refs/heads/master | 2023-03-18T18:16:44.653048 | 2020-01-14T17:48:09 | 2020-01-14T17:48:09 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 30,826 | r | ui.R |
library(shiny)
shinyUI(
fluidPage(
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# Heading Text ----
# Create and display heading text
fluidRow( column( 8, headerPanel('MAGMA Input CSV Creator'), offse... |
ed528d24c3107a7651acfd2b0401853794e1e2f9 | acb0fffc554ae76533ba600f04e4628315b1cd95 | /R/pCO2_computation_script.R | 9af23f896b7044b8127272e8361ada78d6642b08 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | lukeloken/USBRDelta | 83826e12a5b5a2e81adeb2119e9c2599a5f8b870 | fd6569385776d4579748b6422b5153e64606e0ba | refs/heads/master | 2021-06-09T19:08:01.976985 | 2020-05-28T21:51:10 | 2020-05-28T21:51:10 | 145,152,807 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,852 | r | pCO2_computation_script.R |
## Functions and script to compute pCO2 concentration from headspace gas samples
#Adapted by A. Smits from Matlab code
# Adapted by S. Sadro from R code
# created by J. Coloso based on what J. Cole used at the Carry Institute
# and an excel program created by S. Hamilton 2003
# computations assume negligible salinity... |
be06ec49782181b79b9cced1f6d67df8b1a48a84 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/metafor/examples/dat.nielweise2008.Rd.R | a2f3d59375b810310f5654a8b86425b8b1f63de5 | [] | 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 | 723 | r | dat.nielweise2008.Rd.R | library(metafor)
### Name: dat.nielweise2008
### Title: Studies on Anti-Infective-Treated Central Venous Catheters for
### Prevention of Catheter-Related Bloodstream Infections
### Aliases: dat.nielweise2008
### Keywords: datasets
### ** Examples
### load data
dat <- get(data(dat.nielweise2008))
### standard (in... |
5ad58e24237f56d6481cae90ee3074d63a7cc440 | f9762620931c83c67a5d82a4245b6da355e909a3 | /R/BiocNeighborParam-class.R | 6a4c6ac1121594c6a374ed1e733c7c849767991f | [] | no_license | LTLA/BiocNeighbors | 0a5bbdb50a7c6283c04677bbdd79d0b6a8940fba | 8a58137641e9413393553f8f03f0ac3207ba738f | refs/heads/master | 2022-11-24T12:17:57.745775 | 2022-11-08T19:21:31 | 2022-11-08T19:21:31 | 137,922,813 | 5 | 10 | null | 2020-11-14T06:55:51 | 2018-06-19T17:19:14 | R | UTF-8 | R | false | false | 2,887 | r | BiocNeighborParam-class.R | #' The BiocNeighborParam class
#'
#' A virtual class for specifying the type of nearest-neighbor search algorithm and associated parameters.
#'
#' @details
#' The BiocNeighborParam class is a virtual base class on which other parameter objects are built.
#' There are currently 4 concrete subclasses:
#' \describe{
#' ... |
925619c2463e1cfabbfa83fb38857042460287c3 | 46816a1aca9538d4ec1344a40c16253378bd77e7 | /Scraper.R | c9166373ef26ec9562a183d7d8b709e0912ee53f | [] | no_license | srepho/US-Sports-Scraping | 1fe304ceb796a440c680a16680e495fb75330636 | d717dca8657db07ab592cf1e5630de7a1fba0cf6 | refs/heads/master | 2016-09-07T18:59:52.154065 | 2014-05-03T12:51:17 | 2014-05-03T12:51:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 735 | r | Scraper.R | ############################################
# Web Scraper
# by Stephen Oates
############################################
#We will start off using the XML library (even though its HTML!)
library(XML)
library(stringr)
url1 <- "http://scores.espn.go.com/ncf/playbyplay?gameId=33... |
3db47e0f475cfe6cfb8c097105d7e5afb490a41f | dde0bdc929870e5a049b9f81589f405b2b2a1280 | /modelCode/SI_simulations/plot_richness_variability_8species.R | 01f328974cdff56529e8bf847d072ee35b71bc55 | [
"MIT"
] | permissive | atredennick/Coexistence-Stability | 9ee87d09f11269188f321b977576685a9dac2eb1 | 55ea5912f28655d82b4098e3cf950fc75908ddcc | refs/heads/master | 2020-04-03T20:04:41.255744 | 2017-09-26T13:07:01 | 2017-09-26T13:07:01 | 24,862,907 | 2 | 0 | null | 2017-04-18T19:36:32 | 2014-10-06T20:11:43 | R | UTF-8 | R | false | false | 4,600 | r | plot_richness_variability_8species.R | ## plot_richness_variability.R
####
#### LOAD LIBRARIES
####
library(ggplot2)
library(ggthemes)
library(gridExtra)
library(plyr)
library(reshape2)
library(synchrony)
library(RColorBrewer)
library(viridis)
####
#### INITIALIZATIONS
####
# Select path to the results and figures
path2results <- "../../simulationR... |
4d406fb15e1e6e7e434dec4274375a08f0f1a718 | 1a8b647c530b69766f5a715891c8c1fe7dec3d04 | /man/CloudProvider-class.Rd | 1996449a0321b58150554a393161c090659eb1d2 | [] | no_license | cran/DockerParallel | 0b15d2fbb833182f1870484a0266d148d58f372c | e6278f65ba3b1c2633b69d97d34c0373eff02a92 | refs/heads/master | 2023-06-09T00:10:57.303177 | 2021-06-23T12:00:02 | 2021-06-23T12:00:02 | 364,306,712 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 277 | rd | CloudProvider-class.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/AAA.R
\docType{class}
\name{CloudProvider-class}
\alias{CloudProvider-class}
\alias{.CloudProvider}
\title{The root class of the cloud provider}
\description{
The root class of the cloud provider
}
|
ec2712a3e7bf0912e1316ede121ea3dcca86cf7f | 57aa23b02213a3216e3cb1d153673b7e12160757 | /SHA/YT data/01 - YT_demographic_setup.R | 3be4a4815343e686585d7ff52f92ec96fd0ec7cb | [
"MIT"
] | permissive | PHSKC-APDE/Housing | 38c96d8502dc50518601cf2012631a49ad159d79 | 2a3951fa16e79d8d83a7cfe32880d115a7c30213 | refs/heads/main | 2023-09-02T19:48:15.033921 | 2023-08-11T20:30:13 | 2023-08-11T20:30:13 | 68,620,327 | 5 | 6 | MIT | 2023-09-12T22:44:01 | 2016-09-19T15:42:58 | R | UTF-8 | R | false | false | 7,061 | r | 01 - YT_demographic_setup.R | ###############################################################################
# OVERVIEW:
# Code to examine Yesler Terrace and Scattered sites data (housing and health)
#
# STEPS:
# 01 - Set up YT parameters in combined PHA/Medicaid data ### (THIS CODE) ###
# 02 - Conduct demographic analyses and produce visualizatio... |
061de232d25b03635e42e0f349cbfc9b25f8abf4 | a3c78700a65f10714471a0d307ab984e8a71644d | /modules/assim.sequential/man/assess.params.Rd | 24c873b53b26cb1e75794255f0c2cec216ede627 | [
"NCSA",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | PecanProject/pecan | e42a8a6a0fc9c0bb624e0743ab891f6cf131ed3f | ce327b92bf14498fa32fcf4ef500a7a5db5c9c6c | refs/heads/develop | 2023-08-31T23:30:32.388665 | 2023-08-28T13:53:32 | 2023-08-28T13:53:32 | 6,857,384 | 187 | 217 | NOASSERTION | 2023-09-14T01:40:24 | 2012-11-25T23:48:26 | R | UTF-8 | R | false | true | 617 | rd | assess.params.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/assess.params.R
\name{assess.params}
\alias{assess.params}
\alias{assessParams}
\title{assess.params}
\usage{
assessParams(dat, Xt, wts = NULL, mu_f_TRUE = NULL, P_f_TRUE = NULL)
}
\arguments{
\item{dat}{MCMC output}
\item{Xt}{ensemble outpu... |
6d3aaaa1e088e840924db7a989b176dc0666f6e9 | b56ad2e238af61a08368b52a06b86649724d57e7 | /CODE_CHUNKS/make_net2.R | 7dce6d203906866afdeede2397782ad96fe68396 | [
"BSD-3-Clause"
] | permissive | ryscott5/eparTextTools | 113b835df4df2f97be55a32a41f8d7778ad304c6 | 7849d9bcaabb8001a3b04d35aea48369014f265c | refs/heads/master | 2021-05-01T04:44:54.727927 | 2017-10-02T19:13:43 | 2017-10-02T19:13:43 | 63,177,507 | 2 | 3 | null | null | null | null | UTF-8 | R | false | false | 24,142 | r | make_net2.R | #start with first noun
#build tree to all verbs, all nouns
library(devtools)
library(roxygen2)
library(stringr)
library(data.table)
library(igraph)
library(networkD3)
library(RSQLite)
matchtable<-readRDS("../Research.Grants/matchtable.rds")
igraphob_object<-function(WORD,mtable,W,inputWord=TRUE,sankey=FALSE,verbfilte... |
1809bc44d4bc6462c8ba8baa4a4d4a94ac9e5c56 | bbffe8845045c6e4a9e121bef78c8a4d8b2b51c2 | /man/empty.Rd | 36bf7b775c2a8fe441b0b2388b128982e9363e85 | [] | no_license | vsbuffalo/rivr | 43d799b9af22332b648f15d70191439b3224c75b | 0ffe216939d45333a2b4688f68712ec86ea823f1 | refs/heads/master | 2016-09-11T04:53:15.119943 | 2015-04-02T00:49:14 | 2015-04-02T00:49:14 | 32,969,361 | 4 | 1 | null | null | null | null | UTF-8 | R | false | false | 286 | rd | empty.Rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/exception_handler.R
\name{empty}
\alias{empty}
\title{Determine if stream/iterator is empty}
\usage{
empty(x)
}
\arguments{
\item{x}{Iterator}
}
\description{
Determine if stream/iterator is empty
}
|
540d1bc4cc8013dae1c85ac5d0857ba40b41d6d3 | 2a7e77565c33e6b5d92ce6702b4a5fd96f80d7d0 | /fuzzedpackages/JSM/R/InitValMultGeneric.R | 37e6eaee2cddcebc4122da02562d7f8b17d38894 | [] | no_license | akhikolla/testpackages | 62ccaeed866e2194652b65e7360987b3b20df7e7 | 01259c3543febc89955ea5b79f3a08d3afe57e95 | refs/heads/master | 2023-02-18T03:50:28.288006 | 2021-01-18T13:23:32 | 2021-01-18T13:23:32 | 329,981,898 | 7 | 1 | null | null | null | null | UTF-8 | R | false | false | 5,337 | r | InitValMultGeneric.R |
#=============== Initial Value Calculation for Model II with NMRE ===============#
InitValMultGeneric <- function (gamma, B.st, n, Y.st, ni, model, ID, Index, B, Btime, Btime2, start, stop, event, Z, ncz, Ztime2, Index2, Index1, rho, iter, nk, d, Ztime22, Ztime, tol.P) {
BTg <- lapply(B.st, function(x) as.vector... |
a5bd4aaabbba7a219571161a68f4404ea4f474ed | d63505181503615a8d4cbe39a1c0ace9eeb1c36e | /real-data/real-data-univariate/Stomach-data-univariate-wo-cohort.R | 8be486a600adb75d748beb416f97b1a0ba364c01 | [] | no_license | papezneuroO/Project-thesis_Helenerb | d1eebd76e2d067aad949c2cc8e9da79a18aaaecb | 7de5aeee10dfcf6ee6cb904477bc0d446869ffee | refs/heads/main | 2023-06-01T10:22:09.799608 | 2021-06-16T12:01:55 | 2021-06-16T12:01:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,385 | r | Stomach-data-univariate-wo-cohort.R | # Replicate of Real-data-univariate-v1, using the stomach-cancer data instead of
# the lung cancer data.
library(INLA)
library(inlabru)
library(ggplot2)
library(patchwork)
library(tidyverse)
library(lubridate)
library(readxl)
# ---- read data from excel files ----
# read population data
population <- read_exce... |
dc7022a45a3a77dd121d750b803991b7fe3c0dee | 0a906cf8b1b7da2aea87de958e3662870df49727 | /diceR/inst/testfiles/connectivity_matrix/libFuzzer_connectivity_matrix/connectivity_matrix_valgrind_files/1609958624-test.R | 743c45c6e39d0e9c9c239135fbc837dc983d0317 | [] | no_license | akhikolla/updated-only-Issues | a85c887f0e1aae8a8dc358717d55b21678d04660 | 7d74489dfc7ddfec3955ae7891f15e920cad2e0c | refs/heads/master | 2023-04-13T08:22:15.699449 | 2021-04-21T16:25:35 | 2021-04-21T16:25:35 | 360,232,775 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 111 | r | 1609958624-test.R | testlist <- list(x = 2.16443570677964e-312)
result <- do.call(diceR:::connectivity_matrix,testlist)
str(result) |
b322e315ce08ee613fec79f743abc0785e40dff6 | 8f9fea74327fb383b19bdc95b1b1cf703136f433 | /R/global_vars_funs.R | 8d3b2f3888d6aefa588921537a3c4fd4480e859c | [
"Apache-2.0"
] | permissive | rtlemos/rcsurplus1d | a4b98c7ca5e7e16c74506f954de8e4a5059260a3 | 69ef6212b0df416f2ab15ffb147dcd5cc7e93e56 | refs/heads/master | 2021-04-30T16:20:27.719003 | 2020-06-19T01:19:07 | 2020-06-19T01:19:07 | 56,413,138 | 1 | 0 | null | 2016-04-17T02:24:12 | 2016-04-17T01:16:24 | null | UTF-8 | R | false | false | 803 | r | global_vars_funs.R | #' Global specs for rcsurplus
#'
#' \code{rcsurplus1d.defaults} is a list that contains default
#' parameters for this package
#' @param priorK prior for carrying capacity
#' @param priorr prior for intrinsic growth rate
#' @param priorq prior for catchability
#' @param priors prior for observational variance
#' @par... |
8b8679a3a00ed23e0db2d3e367b25601c65bcfd5 | 9463fd30587b1c2608bc53c0e442bab2cd899dd6 | /Modules/downmodule_ui.R | d22c5f42ebd46850768e2ce7fce306c303a328a2 | [] | no_license | microgenomics/HumanMicrobiomeAnalysis | f72c9b3f217a4ea92843ccd8b707e023f80440d9 | a83cd8f4b3ee2c1511e38c45ba8ba37dedaf9a18 | refs/heads/master | 2022-04-30T18:58:25.008184 | 2022-03-08T10:34:41 | 2022-03-08T10:34:41 | 198,847,636 | 2 | 2 | null | 2019-08-01T16:15:45 | 2019-07-25T14:32:45 | R | UTF-8 | R | false | false | 663 | r | downmodule_ui.R | DownloadUI<- function(id){
ns <- NS(id)
tabPanel("Download Data",
sidebarPanel(
selectInput(inputId = ns("DataBase"), label="Data Base",
choices = c("Complete","OneMore","Depths"),
selected = c("Complete")),
uiOutput(ns("SpeciesQ... |
48e1575841b0f0f8605e61ec2b5a854802e951b1 | d9396697675606d97824a787a7b0f8c19619b3f8 | /man/ExpDesigns.Rd | bf6f7c5aa337c9f65851dddf9b34cf438298ee14 | [] | no_license | qchengray/sommer | 45859dbd6550a6c7069ab4a2d1904da6ed41f6b1 | aca3863a7e1df8b462212c40468e44083c76812f | refs/heads/master | 2021-01-23T04:38:57.350625 | 2017-08-24T07:25:49 | 2017-08-24T07:25:49 | 102,450,483 | 1 | 0 | null | 2017-09-05T07:45:38 | 2017-09-05T07:45:37 | null | UTF-8 | R | false | false | 7,557 | rd | ExpDesigns.Rd | \name{ExpDesigns}
\alias{ExpDesigns}
\docType{data}
\title{
Data for different experimental designs
}
\description{
The following data is a list containing data frames for different type of experimental designs relevant in plant breeding:
1) Augmented designs (2 examples)
2) Incomplete block designs (1 ex... |
4187a9285decbdc2c39115a254f515a48202b02e | 5e65f58f231b331ba0cddb512398e39cda3a9a67 | /kew_imperial_grasses_project/Support/handler.R | 4ccf788d281c01b954d1790355c7d1a415694692 | [] | no_license | cwkprojects/myprojects | 719644297fbf8c9269f9e3e440be9988a859df57 | 0bed4cd790cf4e4fa18d4683afadfee400ab7b33 | refs/heads/master | 2021-06-20T20:57:39.324961 | 2017-08-02T18:56:32 | 2017-08-02T18:56:32 | 98,444,604 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 1,873 | r | handler.R | # This script can be used to replicate the analysis undertaken in the summer
# project "Where are the missing grasses?" based at RBG Kew in summer 2016.
#
# For a full explanation of the script and the methods it employs, as well as
# a guide, please see the readme in this repository.
# ... |
ca271d03b95a36afbc8a07d4c0f517ceda43e8f2 | 580be5feec96aee48f98f02683409e373d024783 | /man/c_layout.Rd | 8e7fe7e97d97f62ed014845f2dfbee657062a6e9 | [
"MIT"
] | permissive | han-tun/charter | 86a8ea8b0024785fa7b63b6ee1fa12250008b737 | 6b77bdac72fe27629c90045e6c0b77bca12030f3 | refs/heads/master | 2022-12-30T06:31:57.701194 | 2020-10-13T19:09:40 | 2020-10-13T19:09:40 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 573 | rd | c_layout.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/layout.R
\name{c_layout}
\alias{c_layout}
\title{Layout}
\usage{
c_layout(c, left = NULL, right = NULL, top = NULL, bottom = NULL)
}
\arguments{
\item{c}{An object of class \code{charter} as returned by \code{\link{c_hart}}.}
\item{left, rig... |
7ed0527d0be8ba821429619fb4db2c43e1209acd | 231c176babe88ed186d9edc92799224fac38a75b | /Código/universal 3.0.r | 3e244e3bc47558bde0b0091df8d562c3c058f6ec | [
"Apache-2.0"
] | permissive | ronyrst/analise_temperaturas | b8ca877ea9561f4d389a6e41e46e8d407e76c316 | 2df83e1a9b777436bad3e8e377e4fb316e39cbbf | refs/heads/master | 2020-03-31T00:33:52.713797 | 2019-05-07T22:21:36 | 2019-05-07T22:21:36 | 151,744,099 | 0 | 0 | null | null | null | null | ISO-8859-1 | R | false | false | 89,470 | r | universal 3.0.r | #### FUNCIONALIDADES (a partir da linha 33):
# -'save_data' salva matriz, data.frame ou lista em um arquivo .csv.
# -'ctrab_na' para uso interno dos outros programas.
# -'ctrab_cons' para uso interno dos outros programas.
# -'confere_na' mostra quantos NAs existem em um data.frame já na estrutura de convert_univers... |
a09b90e419a748845097683c93fb78a351caba51 | 122976d6e18856ea2b2c3d876f4d4773209b1fbc | /plot5.R | 5265ca78395e2b06a0d4fe699242423d27b3d0bc | [] | no_license | ovijive/ExData_Plotting2 | 3378618c3ce289478e942acdc6d1a4511f90646e | fafa6ff0d0263362ad5bab0d06b6f34b6d13512a | refs/heads/master | 2021-01-10T05:20:54.502836 | 2016-02-01T22:24:20 | 2016-02-01T22:24:20 | 50,853,377 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 625 | r | plot5.R | # read RDS files
NEI <- readRDS("summarySCC_PM25.rds")
SCC <- readRDS("Source_Classification_Code.rds")
#Baltimore City (fips: 24510)
baltEmiss = subset(NEI, fips==24510 & type =="ON-ROAD")
#Baltimore City emission
totalEmi = aggregate(Emissions ~ year, data = baltEmiss, sum)
#load ggplot2blibrary
library(ggplot2)
... |
31048a5fb28063a27689b215d84cb7428e05116f | bd207458397914151d99414c01662054c31f8e74 | /example.R | 9495adaae22b750d7897017b8ad689a9f8d12e09 | [] | no_license | ineswilms/taglasso | 99f262e2cae38f297db282554da37bf1668b88ee | 6201ac5b4431e2b60bf4a7d99467e100b6863ab4 | refs/heads/main | 2023-03-01T18:35:37.718303 | 2021-01-29T10:00:56 | 2021-01-29T10:00:56 | 321,664,356 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,824 | r | example.R | rm(list=ls())
#### Install package from GitHub ####
install.packages("devtools")
devtools::install_github("ineswilms/taglasso")
library(taglasso)
#### Pre-process the data ####
data('rv')
rv_data <- rv$data
A <- rv$A
# Estimate HAR models
estimate.HAR <- function(y){
# Function : HAR model with daily, weekly and mo... |
e529484365a05598afb3560ed0e8082b8cd6e42e | 4aa6996769d3096a62c87834daed4ce11b5a0ec3 | /R/utils.r | 8b0e89b3b6835775326606eee649c0acd702b917 | [] | no_license | selcukfidan47/testthat | a308a5f8a1637ad6956299def805ab7d4c96cdff | df4ca8c6975d0b45845be481cda89bebe3d8c09e | refs/heads/master | 2021-01-18T08:50:19.832177 | 2016-02-21T10:56:26 | 2016-02-21T10:56:26 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 327 | r | utils.r | `%||%` <- function(a, b) if (is.null(a)) b else a
starts_with <- function(string, prefix) {
substr(string, 1, nchar(prefix)) == prefix
}
is_directory <- function(x) file.info(x)$isdir
is_readable <- function(x) file.access(x, 4) == 0
null <- function(...) invisible()
klass <- function(x) paste(class(x), collapse ... |
724e83a4bf48865fe1f73b562cda42020a7bcaf8 | 136ecc91ee6a29dcd414aba36e19c709c8ce805e | /DataMining.R | 15d28ee3391f6592375d7dc773bcb8915ed17616 | [] | no_license | PabloArmasM/Data-Stream-Mining-para-el-modelado-del-tra-fico-en-Nueva-York | 1c1e05a39fc1b7f77d01eb13a1c194500241b77b | 5d2a7e7cc26f50d67434bd4270f95950afb73119 | refs/heads/master | 2020-12-02T06:24:10.192824 | 2017-07-10T22:45:59 | 2017-07-10T22:45:59 | 96,827,947 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,364 | r | DataMining.R | require('XML')
library("neuralnet")
library("animation")
require("ggplot2")
## Installation from github
##
library("devtools")
require(RMOA)
##
library("arules")
setwd("/home/loedded/Escritorio/XML")
f <- as.formula("Class ~ c1 + c2 + c3 + c4 + c5 + c6 + c7 + c8 + c9 + c10 + c11 + c12 + c13 + c14 + c15 + c16 + c... |
238a6c17539d42e15fc6ce92ba36385231c38807 | f0489c47853fc78a49bfbc28ca3cf39798b17431 | /man/consensusmap-NMFfitX-method.Rd | 1597423b90fd18755c52cfa548adbb0c97c196ce | [] | no_license | pooranis/NMF | a7de482922ea433a4d4037d817886ac39032018e | c9db15c9f54df320635066779ad1fb466bf73217 | refs/heads/master | 2021-01-17T17:11:00.727502 | 2019-06-26T07:00:09 | 2019-06-26T07:00:09 | 53,220,016 | 0 | 0 | null | 2016-03-05T19:46:24 | 2016-03-05T19:46:24 | null | UTF-8 | R | false | true | 574 | rd | consensusmap-NMFfitX-method.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/NMFSet-class.R
\docType{methods}
\name{consensusmap,NMFfitX-method}
\alias{consensusmap,NMFfitX-method}
\title{Plots a heatmap of the consensus matrix obtained when fitting an NMF model with multiple runs.}
\usage{
\S4method{consensusmap}{NMF... |
74f1e2cb00407640a7c8279d738e5450a626cb41 | 6927c39fa8f7762025a999f912f27da02fe88d26 | /code/cats_vs_dogs_SMALL.R | 2680a855e57c026abd9ccdab719ad7f7f0787350 | [] | no_license | uwpz/DL | af6eb9e915e43e81d08d15c6f3f2ebe0dc6ca5e3 | 23948db5715b52323756b783799998fc976df2a7 | refs/heads/master | 2020-07-12T00:19:46.486800 | 2019-08-28T17:48:54 | 2019-08-28T17:48:54 | 204,673,607 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,451 | r | cats_vs_dogs_SMALL.R |
#######################################################################################################################-
#|||| Initialize and ETL ||||----
#######################################################################################################################-
## Libraries
library(reticulate)
library(m... |
6173f9bb7321284e7a471fc4a2e0f1d103cd36af | f32dbf645fa99d7348210951818da2275f9c3602 | /R/MTMdisp.R | 662401ac391c68e181897a37afabffdf487a26cc | [] | no_license | cran/RSEIS | 68f9b760cde47cb5dc40f52c71f302cf43c56286 | 877a512c8d450ab381de51bbb405da4507e19227 | refs/heads/master | 2023-08-25T02:13:28.165769 | 2023-08-19T12:32:32 | 2023-08-19T14:30:39 | 17,713,884 | 2 | 4 | null | null | null | null | UTF-8 | R | false | false | 1,121 | r | MTMdisp.R | `MTMdisp` <-
function(a, f1=f1, f2=f2, len2=1024, PLOT=FALSE)
{
### calculate and plot an MTM spectrum
# a = list(y=ampv, dt=0.008)
if(missing(PLOT)) { PLOT=TRUE }
if(missing(f1)) { f1 = 0.01 }
if(missing(f2)) { f2 = 10 }
len = length(a$y)
if(missing(len2))
{
len2 = 2*next2(len)
}
i... |
776769573609cea12ef77573d2c79953f64a560a | 9cc8d14accb873157822c8790e480ba66e42cb81 | /R/Challenge1_no_solutions.R | ed069790269fd310d26a470bd0e58af9d94c2173 | [
"MIT"
] | permissive | seedpcseed/R-Learning | bfa873fef46cc506c39936505ba294458bff7889 | e30858c668509adfcc793c3b4b10491d1f86a4a6 | refs/heads/master | 2022-11-17T02:39:12.566115 | 2020-07-07T14:28:04 | 2020-07-07T14:28:04 | 268,669,278 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 775 | r | Challenge1_no_solutions.R | # CHALLENGE: Plot the COVID-19 cases and deaths by
#
# You want to get public data about COVID-19
# infections and deaths but
# you want to focus on what happened in
# Midwestern states in April
# Consider what libraries you need to get the data,
# filter the data, and visualize the data
# Go for it!
# libr... |
4b4a19a52bf3b16e1de2efa6258d95a1145d4c94 | da5d74f9895e2c00947a42805f2af73d209082a1 | /ReadingInMinfiFile.R | e2103a5f2a61ce26d4bea94e6efeeb318aef5467 | [
"MIT"
] | permissive | xuefenfei712/sheepclock | b3321bdbee158f249af153d38599e75eeaf68ee2 | b0eaec0b96afcc35f0d60982eb3d1215ea329d64 | refs/heads/main | 2023-06-03T08:50:48.750018 | 2021-06-24T00:49:17 | 2021-06-24T00:49:17 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,810 | r | ReadingInMinfiFile.R | #read in minfi normalised beta values
minfibetas <- read.csv("/Users/victoriasugrue/Documents/Data_Files/MASTERS_DoNotEdit/MASTER_Betas_Minfi_Normalised.csv", header=FALSE)
#transpose the dataframe and remove unneeded columns
tminfibetas <- as.data.frame(t(minfibetas[,-c(1:2)]))
#read in file for headers and transpos... |
f634272110a7cf3bc1345c3f6bc056a77af44896 | c7dd9f32f1b740b3f9b7f45917e0796aea6bbfd8 | /Legacy/Keio_analysis_combined_old.R | 3e3b7815892718c4e62977fdeb973875bae4a61c | [] | no_license | PNorvaisas/5FU_knockouts | 9488845fe17a7a01d52068aaddf56c006b686dd4 | d6b65ee1d0a79129592d0c7e645d72ff14db117c | refs/heads/master | 2021-01-24T00:02:56.536426 | 2018-10-02T16:34:20 | 2018-10-02T16:34:20 | 122,738,398 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 23,287 | r | Keio_analysis_combined_old.R | library('ggplot2')
library('gplots')
library('plyr')
library('reshape2')
library(tidyr)
library(quantreg)
library(ellipse)
#Vennerable installation: install.packages("Vennerable", repos="http://R-Forge.R-project.org")
#library(quantreg)
elipsoid=function(df,xvar,yvar,scale=1,groups=''){
df<-subset(df,!is.na(df[,x... |
8342f3affff711157928c249549215b77ef136e4 | 5713e52ef679c619afaf05f1e1ba6d46ece336ec | /plot1.R | 75a13d75a402cae3a6da407fefd2c53f597cd26a | [] | no_license | threeboys/ExData_Plotting1 | 731932d7c14b046269b8cda135a4c6525770fa14 | bab24ab5f3d0c92bec21703dc2cdf66e819f5af3 | refs/heads/master | 2021-01-15T20:23:15.250350 | 2014-09-07T19:20:09 | 2014-09-07T19:20:09 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 671 | r | plot1.R | ########################################
# plot1.R
# - Drawing plot 1
# - Save plot1.png (Save it to a PNG file with a width of 480 pixels and a height of 480 pixels)
########################################
## locale set to english area
Sys.setlocale("LC_TIME", "C")
source ("./readTidyData.R")
preparedData <- rea... |
006a6da5358eb0ca555424b1b2c71fb1149ff51e | 63d97198709f3368d1c6d36739442efa699fe61d | /advanced algorithm/round3/k-server-analysis-master/data/tests/case054.rd | da217f5eed32f467a724ad08d2602ca8778b50bc | [] | no_license | tawlas/master_2_school_projects | f6138d5ade91e924454b93dd8f4902ca5db6fd3c | 03ce4847155432053d7883f3b5c2debe9fbe1f5f | refs/heads/master | 2023-04-16T15:25:09.640859 | 2021-04-21T03:11:04 | 2021-04-21T03:11:04 | 360,009,035 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,443 | rd | case054.rd | 20
1 [18, 9, 17] 8 8 8 10 10
2 [18, 10, 17] 1 2 10 2 12
3 [18, 9, 17] 1 2 12 2 14
4 [18, 10, 17] 1 2 14 2 16
5 [18, 9, 17] 1 2 16 2 18
6 [18, 10, 17] 1 2 18 2 20
7 [18, 9, 17] 1 2 20 2 22
8 [18, 9, 10] 7 1 21 2 24
9 [3, 9, 10] 5 5 26 10 34
10 [4, 9, 10] 1 2 28 2 36
11 [3, 9, 10] 1 2 30 2 38
12 [4, 9, 10] 1 2 32 2 40
13... |
5c3896d7779e4f11ad84611e00772bae9fa6ee5f | b8d9444434a0ed37cce66230515b5e9436db53b7 | /hw4/do-stepcv.R | d1d4ff34458ae2bea124e3273b15a03ccb7b673b | [] | no_license | zhiminwu29/machine_learning_2021S | 38170f9090bd6d394e4999d4a007f7a0a3e2e2fd | ad003ebd19704565a4f190332a206741b2b2a9bc | refs/heads/master | 2023-04-13T18:48:48.661078 | 2021-04-30T20:10:28 | 2021-04-30T20:10:28 | 340,241,300 | 0 | 1 | null | 2021-04-29T19:38:45 | 2021-02-19T02:53:11 | HTML | UTF-8 | R | false | false | 2,003 | r | do-stepcv.R | library(MASS)
## function to do cv with stepAIC
stepcv = function(ddf,yind,xind,fullform,folds,nstep) {
##function to extract sse using stepAIC
keepf = function(mod,maic) {
yhat = predict(mod,xpred)
return(sum((yhat-ypred)^2))
}
##null model
nullform = as.formula(paste(names(ddf)[yind],"~1... |
5fd52ca7eac35a20a617f2098613d9f8cd1a11d7 | edde3e8b8427fa4802ff9462e2d92e8eedc5ce00 | /man/create_lh_list.Rd | d61dc0208bd19c21505c5b7553cd8e129dcb1001 | [
"MIT"
] | permissive | Henning-Winker/LIME | b0b8933532dbbcf557620e3eabc070483264f94c | 9dcfc7f7d5f56f280767c6900972de94dd1fea3b | refs/heads/master | 2022-11-08T20:23:44.288265 | 2020-06-18T18:23:55 | 2020-06-18T18:23:55 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 4,444 | rd | create_lh_list.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create_lh_list.R
\name{create_lh_list}
\alias{create_lh_list}
\title{Create new life history list}
\usage{
create_lh_list(
vbk,
linf,
lwa,
lwb,
S50,
M50,
S95 = NULL,
M95 = NULL,
Sslope = NULL,
Mslope = NULL,
selex_input ... |
2dbc47b86e62c690959e76880991e2b9bb04cc1c | 49679b97305617476aa1acd685ae31e0c7fadb87 | /R functions/CStask.r | fe594222cfada1165e57d21e5b9b0b5590a1b5a6 | [] | no_license | mvegavillar/Accumbens-Rew-learning | 2541e07dc6e93f7ea1b39516f783f75f97470a20 | be221cf5777ec62365927213c613bc9dd6066664 | refs/heads/master | 2020-05-24T11:19:13.151823 | 2019-07-09T17:01:57 | 2019-07-09T17:01:57 | 187,246,076 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 423 | r | CStask.r | CStask.Rfunc=function(bigoutelement){
out = list(info = bigoutelement$info)
out$receptacleentries = bigoutelement$w
out$receptacleexits = bigoutelement$x
out$CSminuscue = bigoutelement$t
out$CSpluscue = bigoutelement$s
out$laseron = bigoutelement$y
out$rewarddelivery = bigoutelement$u
return(out)
}
sa... |
ef9902d6ed0955511f4c7fd1736edef0d9d3c698 | 339f89e5a10c958859e2ffd369892d6673a38eb3 | /Code/SVM/helper_radial.R | fc2ac624e25c6129cf9d2b34fe70f2796f8fa533 | [] | no_license | pvn25/Hamlet_Extension | 4f7d0e718603a3d9ff638a897ba93fd7d92d562e | 3f5f9fe4ef087385b637552b8ec60be805851648 | refs/heads/master | 2021-01-11T04:39:37.979467 | 2020-09-14T03:36:28 | 2020-09-14T03:36:28 | 71,120,697 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,606 | r | helper_radial.R | #Copyright 2017 Vraj Shah, Arun Kumar
#
#Licensed under the Apache License, Version 2.0 (the "License");
#you may not use this file except in compliance with the License.
#You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#Unless required by applicable law or agreed to in writi... |
8ab42d6807ad521c8dd14f82869e699f92a841eb | c457b4fa4fa50b1767f4766940f42f78e52087bd | /ecosystems/Thomas.R | 5041ff01cdbabe4846e5dd6cb5c9c8b9d8466322 | [] | no_license | alanponce/ESEUR-code-data | f6efefbe63947103868d79c05149077b8353eedf | 9573de006d4327f3ee1bfc823490809cc23e8db8 | refs/heads/master | 2020-04-08T10:11:35.567668 | 2018-11-24T22:49:02 | 2018-11-24T22:49:02 | 159,258,259 | 1 | 0 | null | 2018-11-27T01:38:36 | 2018-11-27T01:38:35 | null | UTF-8 | R | false | false | 1,367 | r | Thomas.R | #
# Thomas.R, 17 Mar 18
# Data from:
# Security metrics for computer systems
# Daniel R. Thomas
#
# Example from:
# Empirical Software Engineering using R
# Derek M. Jones
source("ESEUR_config.r")
library("diagram")
plot_layout(1, 1, default_width=ESEUR_default_width+1,
default_height=ESEUR_default_height+3)
el... |
7c750290ec4c7075f3d0e0ff2384d567272857a5 | 2a2ca3b3c603e39af268a7964062199a8120b44c | /fxrPrototypes/picCorrelation.R | 7a5a1e112c7384ea58e5440b2d434c0c89a06a1d | [] | no_license | arborworkflows/arborCollections | 0953ce7634b17adb696fc19c755553145bee2d31 | 2f301d6c3946d4992dfeb2ec436e7c9bdbfd9ff5 | refs/heads/master | 2021-01-11T10:03:47.664769 | 2018-09-25T19:33:00 | 2018-09-25T19:33:00 | 35,436,091 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 950 | r | picCorrelation.R | library(geiger)
library(aRbor)
table <-
read.csv("/home/lukeh/Documents/arborCollectionsWeb/assets/anolis.csv", row.names=1)
ind_variable<-"SVL"
dep_variable<-"awesomeness"
tree<-read.tree("/home/lukeh/Documents/arborCollectionsWeb/assets/anolis.phy")
plotPICs<-T
# Match tree and tip data
td<-make.treedata(phy, t... |
3c61f2c4fcfff9f264bd6f1661f3eee3e1f43fbc | 3d287de4d79b321e5112ddff1d02fce33841bb5f | /cachematrix.R | 27d32002f94e3b39429e263059dc8648fb596ca1 | [] | no_license | subrata143/ProgrammingAssignment2 | f89c1cca9a8ce7af49efa950a5062c0c78b6fa59 | 922303bff04cd6c58ce380050cc97c0d5219393d | refs/heads/master | 2021-01-15T23:28:27.576018 | 2014-08-24T01:25:44 | 2014-08-24T01:25:44 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,244 | r | cachematrix.R | ## This program contains two functions the 1st one chaches the inverse of a matrix and the second one inverses a matrix if not available in cache. Note that only square matrix can be used.
makeCacheMatrix <- function(x = numeric()) {
mycache <- NULL ## initially cache is set to NULL
# store a matrix
setMa... |
3960195acf241b66a1e1e39eddc7fec950947d96 | 851dfbed249e9672f0f8588f6b75b2fe2743a576 | /Wk11_Workshop_NotesAndCode.R | f7d67f25f8d7967f36bfc7709900055d9bc9863b | [] | no_license | durfey/MSCA_BayesianMethods_class | 9a3f57896ad5284dbd4c56c5df2726a15c3d8bf2 | 38329bced4af80a6da8694f9406e21ae119224f0 | refs/heads/master | 2021-01-19T01:02:08.809158 | 2016-07-01T23:39:16 | 2016-07-01T23:39:16 | 62,424,823 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,319 | r | Wk11_Workshop_NotesAndCode.R | #################################
# Week 11 Workshop Notes & Code #
#################################
library(rstan)
source('//Users/rdurfey/R_misc/BayesianMethods/DBDA2Eprograms/DBDA2E-utilities.R')
##############################
# 1. ANOVA in Bayesian Setup #
##############################
modelString<-"
data {
... |
69a21441a34c6bd0b5218a772600de89e72dade9 | 70a9be4f18fc0749ea4ddb27cfaad33d8734a3ea | /man/build_par.Rd | 171caaa63514e5709f52c6ac0aa74f1c00b71635 | [] | no_license | fickse/RHEM | c40701bf8e16780437ef05476f737321dfa8865e | 875232a26a962efd8ac5217b74f5f6dc2b8ae765 | refs/heads/master | 2020-03-10T11:02:54.882333 | 2018-12-28T23:15:14 | 2018-12-28T23:15:14 | 129,347,032 | 0 | 1 | null | null | null | null | UTF-8 | R | false | true | 1,367 | rd | build_par.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/functions.R
\name{build_par}
\alias{build_par}
\title{Write .par file for input to rhem}
\usage{
build_par(...)
}
\arguments{
\item{...}{named arguments. see \code{details}}
}
\value{
list of inputs for .par file
}
\description{
Write .par fi... |
6f4d02d9c31889afdbadf27bda2cfe700448af41 | 41d7c2ff4628f27213f90aca0be867c0f747b300 | /man/hcsig.Rd | d135411175c6e585d752fafc0460e3ebcdb21103 | [
"CC0-1.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | jlaffy/statistrics | 69e17a043522d3bcad6127127e66eea9649c3a92 | 2de58328790ede712c3aa6bbeccda611d7eaa121 | refs/heads/master | 2020-03-14T03:03:24.759893 | 2018-08-23T12:37:04 | 2018-08-23T12:37:04 | 131,412,171 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,076 | rd | hcsig.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/utils-cluster-significance.R
\name{hcsig}
\alias{hcsig}
\title{hcsig: hcluster Significance}
\usage{
hcsig(k, mat, fc.value = 3, p.value = 10^(-4), p.value.2 = 10^(-5),
pval.adjust = NULL, reorder = TRUE, fc.sort = T, pval.sort = F,
retur... |
c2f3c356d1399633a8cd72e75320a3eb07914f30 | f8b069d84fc20beb5300b26c0df4e31a4b924b4c | /R/zzz.R | 634a8800932fd7a62b482c6d9d6c85572001d876 | [
"MIT"
] | permissive | shanmdphd/PKPDsim | df84dbf4f7ee3be9a081516c3f74a8ac7b85379e | 5aa415da1047795c28091c47623dd0fc4f611c48 | refs/heads/master | 2020-03-26T21:23:52.752205 | 2018-08-20T08:05:04 | 2018-08-20T08:05:04 | 145,385,623 | 0 | 0 | null | 2018-08-20T08:00:51 | 2018-08-20T08:00:51 | null | UTF-8 | R | false | false | 187 | r | zzz.R | # message("\n----\nWarning: \n\nDevelopment of the PKPDsim package has moved from InsightRX/PKPDsim to InsightRX/PKPDsim, please get the latest version from the new repository.\n----\n")
|
e478adbd52e5f6deefb4a2e119e2235235a990a5 | a57e1f283ce9473afc2459cd3cf7ba6ff424e88e | /plot2.R | 29695d21cd97da80ebd0fa1fae6c5c6c7fa0fc9b | [] | no_license | dusanmundjar/EDA-plots | aa31d052f7baf3921053d6ed4e39a9e87f4b8f55 | 85adb8274b5f49ad1d0e30de8be3adcc41d5b509 | refs/heads/master | 2021-01-13T04:34:42.931207 | 2015-02-08T19:03:03 | 2015-02-08T19:03:03 | 30,501,683 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 833 | r | plot2.R | ###import data
data <- read.csv("C:/exdata-data-household_power_consumption/household_power_consumption.txt", sep=";", na.strings="?")
data2 <- data[which(data$Date=="1/2/2007" | data$Date=="2/2/2007"),]
### new variable
dates<-data2$Date
times<-data2$Time
x <- paste(dates, times)
y<-strptime(x, "%d/%m/%Y %H:%M:%S")
... |
b8ea06ca4a29a0425e3f695efcbcbc4236bf7830 | 70e5bc555b9051a2fd043a3c55adcd82cd9bd847 | /run_analysis.R | 728fc714cfc5a8589da2052dd36c4cf214031c24 | [] | no_license | Bogstag/HumanActivityRecognitionUsingSmartphones | 82e02e643a3372d95237fdac9e6434d4704df1e5 | f7cfe73888e64423096c6ce8010aba13510055ce | refs/heads/master | 2016-09-11T04:23:59.485750 | 2014-09-21T17:49:15 | 2014-09-21T17:49:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,044 | r | run_analysis.R | library("plyr")
## Merges the training and the test sets to create one data set
x_test <- read.table("UCI HAR Dataset/test/X_test.txt", header = FALSE)
x_train <- read.table("UCI HAR Dataset/train/X_train.txt", header = FALSE)
subject_train <- read.table("UCI HAR Dataset/train/subject_train.txt", header = FALSE, col.na... |
a2e053b781b67c393055508075f090dff4f01df1 | d57bfd5bbefab86d21ed46b4e15f1d489c61bcbc | /R/fisher_corr.R | eb2378bcaea0c0c7ec590b9097fb9ddc937ebf54 | [] | no_license | cran/smovie | 553d3d6441a762a4b538699c47d028ad4e5c995a | 9a05f94188335a1b79a98bdfa4011bbcbc3033e8 | refs/heads/master | 2021-11-24T16:55:00.478591 | 2021-10-31T04:30:02 | 2021-10-31T04:30:02 | 123,954,735 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,487 | r | fisher_corr.R | #' Fisher's transformation of the product moment correlation coefficient
#'
#' Density, distribution function, quantile function and random generator
#' for the distribution of Fisher's transformation of product moment
#' correlation, based on a random sample from a bivariate normal distribution
#'
#' @param x,q Numeri... |
09a57885a59ac3d64a8045b3db789317ca83e3a5 | 7e1834f16d51844c3ec4fefa1badafe7382784e2 | /app.R | a4385627e2410b018381c03877e7148e782b19a5 | [] | no_license | RforOperations2018/Project_2_afierro | 36735fcd0a0d7ba702f577ee75f91feafde8a0ba | 1fcad9172f6972d63cc1cb3b6ce7384458495ea1 | refs/heads/master | 2020-04-01T21:16:34.570361 | 2018-10-21T17:31:02 | 2018-10-21T17:31:02 | 153,647,327 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,426 | r | app.R | library(shiny)
library(shinydashboard)
library(rgdal)
library(RSocrata)
library(leaflet)
library(leaflet.extras)
library(dplyr)
library(readxl)
library(stringr)
library(httr)
library(jsonlite)
library(ggplot2)
library(reshape2)
library(DT)
library(plotly)
#Load data
schools <- rgdal::readOGR("https://opendata.arcgis.c... |
f2594f9c4489a34e0d47c428460cff693eff8659 | 07469546c11552317e2efa00dcebb823846ba86e | /R/dictionaries-liwc_old.R | 68a630a0e5412c83f6d673e51fc83f0957dc936f | [] | no_license | LuigiC72/quanteda | b846a93e643ab30b419f5bb038592d19f743adf7 | 974b778322a9d56d5678d5a192e1fb69dcf01750 | refs/heads/master | 2021-07-08T04:10:25.684641 | 2017-10-06T08:42:27 | 2017-10-06T08:42:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,370 | r | dictionaries-liwc_old.R | # Import a LIWC-formatted dictionary
#
# Make a flattened dictionary list object from a LIWC dictionary file.
# @param path full pathname of the LIWC-formatted dictionary file (usually a
# file ending in .dic)
# @param enc a valid input encoding for the file to be read, see
# \link{iconvlist}
# @param maxcats the... |
07efe30d307be2a7761b1fed1da090ac8bb2c7f6 | 84e94bd1a156115243b990c56bfa4a107c04a80d | /man/simulateOuterPerformance.Rd | 36cbbe1ed8047c6f756318fc929f03f62ec27b55 | [
"BSD-3-Clause"
] | permissive | jakob-r/mlrOverfit | 54868307513932e8c857a8133a4cfabe9d21a07d | 5d8c1476ebe0156b2a075bd3384c94ec07972b4c | refs/heads/master | 2021-01-01T18:51:05.241275 | 2020-07-01T16:42:16 | 2020-07-01T16:42:16 | 98,448,624 | 3 | 2 | BSD-3-Clause | 2019-07-23T09:11:52 | 2017-07-26T17:27:55 | R | UTF-8 | R | false | true | 558 | rd | simulateOuterPerformance.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/simulateOuterPerformance.R
\name{simulateOuterPerformance}
\alias{simulateOuterPerformance}
\alias{SimulateOuterPerformanceResult}
\title{Simulates the outer test error}
\usage{
simulateOuterPerformance(outer.performance)
}
\arguments{
\item{... |
062b845ff7bd0facd04b749d70b638a42f3a75b7 | 3f90e417415a4b2808bbe4f4cff7601c2272a94e | /Class1RCode-updated.R | e27a41647624161329222d25adc2b4b3c4650a40 | [] | no_license | nuke705/MiscR | f977dcca8ce89e8e73c3b9bef8b5c0c8dd4f6a31 | 8c6005ed053925de0434c084ab5456ea26b6a22f | refs/heads/master | 2020-04-03T07:57:22.358605 | 2018-10-28T21:49:52 | 2018-10-28T21:49:52 | 155,118,918 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,518 | r | Class1RCode-updated.R | # This R Code demonstrates everything we did in class 1 with an example dataset.
# For more detailed and basic examples refer to the presentation.
# Before you work on the code, please set your working directory to the folder that
# contains the sample dataset. You can either do this by navigating to the folde... |
36c6cf4c77339c2bb75f91b5f8aebaa8d8da2413 | 49274f1e603427e17419a480910df649680a02fc | /man/mgmL.Rd | 5a1550b3755f43b18dd954562f70601cfc34333d | [] | no_license | t-arae/prtclmisc | da7b21d9122f5b1a75565f9da1faad4b9e219555 | 08203daa321f63524562d33cca81db976febb1b6 | refs/heads/master | 2021-07-12T06:57:15.555934 | 2020-08-25T07:28:21 | 2020-08-25T07:28:21 | 195,718,678 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 196 | rd | mgmL.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/g_conc.R
\name{mgmL}
\alias{mgmL}
\title{mgmL}
\usage{
mgmL(x)
}
\arguments{
\item{x}{numeric}
}
\description{
mgmL
}
|
7656199ee7f77049d279b73d971cd3c2de07ba11 | 779b83a935336f68204aafb4954dfe81bea3b595 | /demand/man/arima_day.Rd | 536fd75b4e17aec233b8b1a4bed30e7475b75ec2 | [
"MIT"
] | permissive | aidowu/demand_acep | ba42f068efbc613c80b463f9edd98f1fb10fd4ec | 57f838494c60140a17d7a930df4276341e2a0ce8 | refs/heads/master | 2020-05-05T05:55:25.442876 | 2019-08-28T03:13:19 | 2019-08-28T03:13:19 | 179,769,388 | 1 | 0 | MIT | 2019-06-25T04:09:34 | 2019-04-05T23:54:21 | Jupyter Notebook | UTF-8 | R | false | true | 603 | rd | arima_day.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/forecast.R
\name{arima_day}
\alias{arima_day}
\title{arima_day}
\usage{
arima_day(data, meter_name, end_point)
}
\arguments{
\item{data}{Input a dataframe which has peak power values of a virtual meter and the total 4 meters.}
\item{meter_na... |
69ccb3f75419c56ad217de77fa544f3352bb06b0 | 1f9579466118b5303c2681fcc3e87970e94a9eb3 | /global.R | cb36923c646743555835b119a13be37439dde9e8 | [] | no_license | Arevaju/shiny-app | bf2d28761d1cbc7332083575ec30604ea334be3c | 865b1958d586968e0c77b4d367f9f6e14e609112 | refs/heads/master | 2021-01-22T02:33:43.435410 | 2015-07-28T12:24:36 | 2015-07-28T12:24:36 | 21,005,475 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 39 | r | global.R | library(shiny)
load('data.RData')
|
0e2e082da4e54473ed15c5aa01e25bec5e05fbfa | 06b9d2ece554bda6b4402785bc9c7b7a627a6c2f | /man/checkHandlingMortalityConsistency.Rd | 42ed61bdc9b7686d0e0ac1a41c5009aaa8b95243 | [
"MIT"
] | permissive | wStockhausen/rTCSAM2015 | 4f2dd392b32d9a3ea9cce4703e25abde6440e349 | 7cfbe7fd5573486c6d5721264c9d4d6696830a31 | refs/heads/master | 2020-12-26T04:56:03.783011 | 2016-09-30T01:59:06 | 2016-09-30T01:59:06 | 26,103,387 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 870 | rd | checkHandlingMortalityConsistency.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/checkHandlingMortalityConsistency.R
\name{checkHandlingMortalityConsistency}
\alias{checkHandlingMortalityConsistency}
\title{Check handling mortality/fishing equations consistency.}
\usage{
checkHandlingMortalityConsistency(tcsam = NULL, rsi... |
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