content large_stringlengths 0 6.46M | path large_stringlengths 3 331 | license_type large_stringclasses 2
values | repo_name large_stringlengths 5 125 | language large_stringclasses 1
value | is_vendor bool 2
classes | is_generated bool 2
classes | length_bytes int64 4 6.46M | extension large_stringclasses 75
values | text stringlengths 0 6.46M |
|---|---|---|---|---|---|---|---|---|---|
m6 <- read.zoo("./Data/UK/Yield/6m.csv", header = TRUE, sep = ",", index.column = 1, format = "%m/%d/%Y")
m6 <- xts(m6, order.by = time(m6))
uk_yield_curve$'6'[is.na(uk_yield_curve$'6')] = m6[time(uk_yield_curve)[is.na(uk_yield_curve$`6`)]]
remove(m6) | /Utils/missing_uk_6m.R | no_license | Stanimir-Ivanov/Diebold-et-al-2008-Replication | R | false | false | 253 | r | m6 <- read.zoo("./Data/UK/Yield/6m.csv", header = TRUE, sep = ",", index.column = 1, format = "%m/%d/%Y")
m6 <- xts(m6, order.by = time(m6))
uk_yield_curve$'6'[is.na(uk_yield_curve$'6')] = m6[time(uk_yield_curve)[is.na(uk_yield_curve$`6`)]]
remove(m6) |
# Calculate key temperature parameters for each 100m cell
# Process by year and block
# Output by block x risk: xyz file of seasonal values with z as year
# Carson job variables
args <-commandArgs(trailingOnly = TRUE)
print(args)
start.day <- as.integer(args[1])
start.month<-as.integer(args[2])
start.year<-as.integer... | /R/Analysis/t100_year_stats.R | no_license | jrmosedale/microclimates | R | false | false | 9,198 | r | # Calculate key temperature parameters for each 100m cell
# Process by year and block
# Output by block x risk: xyz file of seasonal values with z as year
# Carson job variables
args <-commandArgs(trailingOnly = TRUE)
print(args)
start.day <- as.integer(args[1])
start.month<-as.integer(args[2])
start.year<-as.integer... |
library(data.table)
setwd("d:/SVN/ExData_Plotting1/")
#readData
data <- readRDS("FilteredData.rds")
#Set locale to get proper week days
Sys.setlocale("LC_TIME", "English")
#create PNG file
png("plot2.png", width = 480, height = 480)
plot(data$DateTime, data$Global_active_power,type = "l", xlab = "", ylab = "Global A... | /Plot2.r | no_license | SergeyAshikhmin/ExData_Plotting1 | R | false | false | 356 | r | library(data.table)
setwd("d:/SVN/ExData_Plotting1/")
#readData
data <- readRDS("FilteredData.rds")
#Set locale to get proper week days
Sys.setlocale("LC_TIME", "English")
#create PNG file
png("plot2.png", width = 480, height = 480)
plot(data$DateTime, data$Global_active_power,type = "l", xlab = "", ylab = "Global A... |
## Species.spec organizes data. After using getspec, use species.spec to divide your specs up by species and place everything as tab-delimited text documents in one folder. Necessary precursor for the dimorphism measurement scripts.
species.spec <- function(specs) {
## Create folder for the spec files
dir.create... | /R/species.spec.r | no_license | craneon/pavo | R | false | false | 718 | r | ## Species.spec organizes data. After using getspec, use species.spec to divide your specs up by species and place everything as tab-delimited text documents in one folder. Necessary precursor for the dimorphism measurement scripts.
species.spec <- function(specs) {
## Create folder for the spec files
dir.create... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hello.R
\name{hello}
\alias{hello}
\title{Hello}
\usage{
hello()
}
\description{
Hello
}
| /hello/man/hello.Rd | no_license | grahamrp/ci_test | R | false | true | 167 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hello.R
\name{hello}
\alias{hello}
\title{Hello}
\usage{
hello()
}
\description{
Hello
}
|
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geographicmaphelper.R
\name{GeographicRegionTypes}
\alias{GeographicRegionTypes}
\title{\code{GeographicRegionTypes} Types of Geographic Regions}
\usage{
GeographicRegionTypes()
}
\description{
The geographic region types that are available f... | /man/GeographicRegionTypes.Rd | no_license | Displayr/flipStandardCharts | R | false | true | 419 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/geographicmaphelper.R
\name{GeographicRegionTypes}
\alias{GeographicRegionTypes}
\title{\code{GeographicRegionTypes} Types of Geographic Regions}
\usage{
GeographicRegionTypes()
}
\description{
The geographic region types that are available f... |
## Functions makeCacheMatrix and cacheSolve work together to
## enable the cacheing of inverse matrices, in order to
## efficiently store these data objects for future reuse,
## minimizing use of processing resources.
## makeCacheMatrix a form of the matrix x, that can be cached
## Function setInv() saves the invers... | /cachematrix.R | no_license | johndgalleyne/ProgrammingAssignment2 | R | false | false | 1,415 | r | ## Functions makeCacheMatrix and cacheSolve work together to
## enable the cacheing of inverse matrices, in order to
## efficiently store these data objects for future reuse,
## minimizing use of processing resources.
## makeCacheMatrix a form of the matrix x, that can be cached
## Function setInv() saves the invers... |
#Author: Jian Shi, Univ. of Michigan.
setwd("/Data/Coursera/proj")
df=read.table("household_power_consumption.txt", sep=";",header=TRUE,stringsAsFactors=FALSE)
#Only use the data of this time per the assignment
data <- df[df$Date %in% c("1/2/2007","2/2/2007") ,]
dim(data)
png("plot1.png",width=480,height=480)
hist(as.... | /plot1.R | no_license | Jskywalkergh/ExData_Plotting1 | R | false | false | 461 | r | #Author: Jian Shi, Univ. of Michigan.
setwd("/Data/Coursera/proj")
df=read.table("household_power_consumption.txt", sep=";",header=TRUE,stringsAsFactors=FALSE)
#Only use the data of this time per the assignment
data <- df[df$Date %in% c("1/2/2007","2/2/2007") ,]
dim(data)
png("plot1.png",width=480,height=480)
hist(as.... |
.onLoad= function(libname, pkgname){
options( "ggiwid" = list( svgid = 0 ) )
invisible()
}
setGrobName <- function (prefix, grob)
{
grob$name <- grobName(grob, prefix)
grob
}
| /R/utils.R | no_license | trinker/ggiraph | R | false | false | 185 | r | .onLoad= function(libname, pkgname){
options( "ggiwid" = list( svgid = 0 ) )
invisible()
}
setGrobName <- function (prefix, grob)
{
grob$name <- grobName(grob, prefix)
grob
}
|
rm(list = ls())
# Check for the requried packages and install them
if(!require("rpart"))
{
install.packages("rpart")
library("rpart")
}
if (!require("randomForest")) {
install.packages("randomForest")
library("randomForest")
}
if(!require("kknn"))
{
install.packages("kknn")
library("kknn")
}
... | /HW5/MLHW5/Dataset3.R | no_license | nagabharan/CS6375_ML | R | false | false | 5,022 | r | rm(list = ls())
# Check for the requried packages and install them
if(!require("rpart"))
{
install.packages("rpart")
library("rpart")
}
if (!require("randomForest")) {
install.packages("randomForest")
library("randomForest")
}
if(!require("kknn"))
{
install.packages("kknn")
library("kknn")
}
... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/data_desc.R
\docType{data}
\name{all.genes.lengths}
\alias{all.genes.lengths}
\title{Coding genes length by Ensamble, length is calculated as sum of all coding exons (merged before so each position only once ocunted).}
\format{data fr... | /man/all.genes.lengths.Rd | no_license | luisgls/cDriver | R | false | false | 987 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/data_desc.R
\docType{data}
\name{all.genes.lengths}
\alias{all.genes.lengths}
\title{Coding genes length by Ensamble, length is calculated as sum of all coding exons (merged before so each position only once ocunted).}
\format{data fr... |
source("initialize.R")
###############################################################################
###############################################################################
############################ SOLO QUEUE #######################################
########################################################... | /R-Project/viz.R | no_license | ShabdizGUni/MasterThesis | R | false | false | 49,138 | r | source("initialize.R")
###############################################################################
###############################################################################
############################ SOLO QUEUE #######################################
########################################################... |
library(ibelief)
### Name: decisionDST
### Title: Decision Rules
### Aliases: decisionDST
### ** Examples
m1=c(0,0.4, 0.1, 0.2, 0.2, 0, 0, 0.1);
m2=c(0,0.2, 0.3, 0.1, 0.1, 0, 0.2, 0.1);
m3=c(0.1,0.2, 0, 0.1, 0.1, 0.1, 0, 0.3);
m3d=discounting(m3,0.95);
M_comb_Smets=DST(cbind(m1,m2,m3d),1);
M_comb_PCR6=DST(cbind(m... | /data/genthat_extracted_code/ibelief/examples/decisionDST.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 520 | r | library(ibelief)
### Name: decisionDST
### Title: Decision Rules
### Aliases: decisionDST
### ** Examples
m1=c(0,0.4, 0.1, 0.2, 0.2, 0, 0, 0.1);
m2=c(0,0.2, 0.3, 0.1, 0.1, 0, 0.2, 0.1);
m3=c(0.1,0.2, 0, 0.1, 0.1, 0.1, 0, 0.3);
m3d=discounting(m3,0.95);
M_comb_Smets=DST(cbind(m1,m2,m3d),1);
M_comb_PCR6=DST(cbind(m... |
## Add tidyverse
library(tidyverse)
# Create the subset of lines and TOS that are to have extra data taken
sel_subset <- "Axe, Beaufort, Beckom, Cutlass, Gregory, Kittyhawk, Lancer, Mace, Manning, Scepter,
Trojan, Suntop, Commander, Compass, Fathom, Planet, Spartacus, Urambie, EGA_Gregory, RGT Planet, Spartacus CL"
se... | /NPI_sandbox.R | no_license | EPLeyne/NPI | R | false | false | 2,359 | r | ## Add tidyverse
library(tidyverse)
# Create the subset of lines and TOS that are to have extra data taken
sel_subset <- "Axe, Beaufort, Beckom, Cutlass, Gregory, Kittyhawk, Lancer, Mace, Manning, Scepter,
Trojan, Suntop, Commander, Compass, Fathom, Planet, Spartacus, Urambie, EGA_Gregory, RGT Planet, Spartacus CL"
se... |
## Reading the data
NEI <- readRDS("summarySCC_PM25.rds") # National Emissions Inventory (NEI)
SCC <- readRDS("Source_Classification_Code.rds")
# How have emissions from motor vehicle sources
# changed from 1999-2008 in Baltimore City?
# Type: ON-ROAD, Fips = "24510" Baltimore Motor Vehicle PM[2.5]* Emissions
... | /4- Exploratory Data Analysis/Week 4/plot5.R | no_license | jrreda/JHU-Data-Science | R | false | false | 732 | r | ## Reading the data
NEI <- readRDS("summarySCC_PM25.rds") # National Emissions Inventory (NEI)
SCC <- readRDS("Source_Classification_Code.rds")
# How have emissions from motor vehicle sources
# changed from 1999-2008 in Baltimore City?
# Type: ON-ROAD, Fips = "24510" Baltimore Motor Vehicle PM[2.5]* Emissions
... |
% Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/filterFeatures.R
\name{filterFeatures}
\alias{filterFeatures}
\title{Filter features by thresholding filter values.}
\usage{
filterFeatures(task, method = "rf.importance", fval = NULL, perc = NULL,
abs = NULL, threshold = NULL, mand... | /man/filterFeatures.Rd | no_license | elephann/mlr | R | false | false | 1,739 | rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/filterFeatures.R
\name{filterFeatures}
\alias{filterFeatures}
\title{Filter features by thresholding filter values.}
\usage{
filterFeatures(task, method = "rf.importance", fval = NULL, perc = NULL,
abs = NULL, threshold = NULL, mand... |
#' Report function
#'
#' \code{report} is a general function that returns Markdown code of a statistical test in 6th edition APA style.
#'
#' @param results A tidy stats list.
#' @param identifier A character string identifying the model.
#' @param group A character string identifying the group.
#' @param term A charac... | /R/report.R | permissive | ikbentimkramer/tidystats-v0.3 | R | false | false | 5,762 | r | #' Report function
#'
#' \code{report} is a general function that returns Markdown code of a statistical test in 6th edition APA style.
#'
#' @param results A tidy stats list.
#' @param identifier A character string identifying the model.
#' @param group A character string identifying the group.
#' @param term A charac... |
library(ggthemes)
team_theme <- function() {list(
theme(axis.line = element_line(color = "black"),
text = element_text(size = 8, family = "Times"),
panel.background = element_rect(fill = 'white', colour = 'black'),
panel.grid.minor = element_blank(),
panel.grid.major = element_blank... | /R/graph_theme.R | permissive | UofTCoders/eeb430.2017.Python | R | false | false | 499 | r | library(ggthemes)
team_theme <- function() {list(
theme(axis.line = element_line(color = "black"),
text = element_text(size = 8, family = "Times"),
panel.background = element_rect(fill = 'white', colour = 'black'),
panel.grid.minor = element_blank(),
panel.grid.major = element_blank... |
defaultdir <- getwd()
if (!file.exists("data")){
dir.create("data")
}
setwd("data")
if (!file.exists("household_power_consumption.txt")){
fileUrl <-"https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(fileUrl,"temp.zip")
unzip("temp.zip", "household_power_consu... | /plot3.R | no_license | VJ911/ExData_Plotting1 | R | false | false | 1,318 | r | defaultdir <- getwd()
if (!file.exists("data")){
dir.create("data")
}
setwd("data")
if (!file.exists("household_power_consumption.txt")){
fileUrl <-"https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
download.file(fileUrl,"temp.zip")
unzip("temp.zip", "household_power_consu... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/s4_architecture.R
\name{plotSF}
\alias{plotSF}
\title{Method for plotting the Survival Function of a Curve object}
\usage{
plotSF(theObject, ...)
}
\arguments{
\item{theObject}{The name of the RCurve Object}
\item{...}{Pass-through arguments... | /man/plotSF.Rd | no_license | cran/gestate | R | false | true | 513 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/s4_architecture.R
\name{plotSF}
\alias{plotSF}
\title{Method for plotting the Survival Function of a Curve object}
\usage{
plotSF(theObject, ...)
}
\arguments{
\item{theObject}{The name of the RCurve Object}
\item{...}{Pass-through arguments... |
fig_width <- 15
fig_height <- 10
pdf("R/hs_fig.pdf", width = fig_width, height = fig_height)
source("R/hs_fig.R")
dev.off()
svg("R/hs_fig.svg", width = fig_width, height = fig_height)
source("R/hs_fig.R")
dev.off()
| /R/hs_fig-make-svg-pdf.R | permissive | fboehm/QTLfigs | R | false | false | 218 | r | fig_width <- 15
fig_height <- 10
pdf("R/hs_fig.pdf", width = fig_width, height = fig_height)
source("R/hs_fig.R")
dev.off()
svg("R/hs_fig.svg", width = fig_width, height = fig_height)
source("R/hs_fig.R")
dev.off()
|
# Coursera JHU Exploratory Data Analysis
# Course Assignment 1. Plot 3.
library(dplyr)
source("common.R") # Code for loading data is factored out to common.R
# Running
# Note: Set your working directory accordingly.
# Step 1. Source this file. ie. source("plot3.R")
# Step 2. Load the data via function LoadData(<pat... | /plot3.R | no_license | subwarp/ExData_Plotting1 | R | false | false | 990 | r | # Coursera JHU Exploratory Data Analysis
# Course Assignment 1. Plot 3.
library(dplyr)
source("common.R") # Code for loading data is factored out to common.R
# Running
# Note: Set your working directory accordingly.
# Step 1. Source this file. ie. source("plot3.R")
# Step 2. Load the data via function LoadData(<pat... |
library(MCI)
### Name: huff.shares
### Title: Huff model market share/market area simulations
### Aliases: huff.shares
### ** Examples
data(Freiburg1)
data(Freiburg2)
# Loads the data
huff.shares (Freiburg1, "district", "store", "salesarea", "distance")
# Standard weighting (power function with gamma=1 and lambda=... | /data/genthat_extracted_code/MCI/examples/huff.shares.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 327 | r | library(MCI)
### Name: huff.shares
### Title: Huff model market share/market area simulations
### Aliases: huff.shares
### ** Examples
data(Freiburg1)
data(Freiburg2)
# Loads the data
huff.shares (Freiburg1, "district", "store", "salesarea", "distance")
# Standard weighting (power function with gamma=1 and lambda=... |
> library(datasets); attach(anscombe)
#cos'hanno in comune questi plot??
> par(mfrow=c(2,2)); plot(y1); plot(y2); plot(y3); plot(y4)
#calcolandone le medie...
> apply(cbind(y1,y2,y3,y4),2,mean)
#risultano essere pressoch\`{e} uguali (alla seconda cifra decimale)
> plot(sort(y1)); plot(sort(y2)); plot(sort(y3)); plot(s... | /snippets/anscombe.R | no_license | SunnyWangECNU/StatisticaDoc | R | false | false | 382 | r |
> library(datasets); attach(anscombe)
#cos'hanno in comune questi plot??
> par(mfrow=c(2,2)); plot(y1); plot(y2); plot(y3); plot(y4)
#calcolandone le medie...
> apply(cbind(y1,y2,y3,y4),2,mean)
#risultano essere pressoch\`{e} uguali (alla seconda cifra decimale)
> plot(sort(y1)); plot(sort(y2)); plot(sort(y3)); plot(s... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hello.R
\name{get_last_sunday}
\alias{get_last_sunday}
\title{Return the date for last Sunday}
\usage{
get_last_sunday(now = Sys.Date())
}
\arguments{
\item{now}{Today's date in ymd format. Defaults to the output of \code{Sys.Date()}.}
}
\val... | /scheduler/man/get_last_sunday.Rd | no_license | finchnSNPs/InspirationDisseminationSchedule | R | false | true | 473 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/hello.R
\name{get_last_sunday}
\alias{get_last_sunday}
\title{Return the date for last Sunday}
\usage{
get_last_sunday(now = Sys.Date())
}
\arguments{
\item{now}{Today's date in ymd format. Defaults to the output of \code{Sys.Date()}.}
}
\val... |
##Example for Programming Assignment 2: Lexical Scoping
cachemean <- function(x, ...) {
m <- x$getmean()
if(!is.null(m)) {
message("getting cached data")
return(m)
}
data <- x$get()
m <- mean(data, ...)
x$setmean(m)
m
} | /cachemean.R | no_license | kllontop/ProgrammingAssignment2 | R | false | false | 307 | r | ##Example for Programming Assignment 2: Lexical Scoping
cachemean <- function(x, ...) {
m <- x$getmean()
if(!is.null(m)) {
message("getting cached data")
return(m)
}
data <- x$get()
m <- mean(data, ...)
x$setmean(m)
m
} |
setwd("D://R//job Assign//install//data_for_question_uninstall//interview")
getwd()
# Library
library(lattice)
library(plyr)
library(dplyr)
library(ggplot2)#
library(readr)
library(lubridate)
library(data.table)
library(lattice)
library(ggplot2)
library(reshape)
library(scales)#
library(dat... | /Company C/Script.R | no_license | BhanuPratapSinghSikarwar/Assignments | R | false | false | 20,019 | r | setwd("D://R//job Assign//install//data_for_question_uninstall//interview")
getwd()
# Library
library(lattice)
library(plyr)
library(dplyr)
library(ggplot2)#
library(readr)
library(lubridate)
library(data.table)
library(lattice)
library(ggplot2)
library(reshape)
library(scales)#
library(dat... |
# create test cases for breast cancer project
#
#
#
# print Odds ratios
PRINTORS= FALSE
create.eth <- function() {
i <- round(runif(1,0,3))
eth = 'eur'
if (i==0) {
eth <- 'eur'
}
if (i==1) {
eth <- 'mao'
}
if (i==2) {
eth <- 'oth'
}
return(eth)
}
create.test <- function() {
eth ... | / bctest.R | no_license | OldMortality/bctestR | R | false | false | 7,727 | r | # create test cases for breast cancer project
#
#
#
# print Odds ratios
PRINTORS= FALSE
create.eth <- function() {
i <- round(runif(1,0,3))
eth = 'eur'
if (i==0) {
eth <- 'eur'
}
if (i==1) {
eth <- 'mao'
}
if (i==2) {
eth <- 'oth'
}
return(eth)
}
create.test <- function() {
eth ... |
# exercise 7.1.4
rm(list=ls())
source('setup.R')
# Load results from previous exercise.
source("Scripts/ex7_1_1.R")
alpha = 0.05
rt <- mcnemar(y_true[,1], yhat[,1], yhat[,2], alpha=alpha)
rt$CI # confidence interval of difference theta = thetaA-thetaB
rt$p # p-value of null hypothesis thetaA = thetaB
rt$thetahat #... | /DTU_ML_kursus/02450Toolbox_R/Scripts/ex7_1_4.R | no_license | AnnaLHansen/projects | R | false | false | 378 | r | # exercise 7.1.4
rm(list=ls())
source('setup.R')
# Load results from previous exercise.
source("Scripts/ex7_1_1.R")
alpha = 0.05
rt <- mcnemar(y_true[,1], yhat[,1], yhat[,2], alpha=alpha)
rt$CI # confidence interval of difference theta = thetaA-thetaB
rt$p # p-value of null hypothesis thetaA = thetaB
rt$thetahat #... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/droplevels.R
\name{droplevels.TidySet}
\alias{droplevels.TidySet}
\title{Drop unused elements and sets}
\usage{
\method{droplevels}{TidySet}(x, elements = TRUE, sets = TRUE, relations = TRUE, ...)
}
\arguments{
\item{x}{A TidySet object.}
\i... | /man/droplevels.TidySet.Rd | permissive | annakrystalli/BaseSet | R | false | true | 629 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/droplevels.R
\name{droplevels.TidySet}
\alias{droplevels.TidySet}
\title{Drop unused elements and sets}
\usage{
\method{droplevels}{TidySet}(x, elements = TRUE, sets = TRUE, relations = TRUE, ...)
}
\arguments{
\item{x}{A TidySet object.}
\i... |
#---------------------------------------------------------------------------------------------------------------------------------------
# RJMCMC
# functions
#---------------------------------------------------------------------------------------------------------------------------------------
# MH step
# this perfor... | /RJMCMCfunctions_logit.R | no_license | QuantEcol-ConsLab/Model-Averaging | R | false | false | 4,120 | r | #---------------------------------------------------------------------------------------------------------------------------------------
# RJMCMC
# functions
#---------------------------------------------------------------------------------------------------------------------------------------
# MH step
# this perfor... |
#
# 01 February 2017, updated on 11 December 2020
#
library(raster)
library(fBasics)
library(maptools)
#
data(wrld_simpl)
#
load("plot_data.RData")
load("plotToRemove.RData")
load("pca3.RData")
#
ls()
#
output[[1]]
#
# 858 cells from the PC1-PC2 space have been resampled with a cutoff value of
# 50 p... | /_resampling/03_extracting_selected_plots_from_the_sPlot_database.R | permissive | sPlotOpen/sPlotOpen_Code | R | false | false | 2,576 | r | #
# 01 February 2017, updated on 11 December 2020
#
library(raster)
library(fBasics)
library(maptools)
#
data(wrld_simpl)
#
load("plot_data.RData")
load("plotToRemove.RData")
load("pca3.RData")
#
ls()
#
output[[1]]
#
# 858 cells from the PC1-PC2 space have been resampled with a cutoff value of
# 50 p... |
#### Data preparation ####
#### Library ####
library(tidyverse)
library(reshape2)
library(plyr)
#### Load in data ###
data <- read.delim("Data/Data_Chickens.txt", sep = "")
colnames(data) <- c("Department", "Pen", "Group", "Animal_nr", "Time",
"Weight_change")
#### Set up ####
summary(data)
str(... | /Data_prep.R | no_license | ilsevb95/LMM_Case_Study | R | false | false | 930 | r | #### Data preparation ####
#### Library ####
library(tidyverse)
library(reshape2)
library(plyr)
#### Load in data ###
data <- read.delim("Data/Data_Chickens.txt", sep = "")
colnames(data) <- c("Department", "Pen", "Group", "Animal_nr", "Time",
"Weight_change")
#### Set up ####
summary(data)
str(... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PCT_SAFN.R
\docType{data}
\name{PCT_SAFN}
\alias{PCT_SAFN}
\title{Random forest model for percent sands and fines}
\format{A \code{\link[randomForest]{randomForest}} model}
\usage{
PCT_SAFN
}
\description{
Random forest model for percent sand... | /man/PCT_SAFN.Rd | no_license | SCCWRP/PHAB | R | false | true | 381 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PCT_SAFN.R
\docType{data}
\name{PCT_SAFN}
\alias{PCT_SAFN}
\title{Random forest model for percent sands and fines}
\format{A \code{\link[randomForest]{randomForest}} model}
\usage{
PCT_SAFN
}
\description{
Random forest model for percent sand... |
#install.packages("mapr")
library(mapr)#加载绘图包
map_leaflet(acaule) #绘图
spp <- c('Danaus plexippus', 'Accipiter striatus', 'Pinus contorta')#定义多个物种
dat<- occ(query = spp, from = 'gbif', has_coords = TRUE, limit = 50) #搜索多个物种
map_leaflet(dat, color =c ("#976AAE"," #6B944D","#BD5945")) #可视化 | /output/物种可视化.R | no_license | LHH2021/data-analysis | R | false | false | 336 | r | #install.packages("mapr")
library(mapr)#加载绘图包
map_leaflet(acaule) #绘图
spp <- c('Danaus plexippus', 'Accipiter striatus', 'Pinus contorta')#定义多个物种
dat<- occ(query = spp, from = 'gbif', has_coords = TRUE, limit = 50) #搜索多个物种
map_leaflet(dat, color =c ("#976AAE"," #6B944D","#BD5945")) #可视化 |
testlist <- list(a = 0L, b = 0L, x = c(-1125711872L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L))
result <- do.call(grattan:... | /grattan/inst/testfiles/anyOutside/libFuzzer_anyOutside/anyOutside_valgrind_files/1610386058-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 354 | r | testlist <- list(a = 0L, b = 0L, x = c(-1125711872L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L, 0L))
result <- do.call(grattan:... |
\name{simpleRhat}
\alias{simpleRhat}
\title{
The Brooks-Gelman-Rubin (BGR) convergence diagnostic
}
\description{
An 'interval' estimator of the 'potential scale reduction factor' (Rhat) for MCMC output. Similar to the function \code{\link{gelman.diag}} in \pkg{coda}, but much faster when thousands of parameter... | /man/simpleRhat.Rd | no_license | dsfernandez/wiqid | R | false | false | 1,912 | rd | \name{simpleRhat}
\alias{simpleRhat}
\title{
The Brooks-Gelman-Rubin (BGR) convergence diagnostic
}
\description{
An 'interval' estimator of the 'potential scale reduction factor' (Rhat) for MCMC output. Similar to the function \code{\link{gelman.diag}} in \pkg{coda}, but much faster when thousands of parameter... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CFunctions.R
\name{ForwardR}
\alias{ForwardR}
\title{Forward step}
\usage{
ForwardR(emisVec, initPr, trsVec)
}
\arguments{
\item{emisVec}{a vector of emission probabilities.}
\item{initPr}{a vector specifying initial state probabilities.}
\... | /man/ForwardR.Rd | no_license | julieaubert/CHMM | R | false | true | 428 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CFunctions.R
\name{ForwardR}
\alias{ForwardR}
\title{Forward step}
\usage{
ForwardR(emisVec, initPr, trsVec)
}
\arguments{
\item{emisVec}{a vector of emission probabilities.}
\item{initPr}{a vector specifying initial state probabilities.}
\... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/OLIVESWater.R
\docType{data}
\name{OLIVESWater}
\alias{OLIVESWater}
\title{Olives water requirement for land evaluation}
\format{
A data frame with 3 rows and 8 columns
}
\description{
A dataset containing the water characteristics of the cro... | /man/OLIVESWater.Rd | permissive | alstat/ALUES | R | false | true | 897 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/OLIVESWater.R
\docType{data}
\name{OLIVESWater}
\alias{OLIVESWater}
\title{Olives water requirement for land evaluation}
\format{
A data frame with 3 rows and 8 columns
}
\description{
A dataset containing the water characteristics of the cro... |
.l2norm <- function(vec){sqrt(sum(vec^2))}
.opnorm <- function(mat){.svd_truncated(mat, K = 1)$d[1]} | /R/norm.R | permissive | linnykos/utilities | R | false | false | 101 | r | .l2norm <- function(vec){sqrt(sum(vec^2))}
.opnorm <- function(mat){.svd_truncated(mat, K = 1)$d[1]} |
\name{plotTraj3d,ClusterLongData3d}
\alias{plotTraj3d}
%\alias{plotTraj3d,ClusterLongData3d-method}
%\alias{plotTraj3d,ClusterLongData3d,missing-method}
\alias{plotTraj3d,ClusterLongData3d,numeric-method}
%\alias{plotTraj3d,ClusterLongData3d,Partition-method}
\title{ ~ Function: plotTraj3d for ClusterLongData3d... | /man/plotTraj3d.Rd | no_license | dmurdoch/kml3d | R | false | false | 3,181 | rd | \name{plotTraj3d,ClusterLongData3d}
\alias{plotTraj3d}
%\alias{plotTraj3d,ClusterLongData3d-method}
%\alias{plotTraj3d,ClusterLongData3d,missing-method}
\alias{plotTraj3d,ClusterLongData3d,numeric-method}
%\alias{plotTraj3d,ClusterLongData3d,Partition-method}
\title{ ~ Function: plotTraj3d for ClusterLongData3d... |
library(testthat)
library(variantBedOverlap)
test_check('variantBedOverlap')
| /tests/testthat.R | permissive | letaylor/variantBedOverlap | R | false | false | 78 | r | library(testthat)
library(variantBedOverlap)
test_check('variantBedOverlap')
|
#' Select nodes in a graph
#' @description Select nodes from a graph object of
#' class \code{dgr_graph}.
#' @param graph a graph object of class
#' \code{dgr_graph} that is created using
#' \code{create_graph}.
#' @param node_attr an optional character vector of
#' node attribute values for filtering the node ID
#' va... | /R/select_nodes.R | no_license | Oscar-Deng/DiagrammeR | R | false | false | 6,453 | r | #' Select nodes in a graph
#' @description Select nodes from a graph object of
#' class \code{dgr_graph}.
#' @param graph a graph object of class
#' \code{dgr_graph} that is created using
#' \code{create_graph}.
#' @param node_attr an optional character vector of
#' node attribute values for filtering the node ID
#' va... |
library( ANTsR )
args <- commandArgs( trailingOnly = TRUE )
if( length( args ) != 2 )
{
helpMessage <- paste0( "Usage: Rscript averageImages.R inputFiles outputFile\n" )
stop( helpMessage )
} else {
inputFileName <- Sys.glob( args[1] )
modelFile <- args[2]
}
avg = antsAverageImages( inputFileName )
ants... | /src/averageImages.R | permissive | ANTsXNet/brainSR | R | false | false | 350 | r | library( ANTsR )
args <- commandArgs( trailingOnly = TRUE )
if( length( args ) != 2 )
{
helpMessage <- paste0( "Usage: Rscript averageImages.R inputFiles outputFile\n" )
stop( helpMessage )
} else {
inputFileName <- Sys.glob( args[1] )
modelFile <- args[2]
}
avg = antsAverageImages( inputFileName )
ants... |
complete <- function(directory, id = 1:332){
ids <- c()
nobs <- c()
for(i in id){
fileNcsv <- read.csv(paste0(getwd(), "/", directory,"/",
formatC(i, width=3, flag="0"), ".csv"))
ids <- c(ids, i)
completeNNA <- subset(fileNcsv, !is.na(nitrate) & !is.na(sul... | /complete.R | no_license | mauropaganin/datasciencecoursera | R | false | false | 425 | r | complete <- function(directory, id = 1:332){
ids <- c()
nobs <- c()
for(i in id){
fileNcsv <- read.csv(paste0(getwd(), "/", directory,"/",
formatC(i, width=3, flag="0"), ".csv"))
ids <- c(ids, i)
completeNNA <- subset(fileNcsv, !is.na(nitrate) & !is.na(sul... |
grridge <- function(highdimdata, response, partitions, unpenal = ~1,
offset=NULL, method="exactstable",
niter=10, monotone=NULL, optl=NULL, innfold=NULL,
fixedfoldsinn=TRUE, maxsel=c(25,100),selectionEN=FALSE,cvlmarg=1,
savepredobj="all",... | /R/grridge.R | no_license | magnusmunch/GRridge | R | false | false | 25,802 | r | grridge <- function(highdimdata, response, partitions, unpenal = ~1,
offset=NULL, method="exactstable",
niter=10, monotone=NULL, optl=NULL, innfold=NULL,
fixedfoldsinn=TRUE, maxsel=c(25,100),selectionEN=FALSE,cvlmarg=1,
savepredobj="all",... |
source("../requirements.R")
source("../base_functions.R")
folder <- "../rds/gaussian_hom/"
dir.create(folder, showWarnings = FALSE)
# if x is given, only generate response again
generate_hom_gaussian <- function(n,d,x=NULL)
{
if(is.null(x))
{
x=matrix(runif(n*d,-5,5),n,d)
}
# response
y=x[,1]+rnorm(nrow... | /simulations/comparisons_gaussian_hom_median_only.R | no_license | rizbicki/conformal-cde-experiments | R | false | false | 2,944 | r | source("../requirements.R")
source("../base_functions.R")
folder <- "../rds/gaussian_hom/"
dir.create(folder, showWarnings = FALSE)
# if x is given, only generate response again
generate_hom_gaussian <- function(n,d,x=NULL)
{
if(is.null(x))
{
x=matrix(runif(n*d,-5,5),n,d)
}
# response
y=x[,1]+rnorm(nrow... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GauPro_S3.R
\name{plot.GauPro}
\alias{plot.GauPro}
\title{Plot for class GauPro}
\usage{
\method{plot}{GauPro}(x, ...)
}
\arguments{
\item{x}{Object of class GauPro}
\item{...}{Additional parameters}
}
\value{
Nothing
}
\desc... | /GauPro/man/plot.GauPro.Rd | no_license | akhikolla/TestedPackages-NoIssues | R | false | true | 568 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GauPro_S3.R
\name{plot.GauPro}
\alias{plot.GauPro}
\title{Plot for class GauPro}
\usage{
\method{plot}{GauPro}(x, ...)
}
\arguments{
\item{x}{Object of class GauPro}
\item{...}{Additional parameters}
}
\value{
Nothing
}
\desc... |
# selecteer de rijen die female zijn
ais[ais$sex=='f',]
# selecteer de rijen die sporten row en netball bevatten
# daarna na de "," selecteert men de kolommen die u wilt tonen
ais[ais$sport=='Row' | ais$sport=='Netball',c("sex",'wt')] | /oefening3.6.R | no_license | embobrecht/dataanalyse | R | false | false | 236 | r |
# selecteer de rijen die female zijn
ais[ais$sex=='f',]
# selecteer de rijen die sporten row en netball bevatten
# daarna na de "," selecteert men de kolommen die u wilt tonen
ais[ais$sport=='Row' | ais$sport=='Netball',c("sex",'wt')] |
res <- simulate_farkle(10000, strategy_go_for_broke, parallel = TRUE)
res_max_dice <- simulate_farkle(10000, strategy_prefer_max_dice, parallel = TRUE)
res_three <- simulate_farkle(10000, strategy_prefer_threes, parallel = TRUE)
res_four <- simulate_farkle(10000, strategy_prefer_fours, parallel = TRUE)
list(
"Go ... | /ten-thousand-functions/notes/simulate.R | no_license | liston/slides | R | false | false | 685 | r | res <- simulate_farkle(10000, strategy_go_for_broke, parallel = TRUE)
res_max_dice <- simulate_farkle(10000, strategy_prefer_max_dice, parallel = TRUE)
res_three <- simulate_farkle(10000, strategy_prefer_threes, parallel = TRUE)
res_four <- simulate_farkle(10000, strategy_prefer_fours, parallel = TRUE)
list(
"Go ... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data-help.R
\docType{data}
\name{pertussisIgGPTParams2}
\alias{pertussisIgGPTParams2}
\title{Pertussis IgG-PT Response Parameters Data for Model 2}
\format{A dataframe \code{IgG} containing 3000 rows with 7 parameters for IgG antibody.}... | /man/pertussisIgGPTParams2.Rd | no_license | cran/seroincidence | R | false | true | 627 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data-help.R
\docType{data}
\name{pertussisIgGPTParams2}
\alias{pertussisIgGPTParams2}
\title{Pertussis IgG-PT Response Parameters Data for Model 2}
\format{A dataframe \code{IgG} containing 3000 rows with 7 parameters for IgG antibody.}... |
\name{Bayesian Occupancy Single Season}
\alias{BoccSS}
\alias{BoccSS0}
\title{
Bayesian single-season occupancy modelling
}
\description{
Functions to estimate occupancy from detection/non-detection data for a single season using a Gibbs sampler coded in R or JAGS.
\code{BoccSS0} runs a model in R without... | /man/BoccSS.Rd | no_license | cran/wiqid | R | false | false | 6,450 | rd | \name{Bayesian Occupancy Single Season}
\alias{BoccSS}
\alias{BoccSS0}
\title{
Bayesian single-season occupancy modelling
}
\description{
Functions to estimate occupancy from detection/non-detection data for a single season using a Gibbs sampler coded in R or JAGS.
\code{BoccSS0} runs a model in R without... |
set.seed( 61 )
library(mvtnorm)
library(fields)
library(Rcpp)
library(mclust)
library(kernlab)
library(ConsensusClusterPlus)
simu=function(s){
prob_glcm<-function(c,s=s,mc=30000){
mu<-c(2+c,14-c)
sigma<-matrix(s*c(1,-0.7,-0.7,1),nrow=2)
elip<-rmvnorm(mc,mu,sigma)
# par(xaxs='i',yaxs='i')
... | /s=10/simu_61.R | no_license | mguindanigroup/Radiomics-Hierarchical-Rounded-Gaussian-Spatial-Dirichlet-Process | R | false | false | 9,293 | r | set.seed( 61 )
library(mvtnorm)
library(fields)
library(Rcpp)
library(mclust)
library(kernlab)
library(ConsensusClusterPlus)
simu=function(s){
prob_glcm<-function(c,s=s,mc=30000){
mu<-c(2+c,14-c)
sigma<-matrix(s*c(1,-0.7,-0.7,1),nrow=2)
elip<-rmvnorm(mc,mu,sigma)
# par(xaxs='i',yaxs='i')
... |
# Scrape data from KenPom
#http://kenpom.com/
library('data.table')
library('pbapply')
library('XML')
library('RCurl')
library('stringdist')
library('stringi')
library(xml2)
library(httr)
library(dplyr)
library(rvest)
rm(list=ls(all=TRUE))
gc(reset=TRUE)
set.seed(8865)
#Load Spellings
spell <- fread('data/MTeamSpelli... | /1_KenPom_Scrape.R | no_license | Conor-McGrath/March_Madness | R | false | false | 2,405 | r | # Scrape data from KenPom
#http://kenpom.com/
library('data.table')
library('pbapply')
library('XML')
library('RCurl')
library('stringdist')
library('stringi')
library(xml2)
library(httr)
library(dplyr)
library(rvest)
rm(list=ls(all=TRUE))
gc(reset=TRUE)
set.seed(8865)
#Load Spellings
spell <- fread('data/MTeamSpelli... |
#' Classical estimates for tables
#'
#' Some standard/classical (non-compositional) statistics
#'
#' @param x a data.frame, matrix or table
#' @param margins margins
#' @param statistics statistics of interest
#' @param maggr a function for calculating the mean margins of a table, default is the arithmetic mean
#' @... | /R/stats.R | no_license | matthias-da/robCompositions | R | false | false | 2,986 | r | #' Classical estimates for tables
#'
#' Some standard/classical (non-compositional) statistics
#'
#' @param x a data.frame, matrix or table
#' @param margins margins
#' @param statistics statistics of interest
#' @param maggr a function for calculating the mean margins of a table, default is the arithmetic mean
#' @... |
#' Retrieve the lowest common taxon and rank for a given taxon name or ID
#'
#' @export
#' @param x Vector of taxa names (character) or id (character or numeric) to query.
#' @param db character; database to query. either \code{ncbi}, \code{itis}, or
#' \code{gbif}.
#' @param rows (numeric) Any number from 1 to inif... | /taxize/R/lowest_common.R | no_license | ingted/R-Examples | R | false | false | 6,904 | r | #' Retrieve the lowest common taxon and rank for a given taxon name or ID
#'
#' @export
#' @param x Vector of taxa names (character) or id (character or numeric) to query.
#' @param db character; database to query. either \code{ncbi}, \code{itis}, or
#' \code{gbif}.
#' @param rows (numeric) Any number from 1 to inif... |
##' Update data_key by processing the tracking document and renaming/adding
##' files to data_key.
##'
##' @param path Path to AFS root directory (getOption('afs.path))
##' @param tracker tracking file (getOption('afs.tracker'))
##' @param data Data key (getOption('afs.key')
##' @param save_key Save the returned key ... | /R/update_key.R | no_license | nverno/sync.afs | R | false | false | 2,121 | r | ##' Update data_key by processing the tracking document and renaming/adding
##' files to data_key.
##'
##' @param path Path to AFS root directory (getOption('afs.path))
##' @param tracker tracking file (getOption('afs.tracker'))
##' @param data Data key (getOption('afs.key')
##' @param save_key Save the returned key ... |
testlist <- list(b = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), p1 = c(8.5728629954997e-312, -2.59103114190503e-82, 8.96970809549085e-158, -1.3258495253834e-113, 2.79620616433656e-119, -6.80033518839696e+41, 2.68298522855314e-211, 1444042902784.06,... | /metacoder/inst/testfiles/intersect_line_rectangle/AFL_intersect_line_rectangle/intersect_line_rectangle_valgrind_files/1615769982-test.R | permissive | akhikolla/updatedatatype-list3 | R | false | false | 728 | r | testlist <- list(b = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), p1 = c(8.5728629954997e-312, -2.59103114190503e-82, 8.96970809549085e-158, -1.3258495253834e-113, 2.79620616433656e-119, -6.80033518839696e+41, 2.68298522855314e-211, 1444042902784.06,... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/simulate.R
\name{simulate}
\alias{simulate}
\title{Simulate Spread of Gene for Altruism}
\usage{
simulate(initial_pop = list(m0 = 90, m1 = 0, m2 = 10, f0 = 90, f1 = 0, f2 =
10), average_litter_size = 5, birth_rate_natural = 0.05,
death_ra... | /man/simulate.Rd | permissive | homerhanumat/simaltruist | R | false | true | 4,090 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/simulate.R
\name{simulate}
\alias{simulate}
\title{Simulate Spread of Gene for Altruism}
\usage{
simulate(initial_pop = list(m0 = 90, m1 = 0, m2 = 10, f0 = 90, f1 = 0, f2 =
10), average_litter_size = 5, birth_rate_natural = 0.05,
death_ra... |
#' An animated map for vector data
#' This project is just at its very beginning!
#'
#' @param viewpoint Text. Following the pattern "$projection=$x,$y,$z".
#' @param mode Currently only two values: "air" or "ocean".
#' @param fn filename.
#' @param width Width of the display area of the widget.
#' @param... | /R/Rearth.R | permissive | Rmonsoon/Rearth | R | false | false | 2,534 | r | #' An animated map for vector data
#' This project is just at its very beginning!
#'
#' @param viewpoint Text. Following the pattern "$projection=$x,$y,$z".
#' @param mode Currently only two values: "air" or "ocean".
#' @param fn filename.
#' @param width Width of the display area of the widget.
#' @param... |
## Create the third plot
# Load the dplyr package for later use
library(dplyr)
# Read the data from a file into a dataframe
dat <- read.table("household_power_consumption.txt", header = TRUE, sep = ";", na.strings = "?")
# Split out just the dates that we're looking at (Feb. 1st and 2nd, 2007)
# The dates in the f... | /plot4.R | no_license | DavidSilbermann/ExData_Plotting1 | R | false | false | 1,828 | r | ## Create the third plot
# Load the dplyr package for later use
library(dplyr)
# Read the data from a file into a dataframe
dat <- read.table("household_power_consumption.txt", header = TRUE, sep = ";", na.strings = "?")
# Split out just the dates that we're looking at (Feb. 1st and 2nd, 2007)
# The dates in the f... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dprime.R
\name{dprime}
\alias{dprime}
\title{Calculates Signal Detection Theory indices.}
\usage{
dprime(n_hit, n_miss, n_fa, n_cr)
}
\arguments{
\item{n_hit}{Number of hits.}
\item{n_miss}{Number of misses.}
\item{n_fa}{Number of false ala... | /man/dprime.Rd | no_license | bgautijonsson/neuropsychology.R | R | false | true | 2,182 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dprime.R
\name{dprime}
\alias{dprime}
\title{Calculates Signal Detection Theory indices.}
\usage{
dprime(n_hit, n_miss, n_fa, n_cr)
}
\arguments{
\item{n_hit}{Number of hits.}
\item{n_miss}{Number of misses.}
\item{n_fa}{Number of false ala... |
library(tree)
### Name: prune.tree
### Title: Cost-complexity Pruning of Tree Object
### Aliases: prune.tree prune.misclass
### Keywords: tree
### ** Examples
data(fgl, package="MASS")
fgl.tr <- tree(type ~ ., fgl)
plot(print(fgl.tr))
fgl.cv <- cv.tree(fgl.tr,, prune.tree)
for(i in 2:5) fgl.cv$dev <- fgl.cv$dev +
... | /data/genthat_extracted_code/tree/examples/prune.tree.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 399 | r | library(tree)
### Name: prune.tree
### Title: Cost-complexity Pruning of Tree Object
### Aliases: prune.tree prune.misclass
### Keywords: tree
### ** Examples
data(fgl, package="MASS")
fgl.tr <- tree(type ~ ., fgl)
plot(print(fgl.tr))
fgl.cv <- cv.tree(fgl.tr,, prune.tree)
for(i in 2:5) fgl.cv$dev <- fgl.cv$dev +
... |
################################################################################
## Allen Roberts
## April 23, 2020
## Stat 534
## Homework 4: Helper functions
################################################################################
require(MASS)
## Calculate the log determinant of a matrix
logdet <- function... | /hw4/helperFunc.R | no_license | dallenroberts/stat-534 | R | false | false | 5,839 | r | ################################################################################
## Allen Roberts
## April 23, 2020
## Stat 534
## Homework 4: Helper functions
################################################################################
require(MASS)
## Calculate the log determinant of a matrix
logdet <- function... |
rm(list=ls())
setwd("c:/data/clean")
#clear worksapce and set WD
fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
zipfile="UCI_HAR_data.zip"
download.file(fileURL, destfile=zipfile)
unzip(zipfile, exdir="data")
#download and unzip data
time<-Sys.time()
write.csv(t... | /run_analysis.R | no_license | bdhope/coursera_uci_data_cleaning | R | false | false | 2,409 | r | rm(list=ls())
setwd("c:/data/clean")
#clear worksapce and set WD
fileURL <- "https://d396qusza40orc.cloudfront.net/getdata%2Fprojectfiles%2FUCI%20HAR%20Dataset.zip"
zipfile="UCI_HAR_data.zip"
download.file(fileURL, destfile=zipfile)
unzip(zipfile, exdir="data")
#download and unzip data
time<-Sys.time()
write.csv(t... |
source('init.R')
pckgs <- loadPackages()
lvl2num <- function(x) as.numeric(levels(x)[x])
showdiag <- function(lm.obj){
par(mfrow = c(2, 2))
plot(lm.obj)
}
MAKE_PLOT <- FALSE
cols <- c('egr_diff', # public employement rate
'egr_lagged',
'TIME', # year
'gdpv_annpct', # gdp growth
... | /PublicEmploymentAnalysis/R/eda_annual.R | no_license | davidpham87/public_employment_analysis | R | false | false | 12,902 | r | source('init.R')
pckgs <- loadPackages()
lvl2num <- function(x) as.numeric(levels(x)[x])
showdiag <- function(lm.obj){
par(mfrow = c(2, 2))
plot(lm.obj)
}
MAKE_PLOT <- FALSE
cols <- c('egr_diff', # public employement rate
'egr_lagged',
'TIME', # year
'gdpv_annpct', # gdp growth
... |
\name{prLogisticBootMarg}
\alias{prLogisticBootMarg}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Estimation of Prevalence Ratios using Logistic Models and Bootstrap Confidence
Intervals for Marginal Standardization}
\description{
This function estimates prevalence ratios (PRs)
and boots... | /man/prLogisticBootMarg.Rd | no_license | Raydonal/prLogistic | R | false | false | 4,267 | rd | \name{prLogisticBootMarg}
\alias{prLogisticBootMarg}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{Estimation of Prevalence Ratios using Logistic Models and Bootstrap Confidence
Intervals for Marginal Standardization}
\description{
This function estimates prevalence ratios (PRs)
and boots... |
# Exercise 8: Pulitzer Prizes
# Read in the data
pulitzer <- read.csv("data/pulitzer-circulation-data.csv", stringsAsFactors = FALSE)
# Install and load the needed libraries
# Be sure to comment out the install.packages function so it won't install it every time it runs
# Remeber you only need to install a package on... | /exercise-8/exercise.R | permissive | kgoodman3/m11-dplyr | R | false | false | 1,614 | r | # Exercise 8: Pulitzer Prizes
# Read in the data
pulitzer <- read.csv("data/pulitzer-circulation-data.csv", stringsAsFactors = FALSE)
# Install and load the needed libraries
# Be sure to comment out the install.packages function so it won't install it every time it runs
# Remeber you only need to install a package on... |
summary.TwoStageSurvSurv <- function(object, ..., Object){
if (missing(Object)){Object <- object}
cat("\nFunction call:\n\n")
print(Object$Call)
cat("\n\n# Data summary and descriptives")
cat("\n#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
cat("\n\nTotal number... | /R/summary.TwoStageSurvSurv.R | no_license | cran/Surrogate | R | false | false | 980 | r |
summary.TwoStageSurvSurv <- function(object, ..., Object){
if (missing(Object)){Object <- object}
cat("\nFunction call:\n\n")
print(Object$Call)
cat("\n\n# Data summary and descriptives")
cat("\n#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~")
cat("\n\nTotal number... |
# Information Loss: IL3 ---------------------------------------------------
# Domingo-Ferrer e Torra (2001) p.8
IL3 <- function(dat, dat.agreg) {
n <- nrow(dat)
p <- ncol(dat)
IL <- vector('numeric', 5L)
IL[1] <-
abs(dat - dat.agreg) %>%
`/`(abs(dat)) %>%
sum() %>%
`/`(n * p)... | /IL3.R | permissive | augustofadel/sdc | R | false | false | 1,188 | r | # Information Loss: IL3 ---------------------------------------------------
# Domingo-Ferrer e Torra (2001) p.8
IL3 <- function(dat, dat.agreg) {
n <- nrow(dat)
p <- ncol(dat)
IL <- vector('numeric', 5L)
IL[1] <-
abs(dat - dat.agreg) %>%
`/`(abs(dat)) %>%
sum() %>%
`/`(n * p)... |
#' Central Limit Theorem Function
#'
#' @description Takes in n, iter, a, and b and returns a summation of the y's in iter as a matrix and also returns a histogram of the summations. Under the CLT, the distribution represented by the histogram should be normal as the number of samples of the population, being uniform w... | /R/myclt.R | no_license | w142236/math4753 | R | false | false | 1,178 | r | #' Central Limit Theorem Function
#'
#' @description Takes in n, iter, a, and b and returns a summation of the y's in iter as a matrix and also returns a histogram of the summations. Under the CLT, the distribution represented by the histogram should be normal as the number of samples of the population, being uniform w... |
##download the data, noting it is separated by ; and that the first
##row contains the variables, so header = TRUE
power <- read.table("household_power_consumption.txt", sep = ";", header = TRUE, stringsAsFactors = FALSE)
##stringasfactors makes what would have been factor variables characters
##convert Date variable... | /plot2.R | no_license | Fitzmar88/ExData_Plotting1 | R | false | false | 935 | r | ##download the data, noting it is separated by ; and that the first
##row contains the variables, so header = TRUE
power <- read.table("household_power_consumption.txt", sep = ";", header = TRUE, stringsAsFactors = FALSE)
##stringasfactors makes what would have been factor variables characters
##convert Date variable... |
library(shiny)
# input functions get values from user to pass to the backend
# e.g. selectInput(), sliderInput()
# Input function arguments:
# 1) all input functions have the same first argument:
# inputId
# must be unique!
# connects the front end (ui) to back end (server)
# 2) most have a second parameter w... | /wickham_shiny/chapter03/basic_ui/ui.R | no_license | ilellosmith/r_practice | R | false | false | 641 | r | library(shiny)
# input functions get values from user to pass to the backend
# e.g. selectInput(), sliderInput()
# Input function arguments:
# 1) all input functions have the same first argument:
# inputId
# must be unique!
# connects the front end (ui) to back end (server)
# 2) most have a second parameter w... |
hdpaDir <- '/Users/jonathan/Desktop/data'
hdpaFiles <- matrix(c(
hdpaDir, 'nan-random-t5000-model-b500-k0.9-20130529-0546', 'coherence-20130530-1952.txt', 'eval-20130530-2209.txt',
hdpaDir, 'nyt-random-t5000-model-b500-k0.9-20130529-0546', 'coherence-20130531-0455.txt', 'eval-20130531-0756.txt'
), 2, 4, byrow=T)
o... | /src/main/r/plot-emnlp.R | no_license | jesterhazy/hdpa | R | false | false | 3,965 | r | hdpaDir <- '/Users/jonathan/Desktop/data'
hdpaFiles <- matrix(c(
hdpaDir, 'nan-random-t5000-model-b500-k0.9-20130529-0546', 'coherence-20130530-1952.txt', 'eval-20130530-2209.txt',
hdpaDir, 'nyt-random-t5000-model-b500-k0.9-20130529-0546', 'coherence-20130531-0455.txt', 'eval-20130531-0756.txt'
), 2, 4, byrow=T)
o... |
# Convert JSON to a value
from_json <- function(json) {
fromJSON(json, simplifyDataFrame = FALSE)
}
# Convert a value to JSON
to_json <- function(value) {
# Override jsonlite which converts empty R lists to empty JSON arrays
if (is.list(value) && length(value) == 0) {
'{}'
} else {
toString(toJSON(
... | /R/json.R | permissive | RaoOfPhysics/r | R | false | false | 761 | r | # Convert JSON to a value
from_json <- function(json) {
fromJSON(json, simplifyDataFrame = FALSE)
}
# Convert a value to JSON
to_json <- function(value) {
# Override jsonlite which converts empty R lists to empty JSON arrays
if (is.list(value) && length(value) == 0) {
'{}'
} else {
toString(toJSON(
... |
\name{positioning.functions}
\Rdversion{1.1}
\alias{positioning.functions}
\alias{positioning.function}
\alias{Positioning.Function}
\alias{Positioning.Functions}
\title{Built-in Positioning Functions for direct label placement}
\description{When adding direct labels to a grouped plot, label
placement can be specifie... | /man/positioning.functions.Rd | no_license | cran/latticedl | R | false | false | 1,480 | rd | \name{positioning.functions}
\Rdversion{1.1}
\alias{positioning.functions}
\alias{positioning.function}
\alias{Positioning.Function}
\alias{Positioning.Functions}
\title{Built-in Positioning Functions for direct label placement}
\description{When adding direct labels to a grouped plot, label
placement can be specifie... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fn_exp_categorical_viz.R
\name{ExpCatViz}
\alias{ExpCatViz}
\title{Distributions of categorical variables}
\usage{
ExpCatViz(
data,
target = NULL,
fname = NULL,
clim = 10,
col = NULL,
margin = 1,
Page = NULL,
Flip = F,
sampl... | /man/ExpCatViz.Rd | no_license | daya6489/SmartEDA | R | false | true | 2,445 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fn_exp_categorical_viz.R
\name{ExpCatViz}
\alias{ExpCatViz}
\title{Distributions of categorical variables}
\usage{
ExpCatViz(
data,
target = NULL,
fname = NULL,
clim = 10,
col = NULL,
margin = 1,
Page = NULL,
Flip = F,
sampl... |
training<-read.csv("pml-training.csv",sep=",",header=TRUE,na.strings=c("NA",""),stringsAsFactors=FALSE,as.is=TRUE)
training$classe <- as.factor(training$classe)
training <- training[,-nearZeroVar(training)]
training <- training[,-c(1,2,3,4,5,6,7)]
inTrain <- createDataPartition(y=training$classe, p=0.75, list=FALSE)
tr... | /machine learning.R | no_license | ye298/Machine-learning | R | false | false | 758 | r | training<-read.csv("pml-training.csv",sep=",",header=TRUE,na.strings=c("NA",""),stringsAsFactors=FALSE,as.is=TRUE)
training$classe <- as.factor(training$classe)
training <- training[,-nearZeroVar(training)]
training <- training[,-c(1,2,3,4,5,6,7)]
inTrain <- createDataPartition(y=training$classe, p=0.75, list=FALSE)
tr... |
\name{plotAATT}
\alias{plotAATT}
\title{R function for plotting AA/TT/TA/AT frequency against to the distance from the nucleosome center}
\description{This function plots AA/TT/TA/AT frequency against to the distance from the nucleosome center.
}
\usage{plotAATT(seqname,genfile,center)}
\arguments{
\item{genfile}{on... | /man/plotAATT.Rd | no_license | HaoxiangLin/NuCMap | R | false | false | 1,631 | rd | \name{plotAATT}
\alias{plotAATT}
\title{R function for plotting AA/TT/TA/AT frequency against to the distance from the nucleosome center}
\description{This function plots AA/TT/TA/AT frequency against to the distance from the nucleosome center.
}
\usage{plotAATT(seqname,genfile,center)}
\arguments{
\item{genfile}{on... |
set.seed(14137)
n = 50
len = 1001
require(Rcpp)
require(BH)
require(nloptr)
require(ggplot2)
require(gridExtra)
options(digits=8)
source('../conv_plot.R')
sourceCpp('../Simulation.cpp')
par = c(0.05, 3.9, 0.08, 0.3038, -0.6974, 3.2, -0.3551, 0.0967*0.0967)
sourceCpp('../nll.cpp', verbose = F)
opts <- list(algorithm="... | /svj_stoc/Server_svj_stoc/session13/test.R | no_license | Steven-Sakurai/Heston-SVJ | R | false | false | 1,637 | r | set.seed(14137)
n = 50
len = 1001
require(Rcpp)
require(BH)
require(nloptr)
require(ggplot2)
require(gridExtra)
options(digits=8)
source('../conv_plot.R')
sourceCpp('../Simulation.cpp')
par = c(0.05, 3.9, 0.08, 0.3038, -0.6974, 3.2, -0.3551, 0.0967*0.0967)
sourceCpp('../nll.cpp', verbose = F)
opts <- list(algorithm="... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GA_utils.R
\name{.palette_to_chromosome}
\alias{.palette_to_chromosome}
\title{Get chromosome of palette}
\usage{
.palette_to_chromosome(hex_palette)
}
\arguments{
\item{hex_palette}{Hex strings for palette}
}
\value{
a vector of RGB values
}... | /man/dot-palette_to_chromosome.Rd | permissive | tsostarics/ftpals | R | false | true | 363 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/GA_utils.R
\name{.palette_to_chromosome}
\alias{.palette_to_chromosome}
\title{Get chromosome of palette}
\usage{
.palette_to_chromosome(hex_palette)
}
\arguments{
\item{hex_palette}{Hex strings for palette}
}
\value{
a vector of RGB values
}... |
% Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/pointsWithin.R
\name{range2GRanges}
\alias{range2GRanges}
\title{From data frame of ranges to GRanges object}
\usage{
range2GRanges(df)
}
\arguments{
\item{df}{Data frame with chr, start, and end columns}
}
\description{
From data fra... | /man/range2GRanges.Rd | no_license | JEFworks/badger | R | false | false | 491 | rd | % Generated by roxygen2 (4.1.0): do not edit by hand
% Please edit documentation in R/pointsWithin.R
\name{range2GRanges}
\alias{range2GRanges}
\title{From data frame of ranges to GRanges object}
\usage{
range2GRanges(df)
}
\arguments{
\item{df}{Data frame with chr, start, and end columns}
}
\description{
From data fra... |
testlist <- list(iK = 61951L)
result <- do.call(eDMA:::PowerSet,testlist)
str(result) | /eDMA/inst/testfiles/PowerSet/AFL_PowerSet/PowerSet_valgrind_files/1609870003-test.R | no_license | akhikolla/updated-only-Issues | R | false | false | 85 | r | testlist <- list(iK = 61951L)
result <- do.call(eDMA:::PowerSet,testlist)
str(result) |
#' Mapa del Banco de Porcupine sin referencias en tierra
#'
#' Función auxiliar para sacar el mapa de la campaña Porcupine
#' @param xlims Define los limites longitudinales del mapa, los valores por defecto son los del total del área de la campaña
#' @param ylims Define los limites latitudinales del mapa, los valores p... | /R/mapporco.r | no_license | Franvgls/CampR | R | false | false | 3,720 | r | #' Mapa del Banco de Porcupine sin referencias en tierra
#'
#' Función auxiliar para sacar el mapa de la campaña Porcupine
#' @param xlims Define los limites longitudinales del mapa, los valores por defecto son los del total del área de la campaña
#' @param ylims Define los limites latitudinales del mapa, los valores p... |
#' Load tsoobgx model from binary file
#'
#' Load tsoobgx model from the binary model file.
#'
#' @param modelfile the name of the binary input file.
#'
#' @details
#' The input file is expected to contain a model saved in an tsoobgx-internal binary format
#' using either \code{\link{bgx.save}} or \code{\link{cb.s... | /R/bgx.load.R | permissive | nalzok/tsoobgx | R | false | false | 2,136 | r | #' Load tsoobgx model from binary file
#'
#' Load tsoobgx model from the binary model file.
#'
#' @param modelfile the name of the binary input file.
#'
#' @details
#' The input file is expected to contain a model saved in an tsoobgx-internal binary format
#' using either \code{\link{bgx.save}} or \code{\link{cb.s... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/healthlake_operations.R
\name{healthlake_delete_fhir_datastore}
\alias{healthlake_delete_fhir_datastore}
\title{Deletes a data store}
\usage{
healthlake_delete_fhir_datastore(DatastoreId)
}
\arguments{
\item{DatastoreId}{[required] The AWS-ge... | /cran/paws.analytics/man/healthlake_delete_fhir_datastore.Rd | permissive | paws-r/paws | R | false | true | 526 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/healthlake_operations.R
\name{healthlake_delete_fhir_datastore}
\alias{healthlake_delete_fhir_datastore}
\title{Deletes a data store}
\usage{
healthlake_delete_fhir_datastore(DatastoreId)
}
\arguments{
\item{DatastoreId}{[required] The AWS-ge... |
library(IAPWS95)
### Name: TSats
### Title: Saturation Temperature, Function of Entropy
### Aliases: TSats
### ** Examples
s <- 2.10865845
T_Sat <- TSats(s)
T_Sat
| /data/genthat_extracted_code/IAPWS95/examples/TSats.Rd.R | no_license | surayaaramli/typeRrh | R | false | false | 171 | r | library(IAPWS95)
### Name: TSats
### Title: Saturation Temperature, Function of Entropy
### Aliases: TSats
### ** Examples
s <- 2.10865845
T_Sat <- TSats(s)
T_Sat
|
## Нормализация обучающей выборки
trainingSampleNormalization <- function(xl)
{
n <- dim(xl)[2] - 1
for(i in 1:n)
{
xl[, i] <- (xl[, i] - mean(xl[, i])) / sd(xl[, i])
}
return (xl)
}
## Добавление колонки для из -1 для w0
trainingSamplePrepare <- function(xl)
{
l <- dim(xl)[1]
... | /Lines_algoritms/all.r | no_license | Abkelyamova/SMPR_AbkelyamovaGulzara | R | false | false | 3,036 | r | ## Нормализация обучающей выборки
trainingSampleNormalization <- function(xl)
{
n <- dim(xl)[2] - 1
for(i in 1:n)
{
xl[, i] <- (xl[, i] - mean(xl[, i])) / sd(xl[, i])
}
return (xl)
}
## Добавление колонки для из -1 для w0
trainingSamplePrepare <- function(xl)
{
l <- dim(xl)[1]
... |
library(simsem)
library(semTools)
library(OpenMx)
######################### Fitting factorFit
data(demoOneFactor)
manifestVars <- names(demoOneFactor)
factorModel <- mxModel("One Factor",
mxMatrix(type="Full", nrow=5, ncol=1, values=0.7, free=TRUE, name="A"),
mxMatrix(type="Symm", nrow=1, ncol=1, values=1, ... | /SupportingDocs/Examples/Version05mx/exDemo/OneFactorMatrixDemo.R | no_license | simsem/simsem | R | false | false | 865 | r | library(simsem)
library(semTools)
library(OpenMx)
######################### Fitting factorFit
data(demoOneFactor)
manifestVars <- names(demoOneFactor)
factorModel <- mxModel("One Factor",
mxMatrix(type="Full", nrow=5, ncol=1, values=0.7, free=TRUE, name="A"),
mxMatrix(type="Symm", nrow=1, ncol=1, values=1, ... |
\name{PrepSegments}
\alias{PrepSegments}
\title{Preliminary segmentation analysis}
\usage{
PrepSegments(Data.traj, sd = 1, Km = 30, plotit = TRUE,
nmodels = 10, log = FALSE, mumin = 0, ...)
}
\arguments{
\item{Data.traj}{trajectory}
\item{sd}{standard deviation of step response}
\item{Km}{the ... | /waddle/waddle/man/PrepSegments.Rd | no_license | xiang-chen-git/ecomove | R | false | false | 1,144 | rd | \name{PrepSegments}
\alias{PrepSegments}
\title{Preliminary segmentation analysis}
\usage{
PrepSegments(Data.traj, sd = 1, Km = 30, plotit = TRUE,
nmodels = 10, log = FALSE, mumin = 0, ...)
}
\arguments{
\item{Data.traj}{trajectory}
\item{sd}{standard deviation of step response}
\item{Km}{the ... |
# Chapter 13
# Example 13.2 page no. 514 from the pdf..
# One way ANOVA..
# NULL : H0: mu1=mu2=mu3=mu4
# alternate : H1: at least two are not equal
a <- c(49.20,44.54,45.80,95.84,30.10,36.50,82.30,87.85,105.00,95.22,97.50,105.00,58.05,86.60,58.35,72.80,116.70,45.15,70.35,77.40,97.07,73.40,68.50,91.85,106.6... | /Probability_And_Statistics_For_Engineers_And_Scientists_by_Ronald_E._Walpole,_Raymond_H._Myers,_Sharon_L._Myers,_Keying_Ye/CH13/EX13.2/Ex13_2.R | permissive | FOSSEE/R_TBC_Uploads | R | false | false | 754 | r |
# Chapter 13
# Example 13.2 page no. 514 from the pdf..
# One way ANOVA..
# NULL : H0: mu1=mu2=mu3=mu4
# alternate : H1: at least two are not equal
a <- c(49.20,44.54,45.80,95.84,30.10,36.50,82.30,87.85,105.00,95.22,97.50,105.00,58.05,86.60,58.35,72.80,116.70,45.15,70.35,77.40,97.07,73.40,68.50,91.85,106.6... |
RADprocessingPop <- function(object){
alefq <- list()
realestimate <- list()
name1 <- list()
name2 <- list()
better_bias <- list()
if(is.null(object$alleleDepth) == 0){
object <- list(object)
}
for (m in 1:length(object)){
tryCatch({
real_iterate <- IteratePopStruct(object[[m]])
... | /RADprocessingPop function.R | no_license | jialehe3/polyRAD | R | false | false | 2,095 | r | RADprocessingPop <- function(object){
alefq <- list()
realestimate <- list()
name1 <- list()
name2 <- list()
better_bias <- list()
if(is.null(object$alleleDepth) == 0){
object <- list(object)
}
for (m in 1:length(object)){
tryCatch({
real_iterate <- IteratePopStruct(object[[m]])
... |
#profile analysis of FY18 pop-ups interested primarily in rate of ascent
#and factors influencing rate of ascent
#GOALS with this script: animation of data as pop-up ascends from seafloor to surface,
#compare TTP with SST, response time and precision and accuracy
require("ggplot2")
require("devtools")
require("lubri... | /Engineering/Iridium SBD/Data Costs/profile_analysis.R | permissive | NOAA-PMEL/EcoFOCI_PopUp | R | false | false | 1,470 | r | #profile analysis of FY18 pop-ups interested primarily in rate of ascent
#and factors influencing rate of ascent
#GOALS with this script: animation of data as pop-up ascends from seafloor to surface,
#compare TTP with SST, response time and precision and accuracy
require("ggplot2")
require("devtools")
require("lubri... |
.two_cond_ms <- function(result, IP_BAM, Input_BAM, contrast_IP_BAM, contrast_Input_BAM,
condition1, condition2) {
sample_name <- .get.sampleid(IP_BAM, Input_BAM, contrast_IP_BAM, contrast_Input_BAM)
if (length(sample_name) == 2) {
IP_groupname <- sample_name[[1]]
Input_groupname <... | /R/two_cond_ms.R | no_license | nkreim/Trumpet | R | false | false | 5,568 | r | .two_cond_ms <- function(result, IP_BAM, Input_BAM, contrast_IP_BAM, contrast_Input_BAM,
condition1, condition2) {
sample_name <- .get.sampleid(IP_BAM, Input_BAM, contrast_IP_BAM, contrast_Input_BAM)
if (length(sample_name) == 2) {
IP_groupname <- sample_name[[1]]
Input_groupname <... |
getwd()
data <- read.csv('test.csv',header = TRUE)
x <- seq(1,5)
# recall Graph include all attribute
full <- data[which(data$filename == "cleanedData_full_remove.txt"), "recall"]
collectionCode <- data[which(data$filename == "cleanedData_collectionCode_remove.txt"), "recall"]
habitat <- data[which(data$fil... | /Attribute_rank/recall.R | permissive | isamplesorg/vocabulary_learning | R | false | false | 5,861 | r | getwd()
data <- read.csv('test.csv',header = TRUE)
x <- seq(1,5)
# recall Graph include all attribute
full <- data[which(data$filename == "cleanedData_full_remove.txt"), "recall"]
collectionCode <- data[which(data$filename == "cleanedData_collectionCode_remove.txt"), "recall"]
habitat <- data[which(data$fil... |
\alias{gtkDragDestFindTarget}
\name{gtkDragDestFindTarget}
\title{gtkDragDestFindTarget}
\description{Looks for a match between \code{context->targets} and the
\code{dest.target.list}, returning the first matching target, otherwise
returning \code{GDK_NONE}. \code{dest.target.list} should usually be the return
value fr... | /man/gtkDragDestFindTarget.Rd | no_license | cran/RGtk2.10 | R | false | false | 1,129 | rd | \alias{gtkDragDestFindTarget}
\name{gtkDragDestFindTarget}
\title{gtkDragDestFindTarget}
\description{Looks for a match between \code{context->targets} and the
\code{dest.target.list}, returning the first matching target, otherwise
returning \code{GDK_NONE}. \code{dest.target.list} should usually be the return
value fr... |
timestamp <- Sys.time()
library(caret)
library(plyr)
library(recipes)
library(dplyr)
model <- "awnb"
#########################################################################
set.seed(2)
training <- LPH07_1(100, factors = TRUE, class = TRUE)
testing <- LPH07_1(100, factors = TRUE, class = TRUE)
trainX <- training... | /RegressionTests/Code/awnb.R | no_license | topepo/caret | R | false | false | 2,915 | r | timestamp <- Sys.time()
library(caret)
library(plyr)
library(recipes)
library(dplyr)
model <- "awnb"
#########################################################################
set.seed(2)
training <- LPH07_1(100, factors = TRUE, class = TRUE)
testing <- LPH07_1(100, factors = TRUE, class = TRUE)
trainX <- training... |
## Coursera Exploratory Data Analysis Project 1
setwd("~/a/highEd/dataScience_coursera/ExploreData/data")
# read the part of the file that includes the header record plus
# all the data for 2007-02-1 and 2007-02-01
hpc=read.table("household_power_consumption.txt", sep=";", header=TRUE,
nrows=69518)
hpc$Date<-as.... | /plot1.R | no_license | pwvirgo/ExData_Plotting1 | R | false | false | 1,129 | r | ## Coursera Exploratory Data Analysis Project 1
setwd("~/a/highEd/dataScience_coursera/ExploreData/data")
# read the part of the file that includes the header record plus
# all the data for 2007-02-1 and 2007-02-01
hpc=read.table("household_power_consumption.txt", sep=";", header=TRUE,
nrows=69518)
hpc$Date<-as.... |
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clusters.R
\name{dd_cluster_stations}
\alias{dd_cluster_stations}
\title{dd_cluster_stations}
\usage{
dd_cluster_stations(cl, city, stns, min_size = 3)
}
\arguments{
\item{cl}{Vector of cluster numbers obtained from \link{dd_cov_clusters}}
\... | /man/dd_cluster_stations.Rd | no_license | mpadge/distdecay | R | false | true | 877 | rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/clusters.R
\name{dd_cluster_stations}
\alias{dd_cluster_stations}
\title{dd_cluster_stations}
\usage{
dd_cluster_stations(cl, city, stns, min_size = 3)
}
\arguments{
\item{cl}{Vector of cluster numbers obtained from \link{dd_cov_clusters}}
\... |
# initialize app
# remotes::install_github("ewenme/ghibli")
library(tidyverse)
landings <- read.csv(here::here("05_ggplotly","data","nmfslandings.csv"))
crabs <- landings %>%
filter(Confidentiality == "Public") %>%
#filter(str_detect(NMFS.Name, "CRAB")) %>%
mutate_at(c("Pounds","Dollars"), parse_number)
| /05_ggplotly/00_initializeapp.R | no_license | alopp18/shinyoverview | R | false | false | 316 | r | # initialize app
# remotes::install_github("ewenme/ghibli")
library(tidyverse)
landings <- read.csv(here::here("05_ggplotly","data","nmfslandings.csv"))
crabs <- landings %>%
filter(Confidentiality == "Public") %>%
#filter(str_detect(NMFS.Name, "CRAB")) %>%
mutate_at(c("Pounds","Dollars"), parse_number)
|
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