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08e67c752b11d9ee549cdd844e31c57495ebfcac | 5d5d7785f5ce2ff377ebec29d74382652502c1d8 | /man/create_IV.Rd | 56aee463da052653db9d0908cc608863455daffe | [
"MIT"
] | permissive | standardgalactic/wpa | d7256e719732c7c3f067e88d253e600cd1d66a06 | b64b562cee59ea737df58a9cd2b3afaec5d9db64 | refs/heads/main | 2023-08-10T19:11:03.211088 | 2021-09-08T13:40:35 | 2021-09-08T13:40:35 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,771 | rd | create_IV.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/create_IV.R
\name{create_IV}
\alias{create_IV}
\title{Calculate Information Value for a selected outcome variable}
\usage{
create_IV(
data,
predictors = NULL,
outcome,
bins = 5,
siglevel = 0.05,
exc_sig = FALSE,
return = "plot"
... |
72c455ed39ceaa948df3f1403798949be2bb0a61 | d88feac4b653bbbae48765f667062fa28b6b93aa | /tests/testthat/setup-Strategy.R | b8d0931f3071b4ad56c938ab6bceeaa790abd044 | [
"MIT"
] | permissive | zumthor86/optPnL | 7358f7a674de78534b7e85fbb706af11011ba7e6 | 5540f3f0dead7879590abe269ea31b4c95233d52 | refs/heads/master | 2023-01-09T19:49:24.228151 | 2020-11-15T15:29:52 | 2020-11-15T15:29:52 | 258,577,387 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 82 | r | setup-Strategy.R | setup({data(strategies);
strats <<- lapply(strategies, optPnL:::create_strat)})
|
066c0ae5e9520842d94615c3a2d54e0694b4c883 | d092a1a552ad4265fe6c917bbf4c9e14aa8b2e78 | /R/GUI_juicr.R | c0f31ab65217883992708e7855dd895c74b62054 | [] | no_license | cran/juicr | fed72fc55186d707524f41a8722600b035afbc2e | c4f95aa95ce98bd8ea1f22007b42b5f938d70b06 | refs/heads/master | 2023-04-28T08:34:58.107134 | 2021-04-30T06:10:02 | 2021-04-30T06:10:02 | 363,187,685 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 172,833 | r | GUI_juicr.R | #' A GUI screener to quickly code candidate studies for inclusion/exclusion into
#' a systematic review or meta-analysis.
#'
#' A GUI screener to help scan and evaluate the title and abstract of studies to
#' be included in a systematic review or meta-analysis. A description of GUI
#' options and layout is found here: ... |
9a6946dbbed5af403d880d1b5dfdb21d0c0fa488 | 21c35042573da908206f7736bc54265846e0b35d | /Foo_Using ARIMA and Financial Ratios for Portfolio Optimization.R | a85133596f7c2fa369974f366048de456ba2a20a | [
"MIT"
] | permissive | biaohuan/StatisticalFinance | 837b2ead6794d518855d049a375f1b6c52a51306 | da95b4475967b9e020cd165c7f85fbee3cd47bcd | refs/heads/master | 2020-06-04T22:56:56.705081 | 2019-07-01T11:11:25 | 2019-07-01T11:11:25 | 192,223,386 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 21,170 | r | Foo_Using ARIMA and Financial Ratios for Portfolio Optimization.R | #---
#title: "ARIMA, Sharpe and Beta for Asset Selection and Optimization"
#author: "Biao Huan Foo"
#---
#library(GMCM)
#library(ggplot2)
#library(xts)
#library(forecast)
#library(PortfolioAnalytics)
#library(urca)
#Set Working Directory to full_history (Contains csv of all stocks)
#Step 1.1: Cleaning of... |
62a73725a2363761ee1a301cc3bd68da5d3bc21e | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/multilevel/examples/summary.rgr.agree.Rd.R | 862e4460b6408f834b4a6efc5278cedffcf98512 | [] | 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 | 247 | r | summary.rgr.agree.Rd.R | library(multilevel)
### Name: summary.rgr.agree
### Title: S3 method for class 'rgr.agree'
### Aliases: summary.rgr.agree
### Keywords: programming
### ** Examples
data(bh1996)
RGROUT<-rgr.agree(bh1996$HRS,bh1996$GRP,1000)
summary(RGROUT)
|
a932e44c9122b0ccb3c14042e76c4fe161c35228 | 4d4e54893fe008a3947801f72045932e1ecebaaf | /scripts/Lagarias/LagariasANOVAtmp.R | 831f28573f171f6d092f093cb479cd8a7ad39002 | [] | no_license | nicolise/SideProjects | 835dcf1c35e8b070e3fa8e98637ac3de21f8a08f | 30828173bf0aa3cf9a2e4580f3b250d2b253dc69 | refs/heads/master | 2021-01-21T04:53:51.267551 | 2019-03-30T01:23:53 | 2019-03-30T01:23:53 | 54,146,553 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,416 | r | LagariasANOVAtmp.R | #Nicole E Soltis
#03/17/16
#ANOVA for Lagarias RNAseq
#-------------------------------------------------------------------
#setwd("~/Projects/SideProjects/data/Lagarias")
setwd("~/Documents/GitRepos/SideProjects/data")
myData <- read.csv("for_pathwayANOVA.csv")
names(myData)
#is data normal?
attach(myData)
#graphical... |
f698b96120bb850f2ca8ce762ecb79063e4c887e | 2c13e79e11220d7c942e9c4d049839896d1af22e | /uncertaintyImportance.R | f783da9188933248328c77827020d15065662b7b | [] | no_license | DoktorMike/PlayGround | a2fa2b76093e14241cee8beb5785294149900940 | 3efaa96d201c37825f281de6d521638304f7ae14 | refs/heads/master | 2023-08-08T21:01:24.293399 | 2023-08-06T11:09:01 | 2023-08-06T11:09:01 | 10,732,191 | 0 | 0 | null | 2023-07-25T23:26:03 | 2013-06-17T07:28:48 | HTML | UTF-8 | R | false | false | 1,153 | r | uncertaintyImportance.R | library(ggplot2)
library(scales)
library(tibble)
x <- rgamma(5000, 0.5, 1); quantile(x); mean(x); qplot(x)
mydf <- tibble(TV=rnorm(5000, 0.5, 0.2), Radio=rgamma(5000, 0.5, 1)) %>% gather(Media, ROI)
group_by(mydf, Media) %>% summarise(Mean=mean(ROI), Min=min(ROI), Max=max(ROI),
Med... |
16d03c70f0d83e2a8afa727712418f7665261ac6 | cfc4a7b37657114bb93c7130eff4fc2458381a4f | /doc-ja/sample-geometry01.rb.v.rd | eaadbc36d0f9b42978558a3a0091ad4a4ae4f9cb | [
"MIT"
] | permissive | kunishi/algebra-ruby2 | 5bc3fae343505de879f7a8ae631f9397a5060f6b | ab8e3dce503bf59477b18bfc93d7cdf103507037 | refs/heads/master | 2021-11-11T16:54:52.502856 | 2021-11-04T02:18:45 | 2021-11-04T02:18:45 | 28,221,289 | 6 | 0 | null | 2016-05-05T16:11:38 | 2014-12-19T08:36:45 | Ruby | UTF-8 | R | false | false | 673 | rd | sample-geometry01.rb.v.rd | =begin
# sample-geometry01.rb
require 'algebra'
R = MPolynomial(Rational)
x,y,a1,a2,b1,b2,c1,c2 = R.vars('xya1a2b1b2c1c2')
V = Vector(R, 2)
X, A, B, C = V[x,y], V[a1,a2], V[b1,b2], V[c1,c2]
D = (B + C) /2
E = (C + A) /2
F = (A + B) /2
def line(p1, p2, p3)
SquareMatrix.det([[1, *p1], [1... |
5593b8120a2cc3ab703744689715836e0de00a21 | 9d7e58dbbc2556c5052f5367ad4636f901383b60 | /man/XRchart.Rd | 27511b07047165c4db5184d2b287c5723cfc2710 | [] | no_license | cran/SSDforR | eea003ef400f2274772958dd1a220b2f916feb93 | b0276a38634e9be787d4b5ddaabb3deec768b2fd | refs/heads/master | 2023-02-25T10:54:27.473408 | 2023-02-17T19:10:02 | 2023-02-17T19:10:02 | 17,693,615 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,543 | rd | XRchart.Rd | \name{XRchart}
\alias{XRchart}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{SPC XR-Chart
%% ~~function to do ... ~~
}
\description{This chart can be used when there are multiple observations per sample and uses the mean of each sample to create the chart.
%% ~~ A concise (1-5 lines) descripti... |
8a3bd333c9c0410b39aa34aeed0466c897f9c4ca | 13865ec82c8197b6e547eb12e0ef7aa00e23a137 | /man/cxx11Normal.Rd | ef289b148772624974ae493ab87c758d03b78b10 | [] | no_license | junjiemao/OneDayOneRcpp | c48001a667782237240929fa9b616cb3644874b5 | bb88c7f7c941e27bbfa95283df1327ff263efc43 | refs/heads/master | 2021-01-10T18:59:06.952674 | 2014-08-19T15:20:22 | 2014-08-19T15:20:22 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 259 | rd | cxx11Normal.Rd | % Generated by roxygen2 (4.0.1): do not edit by hand
\name{cxx11Normal}
\alias{cxx11Normal}
\alias{cxx11Normals}
\title{cxx11Normal}
\usage{
cxx11Normals(n, seed = 42L)
}
\arguments{
\item{n}{}
\item{seed}{default value is 42}
}
\description{
cxx11Normal
}
|
ae46ae1465e667649c1f24b31f1250f666b1334c | 5b7920289afd94750ca42e0626a4b1dc394fb6da | /R/Lp.R | c4c93ec15ff84c847fe480ef0b13d03a2431953f | [] | no_license | blasern/edd | 72ac3b4559bb3668b30ea9a5b2e4a2b0fd339d09 | 3c175502fcb29e48fd0ed5f42e0290f361419263 | refs/heads/master | 2021-03-22T03:00:35.917517 | 2019-03-14T22:11:41 | 2019-03-14T22:11:41 | 94,869,826 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 353 | r | Lp.R | #' Lp Distance
#'
#' Compute Lp distance
#'
#' @param X,Y input data
#' @param p the power p
#' @examples
#' X <- rexp(80, rate = 0.2)
#' Y <- rexp(120, rate = 0.4)
#' Lp_dist(X, Y, p = 2)
#' @importFrom rdist cdist
#' @export
Lp_dist <- function (X, Y, p = 2)
{
D <- rdist::cdist(X, Y, metric = "minkowski", p = p... |
71f7583d04f265dcd910ecff10fb70acad5465dc | bf9f77e17111b590fe44905ebd9391009a2a1390 | /man/lib_composante.Rd | 90682095ff0c72605251e208d254d7e633f416d7 | [
"MIT"
] | permissive | ove-ut3/apogee | 5cd9fed8e1cb4fc359b824fdb16ff269952d6320 | c08ff84497bbaab4af90a0eeb779a338ff158b87 | refs/heads/master | 2021-06-02T09:03:41.344113 | 2020-05-19T13:22:59 | 2020-05-19T13:22:59 | 115,185,672 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 582 | rd | lib_composante.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/libelle.R
\name{lib_composante}
\alias{lib_composante}
\title{Renvoie le libelle a partir du code composante}
\usage{
lib_composante(code_composante)
}
\arguments{
\item{code_composante}{Un vecteur de code composante.}
}
\value{
Un vecteur co... |
ec6d632b883c0016f87973f2851b28f15d517fb8 | 0a906cf8b1b7da2aea87de958e3662870df49727 | /diffrprojects/inst/testfiles/dist_mat_absolute/libFuzzer_dist_mat_absolute/dist_mat_absolute_valgrind_files/1609961572-test.R | 8ad51079e537e9b46e7dd55a72866adf57e7bafb | [] | 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 | 670 | r | 1609961572-test.R | testlist <- list(x = c(439374847L, -687920385L, -5723992L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465341784L, -1465... |
87f6dc1e35a96bbd210d692ccfc1f20c04a7ddce | 8b506669cb283da750d473888c11afe7747ab162 | /server.R | 1eabc181c974e0ac5c83c0f01333f28200ce96bb | [] | no_license | Yannael/covid19-forecast-belgium | dd7ca9832e6da0e3e8fdb584cfe6b62ca93aa353 | 309956e93442712f8cdb3c6886c228dde3476b55 | refs/heads/master | 2022-09-16T10:07:05.321457 | 2020-05-29T08:04:06 | 2020-05-29T08:04:06 | 265,491,129 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,510 | r | server.R | library(DT)
library(rpivotTable)
server <- function(input, output, session) {
#############################################################################
# Visualization: Filter data based on user input
data_f <- reactive({ all_data %>% filter(forecast_date == input$forecast_date) })
data_ft ... |
98f0dcf85f0825abbfbf1faed3c5f8181a021f94 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/circular/examples/aov.circular.Rd.R | adf4faeaa8e17896e76a9187baba9851f0016466 | [] | 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 | 351 | r | aov.circular.Rd.R | library(circular)
### Name: aov.circular
### Title: Analysis of Variance for circular data
### Aliases: aov.circular print.aov.circular
### Keywords: models
### ** Examples
x <- c(rvonmises(50, circular(0), 1), rvonmises(100, circular(pi/3), 10))
group <- c(rep(0, 50), rep(1, 100))
aov.circular(x, group)
aov.circu... |
65dda07a6fb44388f10a608aa9cb61feea8200c7 | 9de05fb9c3aa4309a08d85428127ceb8ea7a6193 | /tests/testthat/helper.R | d374939b98458a15a20a98f6bd830fdc39f18e21 | [] | no_license | bbolker/clusteredinterference | 4c54fda11b8d590bdfc5d5f9c285f4f33996041a | 2a56e8fd067d8835b8fa8f1226d826668c28b452 | refs/heads/master | 2023-03-20T04:42:49.847364 | 2019-07-17T23:39:10 | 2019-07-17T23:39:10 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 139 | r | helper.R |
# library(rprojroot)
quickLookup <- function(name) {
rprojroot::find_testthat_root_file("historical_data", name)
}
helper_tol <- 1e-7
|
bfe966148bb5e5aff011fe8adc37cb60ab09a3f0 | c55c02f27dc68f5a912a0cb7edf232ddc7197f7b | /exercises/exc_04_10_1.R | bcead4eaf2e4fd9fcdfd9d2fbd39e32b941ce1e7 | [
"MIT",
"CC-BY-4.0"
] | permissive | benmarwick/gams-in-r-course | 3e631518be8ab89c9e08d83743aa15053a8bc9d1 | ed45f12a183d1ba023ee43e8b2fa557773c9b5ef | refs/heads/master | 2020-05-27T19:02:16.685461 | 2019-05-27T02:01:13 | 2019-05-27T02:01:13 | 188,754,422 | 0 | 0 | null | 2019-05-27T02:00:18 | 2019-05-27T02:00:18 | null | UTF-8 | R | false | false | 229 | r | exc_04_10_1.R | # Calculate predictions and errors
predictions <- predict(log_mod2, newdata = new_credit_data,
type = "link", se.fit = TRUE)
# Calculate high and low prediction intervals
high_pred <- ___
low_pred <- ___
|
e58b4727954c9e34e46f8ecfce4a045aceb412d0 | ef8d66ebaeaf27fa1aed1cf01ebd70ce8224c5cd | /man/reorder_cormat.Rd | 362ababaed7634e53e1743ecd3a6646f988351a8 | [] | no_license | Alice-MacQueen/CDBNgenomics | dd6c8026156d91be7f12a9857d0ebeb89c32c384 | 6b00f48eb1c6eec848f11416d7a5fd752cd778bd | refs/heads/master | 2021-07-08T06:15:56.774003 | 2020-08-12T19:28:32 | 2020-08-12T19:28:32 | 178,261,021 | 2 | 2 | null | null | null | null | UTF-8 | R | false | true | 389 | rd | reorder_cormat.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/handle_mash_results.R
\name{reorder_cormat}
\alias{reorder_cormat}
\title{Reorder correlation matrix}
\usage{
reorder_cormat(cormat)
}
\arguments{
\item{cormat}{A correlation matrix}
}
\description{
Reorder correlation coefficients from a mat... |
5c88056908eb1d51c58430c7eede12640f7ae181 | 94312532e4e32f4d29f8e73eb90bce03d24ab66e | /R/fit3models.alt.R | 3a97cdff16fae0d29af73e0fc69aebf58df6b6c9 | [] | no_license | cran/paleoTSalt | 327f66292808ca313e71c28e70f9ad45b3a53647 | 6782f0756b8a12564b5dabaccd333fb1c3ac27da | refs/heads/master | 2021-01-19T08:29:23.656335 | 2007-10-22T00:00:00 | 2007-10-22T00:00:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 940 | r | fit3models.alt.R | `fit3models.alt` <-
function (y, pool = TRUE, silent = FALSE, wts = "AICc")
{
mn<- c("GRW", "URW", "Stasis")
m.grw <- opt.alt.GRW(y, pool = pool)
m.urw <- opt.alt.URW(y, pool = pool)
m.st <- opt.alt.Stasis(y, pool = pool)
aic <- c(m.grw$AIC, m.urw$AIC, m.st$AIC)
aicc <- c(m.grw$AICc, m.urw$AICc... |
7b2fda500f07feee1227a463ffcb3f6f3254ef6d | 33efeec39033156d7b598f8989f82fcf810db812 | /man/query_pa_dist_sub.Rd | 8c224b84cbe9cd23316c58f775e990d5861d65bd | [] | no_license | johnchower/oneD7 | 76b4712de0bb89fa70246880b69d7c9a1d90a7fa | 0ffcf86db58ddbe80330ac5185a7fc14c355545e | refs/heads/master | 2021-01-11T20:39:07.943924 | 2017-03-08T23:11:30 | 2017-03-08T23:11:30 | 79,161,189 | 0 | 0 | null | 2017-02-23T19:02:14 | 2017-01-16T21:28:54 | R | UTF-8 | R | false | true | 525 | rd | query_pa_dist_sub.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/data_doc.r
\docType{data}
\name{query_pa_dist_sub}
\alias{query_pa_dist_sub}
\title{A string containing the platform action distribution query with a placeholder for
subsetting on users and a relative time frame.}
\format{A length-one charact... |
6d24a810392b85164532c63c958bb49d1875648e | d05015051ae43528589a2a8dd61c72c45e333805 | /inst/shiny-app/server.R | 9025e63f3f2f55020d0c2b6f6ecb2af4a87db005 | [
"MIT"
] | permissive | wrightrc/r1001genomes | c2658de1f0be024c5fab2be8a7e97b14b776d284 | 2efddf207ff532ac390d49af7d70cd5266aeeb20 | refs/heads/master | 2021-06-03T09:20:03.086774 | 2019-10-31T03:28:37 | 2019-10-31T03:28:37 | 115,557,446 | 3 | 2 | null | null | null | null | UTF-8 | R | false | false | 30,518 | r | server.R |
# Server =================================================================
library(shiny)
library(biomaRt)
library(leaflet)
library(RColorBrewer)
library(r1001genomes)
library(knitr)
library(stringr)
library(DECIPHER)
library(ggseqlogo)
library(shinyBS)
library(ggplot2)
library(ggpmisc)
library(dplyr)
library(cowplot... |
9408b290436c14e8484ddcf9f89d8cb296c953c7 | f69138fa69d215b67d8f5ca61a260a19549bf6d4 | /kMeans_Temp_Work.r | fe3d166fe11977b4d291d1743b48c46afaea9cb1 | [
"MIT"
] | permissive | JamesRekow/Canine_Cohort_GLV_Model | 302a6de25897dfd6f038f88def159c8bc4480db3 | b7a3b167650471d0ae5356d1d2a036bde771778c | refs/heads/master | 2021-09-10T06:43:39.086540 | 2018-03-21T19:07:41 | 2018-03-21T19:07:41 | 105,334,062 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 877 | r | kMeans_Temp_Work.r | # James Rekow
# I just returned the fractured abdList in the beginning of the program
abdList = marginalDissDensity(M = 80, thresholdMult = 10 ^ (-3))
# convert abd list to a matrix, each row is an abundance vector, so the columns are the abundances of a
# given species
mat = Reduce(rbind, abdList)
h(10... |
d2a284fd8ea9a706ece795188e6276239bc6db5e | ca07d4e442efc63098e21fd16f6a6ade693bceb6 | /[AP] HDB Resale Flat Price Estimator App/Project-SA1-Team8/server.R | 4134abc06f9dd9cfa7544fe282552ead1ddbd043 | [] | no_license | davidyoucm/projects | ff50d3a03bdf9e651de01d737750884a38fc2304 | c0da6aa812e9873154e37a1298b7c4c228ac56a3 | refs/heads/master | 2023-03-09T18:44:49.297455 | 2021-02-24T17:45:17 | 2021-02-24T17:45:17 | 294,929,476 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 36,789 | r | server.R | library(shinydashboard)
library(leaflet)
library(shiny)
library(curl) # make the jsonlite suggested dependency explicit
library(geosphere)
library(ggmap)
register_google("insert token here")
library(scales)
library(tidyverse)
library(rvest)
library(RCurl)
library(curl)
library(jsonlite)
library(XML)
library(broom)
lib... |
c2ec12b41df7d0498756add81663bc21ee7d8286 | f6aee4d3a145140a277c8668c391f9cca8db3a95 | /Functions/Model/General/CalcAttnWeights.R | 7687561fe10867f1ddc2439e45be5ce6732c6fc7 | [] | no_license | peter-hitchcock/rum_derails_rl | b981336e08882959e9888009e23de8cd25354556 | 1c5ea8737acd2f1f83f4f259cf9218f65d1c5c61 | refs/heads/main | 2023-03-09T17:00:32.649539 | 2021-03-02T04:33:08 | 2021-03-02T04:33:08 | 343,197,552 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,469 | r | CalcAttnWeights.R | CalcAttnWeights <- function(pars,
weights_RL,
param_labels,
reward,
schosen_vector_indices,
color_RL_weights,
texture_RL_weights,
... |
b233272c3705a847792611c5a1b35c33fd5328cb | 77ff13c4c17a8f0c7469cd914eb856ebda6e52a2 | /R/generics.R | f7fce08ed298912a24417166947bf45939eed8ce | [] | no_license | carlonlv/DataCenterSim | f88623620c32816e97bd53b78ef6931f66ca8521 | fa2cc2592969c40d3e8494c2be46a94641b235f1 | refs/heads/master | 2022-01-19T12:04:49.255542 | 2022-01-07T19:40:39 | 2022-01-07T19:40:39 | 228,258,775 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,655 | r | generics.R | #' @include sim_class.R
NULL
#' Get The Slots that Are Considered Hyperparameters of Simulation
#'
#' @param object An S4 sim or pred object
#' @rdname get_param_slots
#' @export
setGeneric("get_param_slots", function(object) standardGeneric("get_param_slots"))
#' Get The Slots that Are Considered Charactersitics o... |
3cf9e00a57ae739750cae2aa5d17af2289f0fd71 | 1fbce482fa0cd8117e0a80e38323c5eb5f67ca7a | /R/makeData.R | 6479ac0a72c6333f57af481e7ebc120d74687617 | [] | no_license | bioinfo16/RIPAT | adf1ef88a37e033d3b4961272d8846370bb685c4 | 4e736b60e9bc2695a67ba13e9a50ed56c9c4d38a | refs/heads/master | 2021-02-06T21:47:10.233559 | 2020-10-13T06:09:25 | 2020-10-13T06:09:25 | 243,133,840 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,548 | r | makeData.R | #' @title Make data files for RIPAT.
#'
#' @description
#' Download datafiles for running RIPAT.
#'
#' @usage
#' makeData(organism = 'GRCh37', dataType = 'cpg')
#'
#' @param organism a single character. Two versions of organism such as GRCh37, GRCh38 (Human).\cr
#' Default is '... |
e62eea240bb1fd5ed4050dd5e01efbc2c27f163e | ed633d145dfa8b32511b3cb13ba95b822e2559c8 | /doc/Calculate.rwg.R | 22f08ffcfd084b2713269c368c89962da8740008 | [] | no_license | wendellopes/rvswf | 51a09f034e330fbb7fd58816c3de2b7f7fdba9dc | ee243c3e57c711c3259a76051a88cc670dfe9c4b | refs/heads/master | 2020-05-19T19:38:18.987560 | 2016-09-11T22:57:37 | 2016-09-11T22:57:37 | 19,242,694 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,580 | r | Calculate.rwg.R | #-------------------------------------------------------------------------------
# WAVE GUIDE PARAMETERS
#-------------------------------------------------------------------------------
rm(list=ls())
#-------------------------------------------------------------------------------
# Basic Parameters
#-------------------... |
8387f0f0fe6d3c1dcc132bf6c871ceeff275bb2d | 627d6dc6554e35fc1835f380157899ecfb8ee377 | /diffSupers.R | 8068a806d69a75a100d25e217db187fe2f98a4cb | [] | no_license | gauravj49/CLL_TFnetworks_2018 | 4ccd98230cc9cda4aba452403185d2215c94adc7 | adcace3c398573c74762534bb730e73beb4dbe38 | refs/heads/master | 2021-07-01T12:17:55.046831 | 2020-11-25T09:26:36 | 2020-11-25T09:26:36 | 197,175,310 | 1 | 1 | null | 2019-07-16T10:45:45 | 2019-07-16T10:45:45 | null | UTF-8 | R | false | false | 7,418 | r | diffSupers.R | ## ----setup, include=FALSE------------------------------------------------
knitr::opts_chunk$set(echo = TRUE,
cache = F,
warning = F,
message = F,
tidy = F)
## ----message=FALSE, warning=FALSE--------------------------------------... |
014df094fd31376ed48aa3d18394340d52965409 | 2ed676cabbe5cc9531a1d159a95a04c0bcc7cbb1 | /plot2.R | 5d8d7f7aff574fd3a47d9a047782d99306c7f061 | [] | no_license | imga2020/ExData_Plotting1 | add1beaa9c50c6caf2aadf175ecf127b47b1272f | c572b9a7e43b7432ae5664a8d73f1bc1c63248f5 | refs/heads/master | 2022-12-01T06:41:07.678739 | 2020-07-25T23:33:43 | 2020-07-25T23:33:43 | 282,058,148 | 0 | 0 | null | 2020-07-23T21:23:36 | 2020-07-23T21:23:35 | null | UTF-8 | R | false | false | 1,740 | r | plot2.R | #Coursera Exploratory Data Analysis
#Course Project 1
#Plot2
#Load the dataset into R
#Download from zip file
fileUrl1 <- "https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
filename <- "DataHouseholdpower.zip"
download.file(fileUrl1, filename, method = "curl")
unzip(filena... |
db640f7bdcf08f7e72122ec091db0ac2a8526b60 | dba2f6213ec4130b7f8344f8a06855a33f2f5be9 | /plot3.R | 5ae1fa9f080b8a7a92d3d0a4f142031dbef932bb | [] | no_license | yrahan/ExData_Plotting1 | 5720a809b96db0b2a891bd31af20a0b56454c6e5 | 6f0fec97960e8b5f2cc18659e29fb64b585267b3 | refs/heads/master | 2021-01-18T11:45:11.973609 | 2014-05-11T14:17:20 | 2014-05-11T14:17:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,297 | r | plot3.R | # read data
consumption <- read.table("household_power_consumption.txt", header=TRUE, sep=";",
na.string="?")
# convert column Date to Date format
consumption$Date <- as.Date(as.character(consumption$Date),format="%d/%m/%Y")
datesPerimeter <- c(as.Date("2007-02-01" , format="%Y-%m-%d"),
... |
5c836fb6cd4a02463206030931545ad287964473 | 3c2715e0dfade25fbedb65aaa21b99a677c2e1d2 | /LDA_logreg_functions.R | ea9f10b0f2f76bfe8e6110d90c5f6bd6c4d4bc2c | [] | no_license | AakashAhuja30/Topic-Modelling-using-Latent-Dirichlet-Allocation-Algorithm | 02be9586f013cfcf332e3249e1e5cbc532643e7c | f75cc4b7687287dc2cfbb7f536e091e1b549d26b | refs/heads/main | 2023-01-14T05:54:25.086423 | 2020-11-10T15:24:08 | 2020-11-10T15:24:08 | 311,695,379 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,880 | r | LDA_logreg_functions.R | #Main Function
Main_function<-function(files,K,top_words){
#Getting the vocab from the docs
temp2<-unlist(files)
docs<-strsplit(temp2, split=' ', perl = T)
t1 <- vector(mode = "list", length = length(docs))
fre_tab <- vector(mode = "list", length = length(docs))
fre_tab2 <- vector(mode = "list"... |
f02e4e4f76c8101ccfd39f16dd9e3cd7566a76d4 | 71821a5612e50fc8120afc8c5dc18019dadb9e84 | /1BM17CS024_DSR Lab/lab 6 04-11-20/dotchart.R | 62971527683174d5102aac98d5fd9d222b64f386 | [] | no_license | dikshajain228/Semester-7 | 825229cd63c4a047ac5dd5c3896a43b9835a791d | 996def1ada173ac60d9fd0e4c9da4f954d2de4f0 | refs/heads/master | 2023-02-04T22:19:25.984283 | 2020-12-20T07:48:06 | 2020-12-20T07:48:06 | 297,544,965 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 133 | r | dotchart.R | install.packages("ggplot2")
library("gcookbook")
mtcars
dotchart(mtcars$mpg, labels = row.names(mtcars),cex = 0.6, xlab = "mpg")
|
c14c44d4ae78f9052cb378fe364304e03c4208d2 | aa29ec4169d341764c714e2f161a09b6d58396ef | /Triangle BLDS/triangle BLDS.R | c4bee9e41f31ee46001dcbac20d9c3ea5570377b | [] | no_license | dnzengou/R_Projects | 3c6b63244041ab3536f48c2e43ef5438172d1a44 | 9e66033b694e53017af496b263ee74631d053f83 | refs/heads/master | 2020-04-02T00:12:49.428521 | 2016-03-15T04:29:03 | 2016-03-15T04:29:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 20,507 | r | triangle BLDS.R | library("RSocrata")
library("httr")
library("devtools")
library("jsonlite")
library("curl")
library("gtools")
install_github("Chicago/RSocrata")
#city of Raliegh old and deprecated
cdi4_url = "https://permits.partner.socrata.com/resource/pjib-v4rg.csv?$limit=50000"
raleigh <- read.csv(curl(cdi4_url))
raleigh$city <- ... |
0e609593020b1217f7674a88970c194c285dbfd0 | 2e95fc984d9893d7619d68f9dae638be0734cca5 | /R/filter_rules.R | 5adf94e5b4bd9521d39fe8f7ecc0ce9c1e426958 | [] | no_license | karsmo/VisuNet | cfc990ad85b20feecf036175e3f1eee5cd5646d8 | 938ddaddd2e9a39afba7bfb71b0ac4b5512bbb99 | refs/heads/master | 2020-05-24T00:43:45.535808 | 2019-12-03T11:51:39 | 2019-12-03T11:51:39 | 168,517,615 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 295 | r | filter_rules.R | filter_rules = function(rules, minAcc, minSupp){
if(max(rules$SUPP_RHS) < minSupp){
'Please change min Support value. Your value is too high!'
}else if(max(rules$ACC_RHS) < minAcc){
'Please change min Accucary value. Your value is too high!'
}else{
NULL
}
}
|
c42ff0dba26bfc84eb8fde5786165e10fba0ea76 | f801a9d6e316db85aad03630dfb660eba7416ad7 | /AnalysisCode/ThinkPiece/old/aboveSaylorville_analyses.R | 4cb765b24b31aafbacbe9811af0628e851bf176d | [] | no_license | jonathan-walter/AquaTerrSynch | 5458c9608faa737d66daf14a6e53d25c1d610d1a | 4388f9b78d7890ed6c9973b2e4281c5ad4d4139c | refs/heads/master | 2021-07-09T01:03:18.024976 | 2020-07-01T16:58:33 | 2020-07-01T16:58:33 | 148,833,977 | 2 | 0 | null | 2020-02-05T02:32:21 | 2018-09-14T19:38:23 | R | UTF-8 | R | false | false | 7,866 | r | aboveSaylorville_analyses.R | rm(list=ls())
library(lubridate)
library(wsyn)
##Data preparation
dat1<-read.csv("~/Box Sync/NSF EAGER Synchrony/Data/Iowa Lakes Data/DesMoinesRiver_Site1_AllData.csv", stringsAsFactors = F)
dat2<-read.csv("~/Box Sync/NSF EAGER Synchrony/Data/Iowa Lakes Data/ACE_Site1_TempFlow.csv", stringsAsFactors = F)
dat<-rbind... |
bf5a47b912236845774f540e820896f314fc1684 | d7c9e107ee8b85a72687b860669bbe20e5e1ab9b | /man/fn.Rd | 419a583f1a71761e319364d34eeca2f705690d2c | [] | no_license | iqis/lispr | 7b13b257125fa513d51bd02fd396463f4fa816ed | b2fda54a426826a74883561c1f286c8a74b1c765 | refs/heads/master | 2020-05-09T13:46:36.249581 | 2019-04-13T12:29:43 | 2019-04-13T12:29:43 | 181,167,152 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 248 | rd | fn.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/core.R
\name{fn}
\alias{fn}
\title{Construct a function}
\usage{
fn(arg, body)
}
\description{
construct a function with a list for arguments and a code block for body
}
|
748cf66b85932a785db02caf18090b0eb8ab525f | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/newsmap/examples/accuracy.Rd.R | c9f23903b2c0eedcc6431f6e9ebc63cd2bf85900 | [] | 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 | 355 | r | accuracy.Rd.R | library(newsmap)
### Name: accuracy
### Title: Evaluate classification accuracy in precision and recall
### Aliases: accuracy
### ** Examples
class_pred <- c('US', 'GB', 'US', 'CN', 'JP', 'FR', 'CN') # prediction
class_true <- c('US', 'FR', 'US', 'CN', 'KP', 'EG', 'US') # true class
acc <- accuracy(class_pred, clas... |
ec02e8fc4ec4d3a4eb2c65bb00a9f89e99e6ac27 | 03c11634037f8863b37a1981a6b7dce8a9a79f06 | /_tests/test-or.r | 31372f98d928643ab2be5b442601025f588fd1b1 | [] | no_license | klmr/parser-combinators | 8f0fa50d4cac48a05bf8bff68937dc93a0ce9ce6 | 515e850a5fe294dd117f35a917151d2221fdc434 | refs/heads/master | 2021-01-10T08:26:13.704232 | 2016-03-20T17:18:58 | 2016-03-20T17:18:58 | 54,326,700 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,243 | r | test-or.r | context('alternative parsers')
a = chr('a')
aa = lit('aa')
a2 = or(a, aa)
ab = or(a, chr('b'))
vowel = any_of('aeiou')
test_that('parsers can be alternated', {
expect_that(a2('a'), has_match(2L))
expect_that(a2('aa'), has_match(2L, 3L))
expect_that(or(empty, a, aa)('aa'), has_match(1L, 2L, 3L))
expect... |
5ffb80ba6191f0cb59d66383d9031b4ea7c9b0fb | d7f314a6661e5e56ec695594f25f4b52de1a18de | /Exam_1/Exam_1_complete.R | 303691e2bd77c1ff5accc676d8a866069fce320e | [] | no_license | twedwards/Data_Course_Edwards | 7aad18a84611b52d98c592b79f0f7eccbc26420d | a78fd68e1d49aec21034fc81ffca0c2489245d33 | refs/heads/master | 2021-07-17T19:20:27.838906 | 2020-08-22T00:08:36 | 2020-08-22T00:08:36 | 203,419,841 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,898 | r | Exam_1_complete.R | library(tidyverse)
##Once you get the file loaded into an R object as a data frame, feel free to do some exploratory visualizations or summaries to get a feel for the data if you like.
##Your first task, though, is to create separate histograms of the DNA concentrations for Katy and Ben. Make sure to add nice label... |
806e7be769dacb46df68363271273741d9ce09b4 | a6d778e2897498d87f12fa6a40f40c009e0aed7c | /marg_vdchildren.R | 3ae9ccd97f205c0cfb1ab460d88636be20a874a3 | [] | no_license | margarc/meta-analysis- | 73b3a6d5062cc95252da68c3bbb162c2dea7ae92 | 2f654c490b80a3813a31ad4f1d5ffaa70327b4c0 | refs/heads/master | 2021-01-13T16:35:18.272067 | 2018-09-28T09:52:50 | 2018-09-28T09:52:50 | 79,135,581 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,383 | r | marg_vdchildren.R | getwd()
setwd("C:/Users/INSPIRON/Documents/Rch")
preval
metaprop(vddch, totch, studlab=paste(study), data = preval)
mpreval <- metaprop(vddch, totch, studlab=paste(study), data = preval)
mpreval
forest(mpreval, comb.fixed=FALSE, xlab= "proportion")
forest(mpreval, comb.random=FALSE, xlab= "proportion")
funnel(m... |
d6a6a9bcb62a8ab2883ee323dde830119c3e5934 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/embryogrowth/examples/weightmaxentropy.Rd.R | 95396372c39cde2f476c15870dec8d0f2ee7a6cf | [] | 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 | 1,051 | r | weightmaxentropy.Rd.R | library(embryogrowth)
### Name: weightmaxentropy
### Title: Search for the weights of the nests which maximize the entropy
### of nest temperatures distribution
### Aliases: weightmaxentropy
### ** Examples
## Not run:
##D library(embryogrowth)
##D data(nest)
##D formated <- FormatNests(nest)
##D w <- weightmaxe... |
ccb4c997b977e4cb8192d5dbb80e9c032acc1597 | f832c182bc84a0a5892b4d84a75acdacdd434e48 | /quiz3.R | b36e8ef365a498d7fc42b64ae74e71030fe4abb0 | [] | no_license | briholt100/GetClean | 1864c7cd3c5b37855d8f0b24bfb334a0e14d2269 | 261da03c3b7dfbb0316861b84f69574e176669e0 | refs/heads/master | 2021-01-18T18:42:52.633419 | 2014-12-30T02:11:26 | 2014-12-30T02:11:26 | 27,646,720 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,283 | r | quiz3.R | getwd()
#for Dater
setwd("/home/brian/Projects/Coursera/GetAndCleanData")
#for latitude
setwd("/home/brian/Projects/Coursera/GetAndClean")
#for dater_bridge
setwd("C:\\Users\\Brian\\Documents\\Projects\\GetClean")
#for campus
setwd("I:\\My Data Sources\\mooc\\GetCleanData")
if (!file.exists("data")) { dir.create(... |
a4dcb2164ae930f630ed607a089a374365cca262 | 5003102e0f392e1e7618f37d1670af813eaf2ed9 | /ScriptforAMCtry.R | 2d0b9bab14282dc2fb6b5831931b14ab952e4e97 | [] | no_license | nilsmy/AMCTestmakeR | 4b08c17ecea2586845394b9563d0f56aa9367acf | 54c75a7b1733d0ea6d4e5d13dab9b5168bf6f357 | refs/heads/master | 2021-01-19T14:13:06.808718 | 2018-11-10T18:40:06 | 2018-11-10T18:40:06 | 84,669,794 | 1 | 0 | null | 2018-11-10T18:30:49 | 2017-03-11T18:04:07 | R | UTF-8 | R | false | false | 207 | r | ScriptforAMCtry.R |
#Full try !!
AMCcreatetest("How much is $1+2$?",2,list("3", "11"), filepath = "~/Google Drive/AMC/essaiR2/groups.tex", title = "This is the title", paper = "a4", instructions = F, separateanswersheet = F)
|
f1f524f1a0444738cd14c4ff44f3c2c41b2e92de | 6e663d8df86b2d291f710b3f469772a84965852c | /SPADE-analysis/dataprep_viz_sibilants_v1.R | 7ea2eefee2d3188ddcca459abcfb7b8289e61e5e | [
"MIT"
] | permissive | jeffmielke/SPADE | a0c90724ac8c81d2529c3870bab7fcede2f5e461 | e110d5797bf793a7f6b8e3fb0496d9b092b3499e | refs/heads/master | 2021-07-11T09:41:27.268020 | 2018-12-04T15:51:53 | 2018-12-04T15:51:53 | 136,250,150 | 0 | 0 | MIT | 2018-12-04T15:51:55 | 2018-06-06T00:32:30 | Python | UTF-8 | R | false | false | 7,890 | r | dataprep_viz_sibilants_v1.R | ##
## first script doing rough visualization of s-retraction, for four datasets processed so far
##
## Morgan, late 10/2017
##
## you must have:
## '../SOTC/SOTC_sibilants.csv'
## '../buckeye/buckeye_sibilants.csv'
## same for raleigh and icecan
##
## (or change paths for your computer)
##
library(stringr)
library(gg... |
e333052b95249e50ba396687b9bd6a644bb77ad7 | ec87eef707dbf374965aef156dda6de8433892b1 | /julia/code/prismaread/pr_rastwrite_lines.R | ffc93241a37e86295d779ae71918466a24d396c1 | [] | no_license | alveraboquet/stage-Machine-learning | 622f6090feeb63f3ade8100ba5e368236cc0e674 | 2446d8c6ceece39a410dc6f9ad75be901b315a99 | refs/heads/master | 2023-07-02T21:44:43.148221 | 2021-08-09T19:58:43 | 2021-08-09T19:58:43 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,202 | r | pr_rastwrite_lines.R | #' @title pr_rastwrite_lines
#' @description Write a raster object by blocks of lines
#' @param rast_in `Raster* object` to be written to disk
#' @param out_file `character` full path of output image
#' @param out_format `character` [\"TIF\" | \"ENVI\"], Default: 'tif'
#' @param proc_lev `character` [\"1\" | \"2D\"], D... |
17117d3be9cd080a66a86441fbdd573f77c4e661 | f898801224c1f17ba62089b28f3f69c7c525e766 | /binomial/tests/testthat.R | 9d9594c2aafaaf7789cbb41a7b531da05e02e3e9 | [] | no_license | stat133-sp19/hw-stat133-nadia1212 | 44079944e7b5ab9dffdddbbb3fb82033d2de79a9 | 57ba3ab524660f9d3e8162f1b53a6d030eac6dd6 | refs/heads/master | 2020-04-28T12:33:00.104710 | 2019-05-03T19:14:44 | 2019-05-03T19:14:44 | 175,279,474 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 101 | r | testthat.R | library(testthat)
library(binomial)
source("../R/functions.R")
test_file("tests/testthat/tests.R")
|
579752588cf81489d8008807088ad0185c8cfb56 | 0b589418cd520393c7489f022f30c113f59d7a8a | /3. Linear Regression And Modelling/Module 1/residuals.R | a6eb4b3f174338428a8f7cace59daad87d0b3f97 | [] | no_license | papas8105/Statistics-With-R | 373998dac918f53fb01abda37370da5eba746ecd | 0d897fe80c8f508ea7fa956c77122451b11bc279 | refs/heads/main | 2023-03-11T20:45:14.156590 | 2021-03-02T16:42:29 | 2021-03-02T16:42:29 | 318,364,986 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,674 | r | residuals.R | # Derived from http://econometricsbysimulation.shinyapps.io/OLS-App/
# Load packages ----------------------------------------------------------------
library(shiny)
library(openintro)
library(plotrix)
# Define inputs ----------------------------------------------------------------
input <- list(rseed = 1)
seed <- as... |
383db93343cf9739294506cd8eb9ab53eab7e872 | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /examples/sqs.R | cc7263139fe6ff49e80b75d1e4951aa47ae657ed | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | false | 623 | r | sqs.R | # Simple Queue Service examples
sqs <- paws::sqs()
# Create a queue.
sqs <- sqs$create_queue(
QueueName = "ExampleQueue"
)
# Add a message to the queue.
sqs$send_message(
QueueUrl = sqs$QueueUrl,
MessageBody = "foo"
)
# Get the queue's attributes.
sqs$get_queue_attributes(
QueueUrl = sqs$QueueUrl,
Attribu... |
01216ea048e1b7b734ec8773a641db185bdda6cf | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/seewave/examples/synth2.Rd.R | 6ce88e6706030711d4d9800c3c31e123fba6fca7 | [] | 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 | 1,847 | r | synth2.Rd.R | library(seewave)
### Name: synth2
### Title: Synthesis of time wave (tonal model)
### Aliases: synth2
### Keywords: datagen ts
### ** Examples
## You can use plot=TRUE and spectro() options
## to directly 'see' the new-built sounds
## MODIFICATION OF A REFERENCE SIGNAL
data(tico)
env.tico <- env(tico, f=22050, plot... |
1d48bb2524fd8d0b89f5f701079fd706f029a83b | 35a4d25ef4da22e639ebd7411c4f1781a46b88d0 | /man/mk_codons.Rd | 23467b92ed07b43f10f34402501102f11578536b | [] | no_license | rforbiodatascience21/2021_group_20_rpackage | 882e1111331a73cd9eea1d4faa7cfdbe376c98e5 | 696132ba40cdef4052b6130bf708daf3e796c23f | refs/heads/main | 2023-03-24T11:52:33.611925 | 2021-03-22T10:20:07 | 2021-03-22T10:20:07 | 350,259,539 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 380 | rd | mk_codons.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mk_codons.R
\name{mk_codons}
\alias{mk_codons}
\title{DNA sequence to Codons}
\usage{
mk_codons(dna, s = 1)
}
\arguments{
\item{dna}{List of nucleotides (A,T,G,C)}
}
\value{
codons Triplets of nucleotides
}
\description{
Separates one sequenc... |
84d6d8dd6a4fb6212a1de852fc00cb3df698bd31 | 3bc412a57570785ad898af1a5e4283d84b109b68 | /section-11/sec-11.R | 289e2c1a068ab3b558d110946e1a1cad2fa2d239 | [] | no_license | pbaylis/ARE212 | 7889bafcc9fcdc1fee1d82f41404ec3506a55776 | 4ae1b7164d315dfea7fce622d0159983b8e9aa87 | refs/heads/master | 2020-05-31T10:48:39.896020 | 2019-04-23T20:12:50 | 2019-04-23T20:12:50 | 15,325,980 | 3 | 5 | null | null | null | null | UTF-8 | R | false | false | 1,831 | r | sec-11.R | rm(list = ls())
library(XML)
library(RCurl)
library(stringr)
options(show.error.messages = FALSE)
token <- "characters"
nameslist <- list()
i <- 1
time <- proc.time()
while (is.character(token) == TRUE & i < 100000) {
baseurl <- "http://oai.crossref.org/OAIHandler?verb=ListSets"
if (token == "characters") {
t... |
78b66967f4a3cace052a2599b01a6c058acb6bd4 | 1cf1f5e094abdca9cf4222aeeaf393154d5b091d | /chap3/RINT302.R | bb1d0dc03bcd33c7e79b5e3600104bb0432e3385 | [] | no_license | Daigo1009/r_introduction | a0c14d5ccc1395118ca2cc1fe6141a743f3eabce | e9983214ce3b61a8197ac003f1ee62fd1b9c0943 | refs/heads/master | 2022-04-19T16:32:38.699232 | 2013-10-08T13:52:12 | 2013-10-08T13:52:12 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 135 | r | RINT302.R | x = 0:7
y = dpois(x,3)
par(family="HiraMaruProN-W4")
plot(x,y,type='l',xlab='x',ylab='y',main=' ポワソン分布')
|
3244dbc2696dc7e7f1f2193893b64ff7470da038 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/rprojroot/examples/root_criterion.Rd.R | b40a2fd2a9c0a15cac8b94e8ef45a29f0a8e2f7d | [] | 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 | 524 | r | root_criterion.Rd.R | library(rprojroot)
### Name: root_criterion
### Title: Is a directory the project root?
### Aliases: root_criterion is.root_criterion as.root_criterion
### as.root_criterion.character as.root_criterion.root_criterion
### |.root_criterion has_file has_dir has_file_pattern has_dirname
### ** Examples
root_criteri... |
2a062f0a03513c5c811e9d88ff60cb1eec0edc4e | 23375da49f22e497f1d805f1a15199c3577b2e02 | /README.rd | 1ca595849c7d0254957ac04836784c3df55dce8b | [] | no_license | acelan86/Jager | e8f44d4fc985d20a829b595f5ab5289f6eb74956 | c47d4b2f378fc6e5262346bf2b1885005116153f | refs/heads/master | 2021-01-19T21:28:10.340732 | 2014-06-27T03:25:37 | 2014-06-27T03:25:37 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 30 | rd | README.rd | # Fate Zero
# Update by acelan |
c1f7fc1831df3680398062eaac4a0fb9f3a9d003 | eb1c89cf89947b2c0222dfede4cd0f3885465e34 | /Dose finding - KGC-v2.0.r | 60af28923955b614e4469d8deff1ae953bf37ddc | [] | no_license | AmirAli-N/DynamicProgramming-DoseFinding | b799b8164280a12e3283a4c365b937e39672883f | 92aa8c618d56f10b801985f4173b719b1d798c34 | refs/heads/master | 2020-04-01T15:46:23.626118 | 2019-07-12T20:11:28 | 2019-07-12T20:11:28 | 153,350,921 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,018 | r | Dose finding - KGC-v2.0.r | library(mvtnorm)
##########################################################################
y=c() #response vector
dose=c() #dose vector
J=11 #number of doses
patient=1000#number of patients
true_sigma=sqrt(10) #true deviation of responses
mu_0=c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0) #initial hyperparameter
sigma_0... |
dae99881c368cf984d9fb2310c70cbf300d95a2e | fd0ab0f09d3c07f03e0af82bf93875524c44a0e9 | /tmp-tests/test-pcadapt3.R | f22eca37f547c849ae43a70f253b91b270f8f278 | [] | no_license | privefl/bigsnpr | b05f9e36bcab6d8cc86fb186c37fe94a6425960a | 83db98f974b68132a9a3f3ee7ca388159a4c12b5 | refs/heads/master | 2023-08-02T13:31:18.508294 | 2023-06-30T12:15:55 | 2023-06-30T12:15:55 | 62,644,144 | 162 | 47 | null | 2022-10-12T16:46:15 | 2016-07-05T14:36:34 | R | UTF-8 | R | false | false | 757 | r | test-pcadapt3.R | snp_pcadapt <- function(G, U.row, ind.row = rows_along(G)) {
K <- ncol(U.row)
stopifnot(all.equal(crossprod(U.row), diag(K)))
zscores <- linRegPcadapt(attach.BM(G), U = U.row, rowInd = ind.row)
d <- covRob(zscores, estim = "pairwiseGK")$dist
fun.pred <- eval(parse(text = sprintf(
"function(xtr) stats::... |
9e67db3a84c1601beb5e70d9389a4d3754266c81 | 5233a4040c4f2d3fc79d98f306e0f7cc1db72171 | /RxODE/tests/test-parsing.R | 524e68c66dd29df071409d0c2a648f10c8735e75 | [] | no_license | hallowkm/RxODE | fccac362359b4874d88292011558d4684aa8610f | 5e0526d1c85a8ae943610ead167bca8b135909d5 | refs/heads/master | 2020-04-03T20:55:35.695093 | 2017-03-28T11:37:45 | 2017-03-28T11:37:45 | 38,068,516 | 18 | 15 | null | 2016-11-01T20:48:13 | 2015-06-25T19:08:25 | C | UTF-8 | R | false | false | 2,254 | r | test-parsing.R | # test ODE parsing for syntax errors
library("RxODE")
library("tools")
tmp <- tempdir()
# list of model specs with errors (test description and code)
errs <- list()
errs[[1]] <-
c(desc = 'incorrect d/dt operator',
code = 'd/dt(y = 1);'
)
errs[[2]] <-
c(desc = 'comments must be outside statements',
... |
6a16fc68c66b5c754e32eedea43f46d4f4e96111 | b1ebb9059b912bd0bee6af370e04533e8ffe1e5d | /week5/67_lab_pcr_pls_regression.R | d9447ae2604ed2c46c6c9a5b30edf792737e3a0f | [] | no_license | sebastianbautista/stat508 | 57c25364361782addba41a69cccb61c274d4dd4b | 9b24d49639747b88e129c9c253d443a2e28cd86f | refs/heads/master | 2020-04-16T11:57:43.166831 | 2019-04-24T21:48:50 | 2019-04-24T21:48:50 | 165,559,062 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 2,106 | r | 67_lab_pcr_pls_regression.R | # 6.7 Lab 3: PCR and PLS Regression
### 6.7.1: Principal Components Regression
library(ISLR)
library(pls)
# Remove missings
df = na.omit(Hitters)
x = model.matrix(Salary ~ ., df)[,-1]
y = df$Salary
# train test split
set.seed(1)
train = sample(1:nrow(df), nrow(df)/2)
test = (-train)
Xtrain = x[train,]
Xtest = x[t... |
065f3fa79c40938426232508ed2d8ff5b25a122f | bde57b95fe493922baded8d3090a7633c56b2b54 | /doc/recipe-install-package.R | 798d11fc6ff2b4c378bfb906b8eec92974661f76 | [] | no_license | datakolektiv/vincent | 49e0110a1c336654e17760b2e20f6abd455eafd0 | 932d2ff1aefd95affdaf242e6cfdf7aa8d4113ea | refs/heads/master | 2022-11-10T11:29:15.842678 | 2020-06-20T06:53:29 | 2020-06-20T06:53:29 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 593 | r | recipe-install-package.R | # This script shows you how to install a new package to the project
# install a package -------------------------------------------------------
renv::install("shinydashboard") # 1. INSTALL the package
usethis::use_package("shinydashboard") # 2. fill in DESCRIPTION
renv::snapshot() # 3.... |
f8a40f9306cfa1477533ffb6caa7a158b4aaddf7 | 9ec017b29b36c2c10468b230b943a592c26ff6d2 | /man/paste.Rd | b042e9f6881c582447dbd12999aeb0041eb4a0fb | [] | no_license | efinite/utile.tools | fa2736d329a31fd20ca33f3b5d1d72750523ce06 | d059e684da40da3adb8c080fc945ffd661d756ba | refs/heads/master | 2023-01-30T16:40:59.681104 | 2023-01-24T00:45:37 | 2023-01-24T00:45:37 | 212,999,245 | 5 | 1 | null | 2022-11-20T12:35:11 | 2019-10-05T12:54:39 | R | UTF-8 | R | false | true | 1,057 | rd | paste.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paste.R
\name{paste}
\alias{paste}
\alias{paste0}
\title{Concatenate strings}
\usage{
paste(..., sep = " ", collapse = NULL, na.rm = FALSE)
paste0(..., collapse = NULL, na.rm = FALSE)
}
\arguments{
\item{...}{R objects to be converted to cha... |
ed1aa505cf099e0409e70faf7a320dfbab36cd44 | f53cd52cab7c69718e63da3a5c42ac504e3f4249 | /R/format_magma_raw.R | 9dcf257ae892b250fbee9c370cfef9976c7c363d | [
"MIT"
] | permissive | mbyvcm/correlation_matrix_for_twas | f27ea4a0bb4c30f9712fc6b5f4af90d24a8fa5cc | 0e4dc0252983eaa056db0b6e8fa42b9c9b80cf2c | refs/heads/master | 2020-03-06T18:26:31.641344 | 2018-03-27T15:31:15 | 2018-03-27T15:31:15 | 127,006,928 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 8,754 | r | format_magma_raw.R |
# Christopher Medway
# Requires that correlations between genes have already been calculated
# using twas_matrix_for_magma.R
format_twas_raw_file <- function(matrix_dir, pos_file, twas_file, sampleSize = 100000, nparam = 100, symbol2EntrezId) {
matrix_files <- list.files(matrix_dir, pattern = ".csv", full.nam... |
c1c00b7fd857e230fef9178048eca98e4f0d0383 | 24de0621f2a4ddfdb4696c071923610167a3c742 | /eda_all.R | 3319c55adb730e4acef76e2652436a4087d782e8 | [] | no_license | truongvv/fineco_as2 | 1d85acbc7a3ba208925d23b383c47ad8d3a95946 | b3f4d015f0ad997e8d88451f7934eba4a49e943d | refs/heads/master | 2020-07-02T16:42:35.472281 | 2019-10-05T01:00:28 | 2019-10-05T01:00:28 | 201,592,492 | 0 | 6 | null | 2019-10-05T01:00:32 | 2019-08-10T06:53:28 | HTML | UTF-8 | R | false | false | 3,844 | r | eda_all.R | install.packages("hrbrthemes")
library(hrbrthemes)
hrbrthemes::import_roboto_condensed()
#John EDA
Combi_df <- data.frame(date=index(Combi), coredata(Combi))
Combi_df$date <- as.Date(Combi_df$date)
#Plotting ASX 200
ggplot(Combi_df, aes(date, asx)) + geom_line() +
xlab("Date") + ylab("ASX Index") + ggtitle("Value of... |
740dcddab32a7344b9ddc0d3569cea40b6893e1c | 78497d81769d572ef666bf91e24be399e6c57de0 | /R/C_MatrixW_treeHarvey.R | cbd878e2093a55596c1638740a8b7b5b236018e6 | [] | no_license | kostask84/MS_Tyrannidae_AgeAssemblage | 112f201a1b9081d7d54afdd3200a2313cd7e2196 | 8dab8dffe3c7269ac13053a8007bbc49e9584bb3 | refs/heads/master | 2023-04-12T20:23:57.850187 | 2021-05-05T15:44:18 | 2021-05-05T15:44:18 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,516 | r | C_MatrixW_treeHarvey.R |
# loading tree from Harvey ------------------------------------------------
trfn = np(paste("T400F_AOS_HowardMoore.tre", sep=""))
moref(trfn)
tr = ape::read.tree(here::here("data", trfn))
# data with species codes
spp_codes <- read.csv(here::here("data", "Species_name_map_uids.csv")) # species codes for phylogenetic ... |
819e81fdcb6ac9c9c0b57cecadd684463db3e601 | fd1453bda46735d1c348e05c482f639f2222e490 | /R/01proc-issp.R | 9ac7807603b3ee1ca5446cc178ae1fc784416011 | [] | no_license | valentinaandrade/health-inequality | a39a0c129ae1408047a531cdaaeef0ef385885f2 | 3955832caf898720f97d77fb3d126aed3e00392b | refs/heads/main | 2023-08-17T02:54:05.531630 | 2021-09-22T10:14:38 | 2021-09-22T10:14:38 | 353,554,695 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 21,288 | r | 01proc-issp.R | # Code 0: Preparation -----------------------------------------------------
# Valentina Andrade
# 1. Cargar librerias -----------------------------------------------------
pacman::p_load(tidyverse, haven,sjPlot,sjlabelled,sjmisc)
# 2. Cargar bases de datos ------------------------------------------------
## ISSP Mo... |
9ecce8905a4147d92acdccdc38d263edaee83acb | a59b0019cd455e5c8c59263d5248b388eb235257 | /tests/testthat/test-residuals.R | 8f145be9cb83a4c6eccabf9feec9f8275166f29a | [
"MIT"
] | permissive | dill/gratia | 4df529f5e636a0139f5c355b52a2924bebf7aca4 | 26c3ece0e6a6298ab002b02019b0ea482d21dace | refs/heads/master | 2023-04-08T18:35:18.730888 | 2023-03-20T12:52:33 | 2023-03-20T12:52:33 | 160,169,115 | 0 | 0 | NOASSERTION | 2018-12-03T09:54:30 | 2018-12-03T09:54:30 | null | UTF-8 | R | false | false | 2,604 | r | test-residuals.R | ## Test partial_residuals() and related residuals functions
## load packages
library("testthat")
library("gratia")
library("mgcv")
library("gamm4")
N <- 400L
df <- data_sim("eg1", n = N, seed = 42)
## fit the model
m <- gam(y ~ s(x0) + s(x1) + s(x2) + s(x3), data = df, method = 'REML')
m_bam <- bam(y ~ s(x0... |
145566c350fa2890943cb99f7ee4cc3da5af53d1 | c5c28143020868ee0ca15f8a99fafffb4c6ea056 | /tests/testthat/test-xml_children.R | d80ee8338c92b1d8b56f0574c6f05acfe3e63e1e | [] | no_license | chan0415/xml2 | 37b9c825cf87460722b48f96d43469db80e1c098 | 8bb23483a85389a053897111045a65381a8bc86f | refs/heads/master | 2021-05-06T03:35:27.368023 | 2017-11-22T21:54:19 | 2017-11-22T21:56:28 | 114,906,229 | 0 | 1 | null | 2017-12-20T16:05:41 | 2017-12-20T16:05:40 | null | UTF-8 | R | false | false | 1,535 | r | test-xml_children.R | context("xml_children")
x <- read_xml("<foo> <bar><boo /></bar> <baz/> </foo>")
test_that("xml_child() returns the proper child", {
expect_equal(xml_child(x), xml_children(x)[[1L]])
expect_equal(xml_child(x, 2), xml_children(x)[[2L]])
})
test_that("xml_child() returns child by name", {
expect_equal(xml_child(... |
76573022a6079e9f7f73df441043d6f4053f94d0 | a5b8eb7b0f3f3c7a9668ee7e07abdb2ef3452cce | /sex.ethnicity.grs.may.2018/scripts/describe.grs.mr.publication.plots.180802.R | a19ccb81e223dba8cd68a3229037920df9a8bc94 | [] | no_license | lindgrengroup/causal.relationships.between.obesity.and.leading.causes.of.death.in.men.and.women | 5073125353b38eed35dc28bc483098e1cfbc89a4 | c991d84967d913c23c665389b17315cdb04a3a3c | refs/heads/master | 2020-07-08T20:30:17.381304 | 2019-10-14T07:30:02 | 2019-10-14T07:30:02 | 203,767,839 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 58,062 | r | describe.grs.mr.publication.plots.180802.R | #!/bin/env Rscript
#$-cwd
library(ggplot2)
library(gridExtra)
library(lattice)
library(grid)
library(grDevices)
library(ggpubr)
X11(height = 30, width = 40)
####################################################################
########################## Start with GRSs
###############################################... |
f35277ee1fcfdb2787ffaec26df59f0458aedfc1 | 6312f6e7e2e22bb7cb7580b0b92c0a6bbeeb5627 | /wltr_new/wltr.git/train.R | 6d19caf5be909b12f2703430e631ce027ac19ba8 | [] | no_license | babyang/wltr | 20708cee2661b9c6ae8b67bdf43343dfbeadac84 | 9a9a76d474aebf3fc350b9cdcf5734328b11be60 | refs/heads/master | 2020-05-17T02:40:21.406024 | 2014-12-02T09:30:23 | 2014-12-02T09:30:23 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,149 | r | train.R | require(glmnet)
require(doMC)
registerDoMC(cores=12)
# zhiyuan code using absolute folder name
# source("/home/zhiyuan/Projects/wltr/utils.R")
# source("/home/zhiyuan/Projects/wltr/alarm_sms.R")
# minxing code using his folder name
#source("/home/minxing/projects/zhiyuan/wltr/utils.R")
#source("/home/minxing/projects... |
a936e09fbc18e8c840a8892f631b5f97fb347904 | 9efa134c757f6f8938cb17d565be9f5e87e8c8e9 | /man/deleteGuild.Rd | 21f87e892f27f8929951557397b53e9134f26700 | [] | no_license | bpb824/brewerydb | 04f07279e18c63c054c62244669aeeaccacbf921 | 1fed6d68ac6a9543b8fa04c0efb11631fdc78d65 | refs/heads/master | 2022-01-20T05:11:49.833630 | 2019-06-23T02:37:58 | 2019-06-23T02:37:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 295 | rd | deleteGuild.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Guild.R
\name{deleteGuild}
\alias{deleteGuild}
\title{Delete an Guild}
\usage{
deleteGuild(guildId)
}
\arguments{
\item{guildId}{The guildId}
}
\value{
none
}
\description{
Deletes an existing guild
}
\concept{Guild}
|
9223d9bf10031315f165f5fa19c33d9c06654bc4 | 7f72ac13d08fa64bfd8ac00f44784fef6060fec3 | /RGtk2/man/gtkTooltipsDisable.Rd | 6e3fe617e533f77d1bffa80cbd25ca37725e8c6d | [] | no_license | lawremi/RGtk2 | d2412ccedf2d2bc12888618b42486f7e9cceee43 | eb315232f75c3bed73bae9584510018293ba6b83 | refs/heads/master | 2023-03-05T01:13:14.484107 | 2023-02-25T15:19:06 | 2023-02-25T15:20:41 | 2,554,865 | 14 | 9 | null | 2023-02-06T21:28:56 | 2011-10-11T11:50:22 | R | UTF-8 | R | false | false | 611 | rd | gtkTooltipsDisable.Rd | \alias{gtkTooltipsDisable}
\name{gtkTooltipsDisable}
\title{gtkTooltipsDisable}
\description{
Causes all tooltips in \code{tooltips} to become inactive. Any widgets that have tips associated with that group will no longer display their tips until they are enabled again with \code{\link{gtkTooltipsEnable}}.
\strong{WARN... |
0af56e631ce4e9edbed2e354938a72a2805de67f | d8674514f06e48dc264d82096dbd5517b115ff29 | /script/known_filter.R | 8c5fba65544d9cb2e7c69a332b763ddc22b0aa7d | [] | no_license | nzhun/PAH | 23d7414b8ea728094ce3d41b4facee4c7733f29f | beb8c52cca7d04b5aac6455d572998902ead9e86 | refs/heads/master | 2021-09-16T12:34:20.463132 | 2018-06-20T17:19:26 | 2018-06-20T17:19:26 | 107,172,775 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,369 | r | known_filter.R | #setwd("~/server")
setwd("/home/local/ARCS/nz2274/")
source("Pipeline/NA_script/R/untils.R")
filter_allfreq_local <- function(data,freq_avg,freq_max){
data <- data[which(na.pass(as.numeric(data$ExAC_ALL)< freq_avg)
&na.pass(as.numeric(data$ExAC_AMR)< freq_max)
&as.numeric... |
5a2b90b0341ff2cdf35d848ca8ce138b0df2d0d7 | 72eea872c42a5197b1e79a53413d718b83d6aebc | /R/as_openadd.R | d4117667e9e84841553f438a80e6448e6164bc8b | [
"MIT"
] | permissive | sckott/openadds | 72b7a422a5363bebca017eb8d2b31c3a5300a0c4 | 7cb6991a5206caeeb0ce9821c83c61fbc40eeb03 | refs/heads/master | 2021-07-11T01:33:01.977702 | 2021-03-17T16:35:47 | 2021-03-17T16:35:47 | 34,580,790 | 9 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,383 | r | as_openadd.R | #' Coerce to openadd object
#'
#' @export
#' @param country (characater) Country name
#' @param state (characater) State (or province) name
#' @param city (characater) City name
#' @param ... ignored
#' @details This is a helper function to let the user specify what they want
#' with any combination of country, state, ... |
107976aa2ebffac1c33900d30118ae1db701dfdb | 64c6ff944757012350441458db8229cca0baa64f | /docs/Shiny_Apps/full_roster_compile/server.R | 8d56e178add41d3dffd2b9ec288c943c0d6c20d1 | [] | no_license | noahknob/Baseball_App | c4a5e324a662ab9104976aa59adbfa9af33758a1 | 75c1bce369eab1c3e2b4c82aa1464593db845320 | refs/heads/master | 2022-02-25T09:39:02.650009 | 2019-10-26T19:10:13 | 2019-10-26T19:10:13 | 115,544,306 | 0 | 0 | null | 2018-01-29T23:48:56 | 2017-12-27T17:44:21 | R | UTF-8 | R | false | false | 3,465 | r | server.R | library(shinydashboard)
library(shiny)
library(tidyverse)
server <- function(input, output, session) {
avg_pitcher_stats <- read_delim("https://raw.githubusercontent.com/noahknob/Baseball_App/master/data/avg_pitcher_stats.txt", delim = "\t")
avg_batter_stats <- read_delim("https://raw.githubusercontent.com/noahkno... |
cb884583d7747fe36b5df4ec67fb388779015117 | 45ab1e397b5fc69ba84c8f5dfb66c09b79bca4c6 | /Course_III/ECONOMETRICS/pract12/task3_reverse.r | ac751d0d9395e713ee444512faad752cbbc6e76a | [
"WTFPL"
] | permissive | GeorgiyDemo/FA | 926016727afa1ce0ee49e6ca9c9a3c60c755b35f | 9575c43fa01c261ea1ed573df9b5686b5a6f4211 | refs/heads/master | 2023-06-28T00:35:43.166167 | 2023-06-16T14:45:00 | 2023-06-16T14:45:00 | 203,040,913 | 46 | 65 | WTFPL | 2022-04-09T21:16:39 | 2019-08-18T18:19:32 | Jupyter Notebook | UTF-8 | R | false | false | 8,236 | r | task3_reverse.r | ###########Это неправильная модель, где зависимость площади от цены, а не наоборот
#####Тоже проанализитровал все коэффы тестов, поэтому жаль удалять
#install.packages("lmtest")
#install.packages("forecast")
#install.packages("tseries")
#install.packages("orcutt")
#install.packages("orcutt")
library(orcutt)
library(lm... |
953f2b84da06d0d4582180ae35c552f3c1070b0d | 01d9837a6754cb24d10a2874b7c49f224e3b97ba | /lab3package/R/laboratory3.R | 3b7fc48d69b42f6e2f68d321f14a4b986acd5f9e | [] | no_license | tenoglez/ARP_Laboratory3 | 89f81ee4fd351214d250766d41ee018e0c7e90c3 | e60aac5379fcbf268e2136f995b13d199439cbb2 | refs/heads/master | 2020-04-10T19:45:54.487373 | 2016-09-15T12:34:16 | 2016-09-15T12:34:16 | 68,100,323 | 0 | 2 | null | null | null | null | UTF-8 | R | false | false | 834 | r | laboratory3.R | #' A package for computating the notorious Dijkstra and Euclidean algorithms.
#'
#' @description The lab3package provides two categories of important functions:
#' euclidean and dijkstra. Furthermore, it contains the dataset wiki_graph for dijkstra funtion testing.
#'
#' @details The lab3package functions consist of ... |
0be7a5f87087e59210601d81e70237cfc0117bee | 7b82068433efacf8840c57e2c05b613dbe13d31c | /man/HyperparameterTuner.Rd | 0c8263f5ddc93097ab68e351d3780708e81e6a16 | [
"Apache-2.0"
] | permissive | OwenGarrity/sagemaker-r-sdk | d25f0d264dcddcb6e0fa248af22d47fc22c159ce | 3598b789af41ed21bb0bf65bd1b4dfe1469673c9 | refs/heads/master | 2022-12-09T04:50:07.412057 | 2020-09-19T13:02:38 | 2020-09-19T13:02:38 | 285,834,692 | 0 | 0 | NOASSERTION | 2020-09-19T13:02:39 | 2020-08-07T13:23:16 | R | UTF-8 | R | false | true | 34,343 | rd | HyperparameterTuner.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/tuner.R
\name{HyperparameterTuner}
\alias{HyperparameterTuner}
\title{HyperparamerTuner}
\description{
A class for creating and interacting with Amazon SageMaker hyperparameter
tuning jobs, as well as deploying the resulting mode... |
f121b8cab980c3d88c051a53512adb8d8dea2406 | da54c2a9cbf91a38b68b8b5424e5297ed83600fb | /man/inspect_panelist_preference.Rd | 6c1e51986c75d277057586a7a45bf6aefd75812e | [
"MIT"
] | permissive | isoletslicer/sensehubr | 19242d0d9bedb949bb617dbb274b2d1c95410182 | 85f70435439030a6d11ec5fd1e793c68ca692ae1 | refs/heads/master | 2020-06-19T07:30:55.226074 | 2019-08-20T04:20:51 | 2019-08-20T04:20:51 | 196,618,502 | 0 | 0 | NOASSERTION | 2019-08-20T03:15:11 | 2019-07-12T17:23:46 | R | UTF-8 | R | false | true | 472 | rd | inspect_panelist_preference.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/inspect-panelist-preference.R
\name{inspect_panelist_preference}
\alias{inspect_panelist_preference}
\title{Inspect preference}
\usage{
inspect_panelist_preference(res_preference, dimension = c(1, 2))
}
\arguments{
\item{res_preference}{outpu... |
41504d959b99702433255d920eea1f8190d7905d | a47ce30f5112b01d5ab3e790a1b51c910f3cf1c3 | /A_github/sources/authors/864/jointDiag/ajd.R | 2b1156b39fa6659be860a296d19d922845b89026 | [] | no_license | Irbis3/crantasticScrapper | 6b6d7596344115343cfd934d3902b85fbfdd7295 | 7ec91721565ae7c9e2d0e098598ed86e29375567 | refs/heads/master | 2020-03-09T04:03:51.955742 | 2018-04-16T09:41:39 | 2018-04-16T09:41:39 | 128,578,890 | 5 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,125 | r | ajd.R | ## a wrapper to joint approximate functions
ajd <- function(M,A0=NULL,B0=NULL,eps=.Machine$double.eps, itermax=200,
keepTrace=FALSE,methods=c("jedi")) {
nmeth <- length(methods)
if (nmeth==1) {
for (i in 1:nmeth) {
if (methods=="jedi")
res <- jedi(M,A0,eps,itermax,keepTrace)
if (methods=="uwedge")
... |
3064a132ee7ecc104cb7fe8013a78e24f6592485 | 5bb2c8ca2457acd0c22775175a2722c3857a8a16 | /man/coefficients-Zelig-method.Rd | d3bb4ee6b1876074721c862dcc8d247871e4410e | [] | no_license | IQSS/Zelig | d65dc2a72329e472df3ca255c503b2e1df737d79 | 4774793b54b61b30cc6cfc94a7548879a78700b2 | refs/heads/master | 2023-02-07T10:39:43.638288 | 2023-01-25T20:41:12 | 2023-01-25T20:41:12 | 14,958,190 | 115 | 52 | null | 2023-01-25T20:41:13 | 2013-12-05T15:57:10 | R | UTF-8 | R | false | true | 432 | rd | coefficients-Zelig-method.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/model-zelig.R
\docType{methods}
\name{coefficients,Zelig-method}
\alias{coefficients,Zelig-method}
\title{Method for extracting estimated coefficients from Zelig objects}
\usage{
\S4method{coefficients}{Zelig}(object)
}
\arguments{
\item{obje... |
f95e0d2ebe54469a5669f55e42d42d2068596f1e | 6d5a7d0a5f55520fceb0a2868bc6b7fb7903075a | /man/as.tree.Rd | a7a65e07358ee33ca9d458f6af3b62106ab355b5 | [] | no_license | meta-QSAR/simple-tree | 7dbb617aff4e637d1fcce202890f322b99364494 | 28ff7bf591d3330498a3c8a85d8ae5a3d27b37d5 | refs/heads/master | 2016-09-14T07:08:33.743705 | 2015-08-04T09:31:24 | 2015-08-04T09:31:24 | 58,349,277 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 648 | rd | as.tree.Rd | % Generated by roxygen2 (4.1.1): do not edit by hand
% Please edit documentation in R/class-tree.R
\name{as.tree}
\alias{as.tree}
\title{Convert a data frame to a tree object}
\usage{
as.tree(df, id.col = "id", parent.id.col = "parent.id", name.col = "name")
}
\arguments{
\item{df}{A data frame.}
\item{id.col}{Column ... |
4513860251374aec0a2f504ba33cddae5e51febd | 3355b24230020e5fdcdef52a3d621cd0d96ee72e | /2PropTestMC1.R | 088c261ac70a42165604744afc4602d55b1def6a | [] | no_license | IKapenga/Stat1600-QGen | 42f255fba63308b8b1376211066f2d6c01d1d329 | aca46c451d5b45caf70f87d9a58a83bbcbe4f19a | refs/heads/master | 2021-06-03T22:13:23.138457 | 2020-07-16T18:29:38 | 2020-07-16T18:29:38 | 134,891,183 | 0 | 2 | null | 2020-06-13T19:26:53 | 2018-05-25T18:26:50 | R | UTF-8 | R | false | false | 4,679 | r | 2PropTestMC1.R | ##### 2PropTestMC1 #####
twoPropTestMC1= function(
title = "2PropTestMC1", # Question-bank title that will be easily viewable in e-learning
n = 200, # Number of questions to generate
type = "MC", # The question type, one of many possible types on e-learning
answers = 5, # Number of answers per MC question
points.per.q ... |
957dfbbff734fa9303e60d7a2abd1bca431e9719 | f547a9f2f59d51416399e7798c395b04c6f3713c | /HDT8.R | 5d366eeec57cddffd599061d5b53d22515e46bc4 | [] | no_license | andreaeliasc/HDT8-RNA | e0a8fccbba125e6311b83ae6dcdca7f5d342650f | a0636f391058982125cb73036b08344cd688ae20 | refs/heads/main | 2023-04-14T22:00:08.979773 | 2021-05-04T06:01:49 | 2021-05-04T06:01:49 | 364,089,170 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,947 | r | HDT8.R | ibrary(e1071)
library(caret)
library(rJava)
library(nnet)
library(RWeka)
library(neural)
library(dummy)
library(neuralnet)
library(dplyr)
library(tidyr)
library(rpart)
library(caret)
library(tree)
library(rpart.plot)
library(randomForest)
library(cluster)#Para calcular la silueta
library(e1071)#para cmeans
library(clus... |
1346c54a6ab8cc64ffea6211dc47606e39cb4417 | 46b8efea7116a3808a2009faad5ed5b90238ec04 | /man/rep_style_rel.Rd | 770475b14f3de317c23d72433033f88cb05e303f | [] | no_license | erge324/stylesim | 205e49855323280f16d3c2dc8f604f3827ee1719 | bd2ee33771ac5c7c480e34e71231f5504a1e488c | refs/heads/master | 2022-02-25T08:20:50.295444 | 2016-03-04T10:57:00 | 2016-03-04T10:57:00 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 3,597 | rd | rep_style_rel.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fun_replicate-simulation.R
\name{rep_style_rel}
\alias{rep_style_rel}
\title{Replicate a Style Simulation and Investigate Effect on Cronbach's Alpha}
\usage{
rep_style_rel(reps = 1000, n = c(100, 1000), items = c(5, 10),
categ = c(3, 7), nd... |
9cdc7b6e2e66260c11e0ddc3d02b1dca0be209e5 | e9275362bc90afb1218c7035db5e993d2cf256aa | /statistical_rethinking/code/quadratic_curves_from_lines.r | bacf8f80bad2ca26716fc4117b45a185b323f91a | [] | no_license | hanson377/textbook_notes_and_exercises | 620cd844926a0553c3dfc46634ae991dadbe57eb | 09c60c523ac8730c054c535515e9cda7271d642e | refs/heads/main | 2023-06-05T20:57:54.007065 | 2021-07-07T11:54:15 | 2021-07-07T11:54:15 | 383,776,330 | 0 | 0 | null | 2021-07-07T11:54:16 | 2021-07-07T11:33:58 | Python | UTF-8 | R | false | false | 1,716 | r | quadratic_curves_from_lines.r | library(rethinking)
data(Howell1)
d <- Howell1
## first, standardize metrics
d$weight_s <- (d$weight - mean(d$weight))/sd(d$weight)
d$weight_s2 <- d$weight_s^2
m4.5 <- quap(
alist(
height ~ dnorm(mu,sigma),
mu <- a + b1*weight_s + b2*weight_s2,
a ~ dnorm(178,20),
b1 ~ dlnorm(0,1),
b2 ~ dnorm(0,1... |
03687b861878a70bc342de2d66146233ef9f7c06 | 47c81e91c91d6f321418042a69d5770b5aaadbdf | /tests/test_graphics.R | b1eede9699f183dba615e2b36ed48bc2ef02b369 | [
"Apache-2.0"
] | permissive | Kaggle/docker-rstats | f6e4c28638e5f9d33de59bcc56ac296da49f2176 | 2a42e7619ff99579011ca9cace98ee4604d9c068 | refs/heads/main | 2023-09-01T11:24:00.881089 | 2023-08-22T16:43:21 | 2023-08-22T16:43:21 | 33,904,503 | 135 | 103 | Apache-2.0 | 2023-08-29T14:50:52 | 2015-04-14T01:46:50 | R | UTF-8 | R | false | false | 179 | r | test_graphics.R | context("graphics")
test_that("plot", {
testImage <- "/working/base_graphics_test.jpg"
jpeg(testImage)
plot(runif(10))
dev.off()
expect_true(file.exists(testImage))
})
|
c4fcebb2fb1d62914d81825ffac240fe948ac008 | cb66ae3bf5bd2422e70df574340e0d5f5388eb8e | /Lorenz_test_presentation.R | 768bce691beb7c6c470b675e90f754f3f1d63800 | [] | no_license | jvoorheis/MSA_Ineq | 779f28947f243495d4c28b6841b56d2c51dc97e6 | 3dbec52e82d0ae86d6d88c6550aadba4b43cb81a | refs/heads/master | 2016-08-02T22:44:29.331869 | 2013-12-28T07:50:20 | 2013-12-28T07:50:20 | 11,228,792 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 7,481 | r | Lorenz_test_presentation.R | #load lorenz_data
library(data.table)
library(xtable)
load("/media/john/Shared Linux_Windows Files/MSA Level Inequality/Data/lorenz_stats.rda")
source("/media/john/Shared Linux_Windows Files/MSA Level Inequality/Code/functions.r")
load("/media/john/Shared Linux_Windows Files/MSA Level Inequality/Data/PersInc.rda")
libr... |
79967ebd58aeee3b540468d1a778129d10c64b39 | e3259d8f489b093b246fe2fd0c4fb6999d6466bf | /man/camptoyear.Rd | 4706f7e5539d724430e919c8da749fcf34283980 | [] | no_license | Franvgls/CampR | 7baf0e8213993db85004b95d009bec33570c0407 | 48987b9f49ea492c043a5c5ec3b85eb76605b137 | refs/heads/master | 2023-09-04T00:13:54.220440 | 2023-08-22T14:20:40 | 2023-08-22T14:20:40 | 93,841,088 | 0 | 2 | null | null | null | null | UTF-8 | R | false | true | 742 | rd | camptoyear.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/camptoyear.R
\name{camptoyear}
\alias{camptoyear}
\title{Transforma series de nombres de campaña en años}
\usage{
camptoyear(x)
}
\arguments{
\item{x}{Vector con la serie de nombres de campaña a transformar a años}
}
\description{
Transforma ... |
06cfe4859bb2db1118ec66fb92139c10d79eff01 | 5be5d6d7383922adb917c91caa03765eb68a37b9 | /R/helper.R | aed9c5b04f80696b0f34f9d2d81f30c8f3cf9788 | [] | no_license | philipbarrett/debtLimit | f70c547bc5bc916ca847ab07c034572392ec6109 | 82c70931c8f6e0ee230e2ca3a8c2f597e86fdaae | refs/heads/master | 2021-09-07T02:12:59.029093 | 2018-02-15T16:35:19 | 2018-02-15T16:35:19 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,928 | r | helper.R | ####################################################################################
# helper.R
#
# Various helper functions
# 01jun2017
# Philip Barrett, Washington DC
#
####################################################################################
rg.read <- function( cty = 'USA', start.date = "1960-01-01" ){
... |
e97b33cc8c32d1871099b8d13046de8b2ab2852d | 740c286f1328664983afd3d920bdf2d74715dc5d | /2017/2017_Fall_RShiny_DC_Crime/global.R | 35714d1ffaaa8a12e513c074f38d54a096a9c080 | [] | no_license | WeihaoZeng/Work_Sample | 8935f0c3e060ffca113ea5f380c018c3e1cc1a01 | ed888dbfb129ed7fb562a9ea478af3b491ea3dbf | refs/heads/master | 2020-04-09T05:34:47.125166 | 2019-01-08T22:27:38 | 2019-01-08T22:27:38 | 160,070,477 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 176 | r | global.R | # Loads the Shiny and leaflet libraries.
library(shiny)
library(leaflet)
# read the file
crime <- read.csv("Crime_Incidents_in_2017.csv", header=TRUE, stringsAsFactors=FALSE)
|
454171e81e81572a674a73c598c3afae8023ed09 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/spatstat/examples/psp.Rd.R | 442cd19f4aa519adec95502c90448f3aaedc4bc5 | [] | 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 | 335 | r | psp.Rd.R | library(spatstat)
### Name: psp
### Title: Create a Line Segment Pattern
### Aliases: psp
### Keywords: spatial datagen
### ** Examples
X <- psp(runif(10), runif(10), runif(10), runif(10), window=owin())
m <- data.frame(A=1:10, B=letters[1:10])
X <- psp(runif(10), runif(10), runif(10), runif(10), window=owin(... |
78d2e13238bc3fa5bd4ca33e0071649bab178659 | ddfd5c580e291f215eec57f18b43f37d9a017a10 | /code/plot2.R | 1601551468603151d22438a4476db6057a714629 | [] | no_license | yvgg/ExData_Plotting1 | 9eda40f4bd43cdee09a1a32e111653314f7af97d | e21975814252b977976d0b44e26198edbf8230ad | refs/heads/master | 2021-01-14T08:40:04.901157 | 2014-11-06T11:57:56 | 2014-11-06T11:57:56 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 119 | r | plot2.R | png(file = 'plot2.png')
plot(Datetime, Global_active_power, type="l", ylab='Global Active Power (Kilowatts)')
dev.off() |
3387e4073e769b230c4a4caf941f26cd0740334f | 75a6e5788f83437f1e3ea7eda1dc2bc452368b40 | /plot4.R | 484cacbb19c7b8e9f8a958e43e5c52a478e3571b | [] | no_license | brbza/ExData_Plotting1 | 4e8c663d1b79b39b8433faed36c0daf8b60dbdfb | cbee4d4c811836830d626190ff645aadef2861fc | refs/heads/master | 2021-01-18T08:56:48.839264 | 2015-01-11T01:42:39 | 2015-01-11T01:42:39 | 28,917,489 | 0 | 0 | null | 2015-01-07T14:19:08 | 2015-01-07T14:19:08 | null | UTF-8 | R | false | false | 2,512 | r | plot4.R | # Author: Carlos Barboza
# Date: 2015-01-10
# Coursera Exploratory Data Analysis Course, JHS
#
# This scripts creates plot4.png (4 graphs on the same graph device).
#
# It looks for the filtered set of measurements (filtered_power_consumption.csv) on the working directory.
# If the file is not found, it calls the fil... |
7908b2b3582cb80f136bbf0a71875187baec97dd | 2d17ffe9f953d3fe02c91406491e0ed0a00427da | /requirements.R | d48fed4d0e439d122c41851ca4bbe7b26751a3f2 | [
"Apache-2.0"
] | permissive | magnusnissel/pumpR | 3ac7ae6048c441829722b8f1c89bcb26d42672ac | eea98410985b83edb5cc0642963328e109ec1175 | refs/heads/master | 2023-02-13T17:11:59.752463 | 2021-01-13T20:30:13 | 2021-01-13T20:30:13 | 80,954,928 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 197 | r | requirements.R | install.packages("readr")
install.packages("dplyr")
install.packages("purrr")
install.packages("lubridate")
install.packages("ggplot2")
installed.packages("ggthemes")
installed.packages("bookdown") |
3350748cc98b0f8562e4d108ccdbee7e4322e184 | fc8b4f69821d433a3a5976a6b772dfb38eae31bd | /man/hrdiweibull.Rd | 1ae70adb5743b9b4c687978c0c624a59bcf140eb | [] | no_license | cran/DiscreteInverseWeibull | 73ee734dc9b5b4653f68fa7b571bb6d3faa14f96 | d43d2c6765383f73a90e75c762c0be131b8d61ac | refs/heads/master | 2021-01-18T21:46:15.030737 | 2016-05-01T00:44:40 | 2016-05-01T00:44:40 | 17,678,830 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 706 | rd | hrdiweibull.Rd | \name{hrdiweibull}
\alias{hrdiweibull}
\title{
Hazard rate function
}
\description{
Hazard rate function for the discrete inverse Weibull distribution
}
\usage{
hrdiweibull(x, q, beta)
}
\arguments{
\item{x}{
a vector of values
}
\item{q}{
the value of the \eqn{q} parameter
}
\item{beta}{
the v... |
8b62dd67fdc831fc4df8ab2f8c17a5ce8559c1fa | 3fa4ab911dd36a07456263dda7b94542a898fa5c | /code/plot_series.R | 63c26cbe7465578312d7610ef30e82bed3f86453 | [
"MIT"
] | permissive | ridwan608/conteStreamTemperature_northeast | 0f5351227078015fe19530fe9e6e477594259c4c | 92df915cb263e0aab6afffa51fb2fd6fbb0e8709 | refs/heads/master | 2023-03-17T03:17:20.263863 | 2018-07-25T15:34:23 | 2018-07-25T15:34:23 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 595 | r | plot_series.R |
load(file = paste0(output_file4, "/data_dir.RData"))
df_south <- df_values %>%
dplyr::filter(latitude < 40.7127)
if(!file.exists(file.path(getwd(), data_dir, "plots"))) dir.create(file.path(getwd(), data_dir, "plots"))
series <- unique(df_south$series_id)
for(i in series) {
ggplot(df_south[which(df_south$series... |
5f156bdd0da02fd4b8058c983d0731c436244f48 | 96c504984740d50f9d2446103bc5c560ec7b0271 | /man/color.shape.Rd | 0ca3a45f464a56975e9ae3bee545359dfccf4e59 | [] | no_license | ash129/penrose | 0f5adfa05d18fba913b592d355e688d8bd409bca | c59716d2ae344f9a9612030ffc590852395b8ce1 | refs/heads/master | 2021-07-01T00:20:25.150513 | 2017-09-19T19:34:15 | 2017-09-19T19:34:15 | 104,007,536 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 786 | rd | color.shape.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/color.shape.R
\name{color.shape}
\alias{color.shape}
\title{Give the hex color to a shape based on hsv coordinates and additional rules}
\usage{
color.shape(ang, s = 1, v = 1, rot = 0, type = "kite")
}
\arguments{
\item{ang}{numeric angle in ... |
a387e055eb02c41b7a1f464c45ca7b7044e9b060 | 49d331fb01b73b043959793a66c03d1713d8f4db | /UPDATED_CODE/run_simulations_main/run_all.R | 8dce334719766b84b3dd3fd4b3921a9f1cf59d3b | [] | no_license | ruslana-tymchyk/masters-diss | 31287ff61631c4fb2726474a48c6ca3adc47447f | bec892c6e335748dedfaf0bcb69196d6b270b16d | refs/heads/master | 2022-11-05T03:49:14.047210 | 2022-10-24T10:32:22 | 2022-10-24T10:32:22 | 258,590,418 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,485 | r | run_all.R | #From this file you can run any simulation
#Import all simulation files
wd <- getwd()
setwd(wd)
setwd("../logistic")
source("logistic_main.R")
setwd("../multivariate_ddm")
source("mvt_main.R")
setwd("../univariate_ddm")
source("uni_main.R")
#-----------------------------------------------------------------------------... |
d9806018f348f70abc8f4cc678d623d33b23abc6 | 753e3ba2b9c0cf41ed6fc6fb1c6d583af7b017ed | /service/paws.lexmodelbuildingservice/man/delete_bot_version.Rd | 70118d607949a7bd8a3e861294ab510b3ab8d6f0 | [
"Apache-2.0"
] | permissive | CR-Mercado/paws | 9b3902370f752fe84d818c1cda9f4344d9e06a48 | cabc7c3ab02a7a75fe1ac91f6fa256ce13d14983 | refs/heads/master | 2020-04-24T06:52:44.839393 | 2019-02-17T18:18:20 | 2019-02-17T18:18:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 825 | rd | delete_bot_version.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/paws.lexmodelbuildingservice_operations.R
\name{delete_bot_version}
\alias{delete_bot_version}
\title{Deletes a specific version of a bot}
\usage{
delete_bot_version(name, version)
}
\arguments{
\item{name}{[required] The name of the bot.}
\... |
4836b79f4b4c7d0dc28b48aa23bb043aba6b8433 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/ecolottery/examples/coalesc_abc.Rd.R | 4eb231442c2e134b2d8ea763d725b1c4f65acd19 | [] | 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 | 3,474 | r | coalesc_abc.Rd.R | library(ecolottery)
### Name: coalesc_abc
### Title: Estimation of neutral and non-neutral parameters of community
### assembly using Approximate Bayesian Computation (ABC)
### Aliases: coalesc_abc do.simul
### Keywords: coalescent Approximate Bayesian Computation niche-based
### dynamics neutral dynamics
### **... |
7c159c2c36f686ed72a26293af966815b754dd20 | 27d846ed2b771abbd715e2f7e580e416f0b45f06 | /plot1.r | 976149b4e2dd9c02a03d07e68b6c8a9fe2533fd7 | [] | no_license | mikeaadd/ExData_Plotting1 | 9b0e2473842521755a5910f078b97efb9fa108ac | f9ff5812f2845ffc6eab0a2e3bd018a1c800c011 | refs/heads/master | 2021-01-18T01:56:30.187377 | 2015-06-08T13:59:51 | 2015-06-08T13:59:51 | 37,032,492 | 0 | 0 | null | 2015-06-07T21:13:10 | 2015-06-07T21:13:10 | null | UTF-8 | R | false | false | 553 | r | plot1.r | library(dplyr)
#find and clean table
setwd("/Users/josephaddonisio/Downloads/Cousera")
filepath <- "./Exploratory Data Analysis/household_power_consumption.txt"
dataset <- read.table(filepath, header=TRUE, sep=";", stringsAsFactors=FALSE, dec=".")
newdataset<-filter(dataset,Date == "1/2/2007" | Date =="2/2/2007")
#de... |
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