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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
942408e8523efac2bddeded625627b12905d892e | 4c322322ea511b384eb9b60dac00507db04051d6 | /R/asciiDefault.r | fbd05f086a2372a401fb39fb5976c241010a8003 | [] | no_license | oganm/ascii | cb48c9e8f20c8486ea9beadd222d3bf9dceadfc7 | 3a940b383ed8315e4a62bec0dcd61d0b1946d03a | refs/heads/master | 2020-06-23T17:01:19.629427 | 2019-07-24T18:25:33 | 2019-07-24T18:25:33 | 198,688,895 | 0 | 1 | null | 2019-07-24T18:24:21 | 2019-07-24T18:24:20 | null | UTF-8 | R | false | false | 9,893 | r | asciiDefault.r | ##' @param x An R object of class found among
##' \code{methods(ascii)}. If \code{x} is a list, it should be a list
##' of character strings (it will produce a bulleted list output by
##' default).
##' @param include.rownames logical. If \code{TRUE} the rows names are printed.
##' Default value depends of class of \c... |
f293e6095909bb1b308a21ab8723554ea6c0dfe6 | 433b00198e92e756a37441b82727cfb1e9a6436a | /Acc_Calibration_Mongoose_Behavior_2022.R | 97d0732bcc7ecffde94da53c1cbc49d1399b9f00 | [] | no_license | pvandevuurst/Accelerometer_Callibration_Mongoose_Behavior | 05a7cf9a270b54cce8a8228d9b09f877a05936fd | b3e63efc2cbb897acda22a77605d0ec98bff4057 | refs/heads/main | 2023-04-07T11:57:38.581141 | 2023-03-24T16:11:21 | 2023-03-24T16:11:21 | 478,636,409 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,369 | r | Acc_Calibration_Mongoose_Behavior_2022.R | #Begin by setting a working directory (i.e., file where all your data is stored)
setwd("C:/Users/paige/Desktop/Data/Accele_Data_AlexLab")
#install.packages(c("pracma", "rgl"))
#install.packages("rgl")
#install the library for these packages in your session
library (pracma)
library (rgl)
library(ggplot2)
lib... |
78203e04c1e57eae2a63b0b8cc2e65c76493e8f8 | 3ea006d26ec3b8944c7651c1960780d8fa0d5cbd | /aijContext.R | 9a16b3d80f20ea2a88b59384a2297cf1ab1df353 | [] | no_license | Dordt-Statistics-Research/Bacterial-Code | d192d90aedbf2be72e55e87568b7e8823c76da33 | 5b3e3859162f176142e84119fe4070c4a9a5326b | refs/heads/master | 2021-01-12T17:49:36.793510 | 2019-07-25T15:21:06 | 2019-07-25T15:21:06 | 69,396,077 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 28,886 | r | aijContext.R | # Methods for aijContexts
# Gives a vector of gene names; the same as the rownames of the expression data, and guaranteed to be in the same order
get.genenames <- function(context) UseMethod("get.genenames")
# Gives a vector of experiment names; the same as the colnames of the expression data, and guaranteed to ... |
e36991260431ccb4db828f3d07d3fa133119a436 | 5bdbd3096980e1f151469c38e04ddaa83ec95df2 | /Methylation/Methylation_Test.R | 4435bf49951cbaa0c59d3c674ed7e5d95babe2bc | [] | no_license | jshkrob/BDSI-Project | 757f489c7a175fd493cda6914265abe3fd3959e7 | 97f294b0cf59076135cae480eff17fe11dd5fe81 | refs/heads/master | 2020-07-21T09:38:57.586421 | 2019-09-06T23:23:34 | 2019-09-06T23:23:34 | 206,818,780 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 37,800 | r | Methylation_Test.R | # packages:
library(tidyverse)
library(caret)
library(rpart)
library(randomForest)
library(naivebayes)
library(MASS)
library(glmnet)
library(caret)
library(rrlda)
library("class")
# loading data
screening <- readRDS("C:/Users/yasha/Desktop/BDSI/Data Mining/screening.rds")
meth <- readRDS("C:/Users/yasha/Desktop/BDSI/D... |
01dce348ee0ed41da40077d97966feb1902409a8 | e86bc0e7c2bd9c07f44c31f7482d4bcbc7205382 | /plot2.R | 4648658f37b1dec110754e68b17679ca26f475dd | [] | no_license | jgoetsc2/Course-Project-1 | 2662d72ee79faa1e58febfb4490f8d4d47f21892 | 9c06f36d94ef69038fb4159d34ceb8b5b90b9966 | refs/heads/master | 2023-01-15T15:36:55.538077 | 2020-11-18T20:17:46 | 2020-11-18T20:17:46 | 314,005,026 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,124 | r | plot2.R |
library(dplyr)
# filename <- "EPC.txt"
# url<-"https://d396qusza40orc.cloudfront.net/exdata%2Fdata%2Fhousehold_power_consumption.zip"
# f <- file.path(getwd(), filename)
# download.file(url, f)
# unzip(filename)
EPC <- read.table('household_power_consumption.txt',header = TRUE,sep = ";",na.strings = "?")
#Format date... |
11e324fd7e1fdb665b4a2260a23d658478e676a5 | 443b37ea9377bfd267f68c20123893a85db17852 | /R/parse_metadata.R | ab1efe1a32edf632e63781bb0f87ed530a565d2b | [] | no_license | CharlesJB/rnaseq | 7cda74303ebceaf9f8561ce5f331c35f034793d6 | 77352def1a5a2b0e0b7e6400ad13bd7385de0181 | refs/heads/master | 2023-04-02T13:03:09.120128 | 2023-03-15T20:12:24 | 2023-03-15T20:12:24 | 125,427,062 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 21,120 | r | parse_metadata.R | #' Parse metadata LO
#'
#' Parse metadata and generate a draft for pca_info, volcano_info, report_info
#' files.
#'
#' @param metadata (dataframe)
#' @param pca_subset (character) column of metadata, filter for automated PCA (ex.: Cell type)
#' @param pca_batch_metadata (character) extra columns for pca coloring (biolo... |
07261baec98a9f791d1e67fb51d1d4d95fe55a33 | 77851606fdf0be274530bb10d160b130baa6b0bf | /15th May Factors.R | 2216ce3003ee3b3589eff2f17db77eac2657970e | [] | no_license | VerdeNotte/EstioTraining | 04c689b0f36e66a9180c461d6dc8297d3c017118 | a2d4b439373d82815e5eb7a584ed242aa26ff2d2 | refs/heads/master | 2020-05-24T00:48:27.342637 | 2019-07-02T09:52:43 | 2019-07-02T09:52:43 | 187,023,330 | 0 | 0 | null | 2019-05-20T13:25:50 | 2019-05-16T12:27:10 | R | UTF-8 | R | false | false | 704 | r | 15th May Factors.R | DataEstio <- factor (c("Richard", "Sue", "Katy", "Liz","Tom"),
labels = c("Richard", "Sue", "Katy", "Liz","Tom"), ordered = F)
#Drop down menu, second bit is telling us the option
View (DataEstio)
#Look at the data
#All we want to do is add in another level but there's... |
59b682260702b13cbffe6c9b98073379f33751c7 | e1ab103f11b794e4e3bcd0cb23f5bcc346b4780d | /man/parsimony_Crossover.Rd | 29e7d64f64ac975734bb0d7673dc3e8e51ccfbed | [] | no_license | jpison/GAparsimony | cd2145efabdab63e419bb49226d60050bfed202b | cdaad1e009b11481e3cd1619467e65122fcd0557 | refs/heads/master | 2023-04-12T16:35:21.304719 | 2023-04-07T09:48:48 | 2023-04-07T09:48:48 | 90,851,451 | 4 | 3 | null | null | null | null | UTF-8 | R | false | false | 2,016 | rd | parsimony_Crossover.Rd | \name{parsimony_crossover}
\alias{parsimony_Crossover}
%
\alias{parsimony_crossover}
\title{Crossover operators in GA-PARSIMONY}
\description{Functions implementing particular crossover genetic operator for GA-PARSIMONY. Method uses for model parameters Heuristic Blending and random swapping for binary selected featu... |
7c6dce086cfa6dc94e572f241cd09f7f81e08379 | f8509a0de4c57931f644a10bec3b783dc21722da | /analysis/archive/ggw-mod2_ALL_inprogress.R | c07ab4dd273353d9bdb3ce20aa0baa6d8ad3ee78 | [] | no_license | kgweisman/ggw-mod2 | ee30ef8315ad7e3f501f696dec808baa832f79d0 | acb87bd0e7f271e9f5f0cb34f1bab9f8c17f5614 | refs/heads/master | 2020-04-15T14:28:50.292381 | 2017-10-03T01:09:50 | 2017-10-03T01:09:50 | 48,076,480 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 28,622 | r | ggw-mod2_ALL_inprogress.R | #################################################### WORKSPACE SETUP ###########
# set up workspace -------------------------------------------------------------
# load libraries
library(devtools)
library(psych)
library(stats)
library(nFactors)
library(ggplot2)
library(knitr)
library(tidyr)
library(dplyr)
# clear wo... |
8ff0eb13fadf91a978e299a774320237556d9e05 | 6c5bd91e0383af2a4134a07e121a3ea6ed2119af | /man/shattered.regions.cnv.Rd | 0730ed0f56c4e5f84dd20917d6e4adb8aaa784c6 | [] | no_license | cansavvy/svcnvplus | d41f3503c42f400acb0e606d7ece209d8d01132f | ea43a5dbd7ae38f1b26520a31af1daddadbaf5dd | refs/heads/master | 2020-12-04T04:21:20.444872 | 2019-12-16T19:42:28 | 2019-12-16T19:42:28 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,580 | rd | shattered.regions.cnv.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/shattered.regions.cnv.r
\name{shattered.regions.cnv}
\alias{shattered.regions.cnv}
\title{Caller for shattered genomic regions based on breakpoint densities}
\usage{
shattered.regions.cnv(
seg,
fc.pct = 0.2,
min.seg.size = 0,
min.num.... |
075d6bbe755e88785d2f4dfa94acd860fe380d77 | acb2b3bebdbcb1d3e686d51b87c100353dc4a54f | /R/plotlis_somtc.R | 802f90a348df347a6fdfb74601f800e96a9edcba | [] | no_license | wangdata/soyface_daycent | ce5b3ce38d7abc0cb0898941de85ada1441b5cf2 | 21f459cbbf7b5f2c002940eb1ba6c1bf5e616f47 | refs/heads/master | 2023-07-21T06:51:08.221378 | 2018-06-01T06:51:27 | 2018-06-01T06:51:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,593 | r | plotlis_somtc.R | #!/usr/bin/env Rscript
# A specialized variant of plotlis.R, created mostly to present annual values instead of monthly fluctuations for the publication version of total SOM C predictions.
library(ggplot2)
library(grid)
library(dplyr)
library(ggplotTicks)
library(DeLuciatoR)
# If argv exists already, we're being sou... |
13705f3def92f2bf9abe40fadc3c960674c81485 | 8f7320c10f2c5fc8475753dc5256d1a66067e15c | /rkeops/man/extract.Rd | 964aa445e59e3eeae94771d4a2f0361c52a8717c | [
"MIT"
] | permissive | getkeops/keops | 947a5409710379893c6c7a46d0a256133a6d8aff | 52ed22a7fbbcf4bd02dbdf5dc2b00bf79cceddf5 | refs/heads/main | 2023-08-25T12:44:22.092925 | 2023-08-09T13:33:58 | 2023-08-09T13:33:58 | 182,054,091 | 910 | 69 | MIT | 2023-09-03T20:35:44 | 2019-04-18T09:04:07 | Python | UTF-8 | R | false | true | 2,269 | rd | extract.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/lazytensor_operations.R
\name{extract}
\alias{extract}
\title{Extract.}
\usage{
extract(x, m, d)
}
\arguments{
\item{x}{A \code{LazyTensor} or a \code{ComplexLazyTensor}.}
\item{m}{An \code{integer} corresponding to the starting index.}
\it... |
17d6a3fda732624fa3246a0d8341fe0864802984 | 897425b5ca880e106aae6483c2967a4e4540b81c | /deseq2/test.R | 16679d0e81d5e6262aa867e6eb11bffa56fd93c5 | [] | no_license | MingChen0919/RShinyApps | ff4ab5398a27b500a198342cfcf59d225c3cef4c | 74026c2a8f2a4f8a83d384d7fd361e440f41e6f5 | refs/heads/master | 2020-05-21T08:06:36.635508 | 2018-07-12T03:44:29 | 2018-07-12T03:44:29 | 84,600,724 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,351 | r | test.R | library(DESeq2)
library("pasilla")
pasCts <- system.file("extdata", "pasilla_gene_counts.tsv",
package="pasilla", mustWork=TRUE)
# pasAnno <- system.file("extdata", "pasilla_sample_annotation.csv",
# package="pasilla", mustWork=TRUE)
countData <- as.matrix(read.csv(pasCts,se... |
40b77779469bfde10da199d6428879104c9ea223 | 95754178320398752703338517402d7cbf1781b9 | /KCompetition_GettingStarted.R | 336331a860cbf1e6e67a1d6dd0960a2653e04c6a | [] | no_license | emredjan/15.071x_Voting_Outcomes | 8566156dac5ec8469707db030084396ced577ea8 | 1cf65273868420ee2d12f2a7d6d139508a1d0508 | refs/heads/master | 2021-01-09T20:41:18.127917 | 2016-06-14T17:56:33 | 2016-06-14T17:56:33 | 61,073,681 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,568 | r | KCompetition_GettingStarted.R | # KAGGLE COMPETITION - GETTING STARTED
# This script file is intended to help you get started on the Kaggle platform, and to show you how to make a submission to the competition.
# Let's start by reading the data into R
# Make sure you have downloaded these files from the Kaggle website, and have navigated to the di... |
d08238aace42279afce8dc11dcb6a7d0b14b1373 | 57ad5699cd427042bbf93ae9cd7d54af39788f73 | /R/prox.isotonic.R | 5d864a457e402dd2b627c8fa1d388a59132edc84 | [] | no_license | AlePasquini/apg | 94f9eef7f233d721c663a4956581963d04d537df | 8900984a8e7b1a469d2b775d56bf07bd192e252b | refs/heads/master | 2020-04-12T04:44:58.238828 | 2016-06-04T01:44:00 | 2016-06-04T01:44:00 | 162,304,614 | 3 | 0 | null | 2018-12-18T14:59:41 | 2018-12-18T14:59:41 | null | UTF-8 | R | false | false | 453 | r | prox.isotonic.R | #' Proximal operator of the isotonic constraint
#'
#' Computes the proximal operator of the isotonic constraint, i.e., the
#' projection onto the set of nondecreasing vectors.
#'
#' @param x The input vector
#'
#' @return The projection of \code{x} onto the set of nondecreasing vectors,
#' obtained by solving an isot... |
2d509d14fdc2b510a0cf43cf8b7e94c006d72a4a | e5dcc8a6a80a5785d98ff7be57de24aa9690d982 | /learning_function.R | 15ea97997ffad5265f4b2d8fad7ecb574934355e | [] | no_license | lja9702/No_namedTeam | 182c13fe41569e79a50b1602b0e83adc4ccb947d | 71387a10fb93cf5daea4f7e421d79eef1127df9f | refs/heads/master | 2020-03-24T04:16:26.415124 | 2018-08-23T14:03:10 | 2018-08-23T14:03:10 | 142,450,049 | 0 | 0 | null | 2018-08-01T14:42:04 | 2018-07-26T14:10:13 | R | UTF-8 | R | false | false | 22,069 | r | learning_function.R |
source("./setup_lib.R", encoding="utf-8")
source("./make_x.R", encoding="utf-8")
##########################################################################################함수등록
# 주야
# day_night(path, 0.01, 30, 20, round, 2000)
day_night <- function(path, learning_rate, out_node, hidden_node, round, seed)
{
file <- ... |
ffa908219427441d590b76580cfcbca07c76d803 | 7a3e07ba0e54293cd2e06bdce8d4d9f497a07b10 | /code/make_1h_stripchart.R | 0af70ae7f27fa186d6de953ba085ef563bebb38e | [] | no_license | BAAQMD/SFBA-COVID-air-quality | 9742ebd76f6261eb8378ae998fd227921be8a606 | 46e395646c62a0db5afd42e3d5da4726fa78127e | refs/heads/master | 2022-07-16T13:34:58.552026 | 2020-05-18T18:42:52 | 2020-05-18T18:42:52 | 263,976,229 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,071 | r | make_1h_stripchart.R | source(here::here("code", "chart-helpers.R"))
source(here::here("code", "tidy_1h_data.R"))
source(here::here("code", "with_epoch.R"))
make_1h_stripchart <- function (
input_data,
value_var,
value_limits,
...
) {
chart_data <-
input_data %>%
tidy_1h_data(
value_vars = value_var,
na.rm =... |
bf40a9d0b7f42e5dce11294065b3157a8fea412b | 309ae3e447336af016b6df7b3b34845280e4fe9d | /eric.R | e045d3e9f09a64b83698345d76d6667b1e795043 | [] | no_license | Vexeff/family-cohort | 91322bd09af94d2979b6e9f6d8df4cdd283855a7 | e2282bffcd7ca7578b043e1b40a56f468ef58e03 | refs/heads/master | 2022-09-27T09:18:13.713717 | 2018-11-11T18:28:01 | 2018-11-11T18:28:01 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 59 | r | eric.R | # HI MY NAME IS ERIC
# THIS IS MY FIRST R SCRIPT
3 + 4
|
549b6ed9c444207aa296eb985217e8e4cb37cafd | ff6b811e0e352859468cb0e2098b88024fcfc630 | /ProgrammingAssignment1/corr.R | efba5606ce2bff00607fc0620548bf1e2b20ce47 | [] | no_license | sagospe/R-Programming | 99f8eede50bbb616abe5133e1933df43a4aa812e | 6321eac74e04286b5bfaee5384ba8ef87e7393d9 | refs/heads/master | 2021-01-11T01:04:21.796582 | 2016-10-13T21:00:44 | 2016-10-13T21:00:44 | 69,615,226 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 971 | r | corr.R | corr <- function(directory, threshold = 0) {
## 'directory' is a character vector of length 1 indicating
## the location of the CSV files
## 'threshold' is a numeric vector of length 1 indicating the
## number of completely observed observations (on all
## variables) r... |
db50c8d290175dd6f2af06644bebb628dfdfe5ba | 7469bb7562c649c9799202ac5be0e0857d05a506 | /man/PlotFreq.Rd | c0f1c99c38f9113fa759c5007f09ef50c4f68fd7 | [] | no_license | gilles-guillot/Geneland | 8798447ec1936a26a86d5be24fe9ec4668935ba8 | 8e5873cc130ef5874c98b1d5766f54230e4c547a | refs/heads/master | 2021-06-03T16:18:25.611534 | 2020-02-20T11:57:35 | 2020-02-20T11:57:35 | 234,557,841 | 6 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,033 | rd | PlotFreq.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/PlotFreq.R
\name{PlotFreq}
\alias{PlotFreq}
\title{PlotFreq}
\usage{
PlotFreq(path.mcmc,ipop,iloc,iall,printit=FALSE,path)
@param path.mcmc Path to output files directory
@param ipop Integer number : index of population
@param iloc Integ... |
773cfbda110a61121ba7ddf651984716cb5eecf0 | 27003deb72c65e565c084d1f077db8a6c04b0e45 | /ferramentas_paraRevisar/log2_transf.r | 179d479f431f0ca45a7ea684cf2c809777d629a7 | [] | no_license | LABIS-SYS/GALAXY_OLD | 57e46436ed16daf747be1a90477d177c4f87be1d | 7315e239c198117ac126b0ab15e0afad9e542b34 | refs/heads/master | 2021-05-15T11:21:59.498310 | 2017-10-25T19:36:30 | 2017-10-25T19:36:30 | 108,316,021 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,116 | r | log2_transf.r | #!/usr/bin/Rscript
# Import some required libraries
library('getopt');
library('scatterplot3d');
# Make an option specification, with the following arguments:
# 1. long flag
# 2. short flag
# 3. argument type: 0: No argument, 1: required, 2: optional
# 4. target data type
option_specification = matrix(c(
'infilenam... |
067a38282256eeaa04d725c932edc8fb9f3df402 | 998bdef38eeb195434b444c275eb875932304019 | /dec11 index testing dataset.R | e0ad02917bc037b0247b5fd9b7bf9c8a0709e01a | [] | no_license | shazadahmed10/code | 35a4697bd5824c0e21c866c89271766cb319ad4e | ef8b488cd05547be1b951147254bfedd5f53b2ad | refs/heads/master | 2021-11-24T17:46:32.661522 | 2021-10-29T21:20:45 | 2021-10-29T21:20:45 | 123,955,897 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,723 | r | dec11 index testing dataset.R | library ("tidyverse")
library ("openxlsx")
master <- read_tsv ("C:/Users/lqa9/Desktop/19Q4/Clean/MER_Structured_Datasets_PSNU_IM_FY17-20_20191220_v2_2.txt")
master2 <- master %>%
select(-c(region, regionuid, operatingunituid, countryname, mech_code, mech_name, pre_rgnlztn_hq_mech_code,
prime_partn... |
1000c4f1397c16c31d1da9789f48ab17591cdd88 | 3f41dcde4498fcf47a5f8314de6086ffec3dd082 | /man/makeplot.pseudo.ess.Rd | 77f8c8ee66a802775aad51201bee11749a74e93e | [] | no_license | arborworkflows/RWTY | 6f961f76b69776d9c752be0483416dec7448661b | fbf5b695a1c8d16f7532123fb86715152f430b06 | refs/heads/master | 2020-12-31T02:01:50.609590 | 2016-08-17T22:16:18 | 2016-08-17T22:16:18 | 65,751,392 | 0 | 1 | null | 2016-08-15T17:31:51 | 2016-08-15T17:31:51 | null | UTF-8 | R | false | true | 1,417 | rd | makeplot.pseudo.ess.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/makeplot.pseudo.ess.R
\name{makeplot.pseudo.ess}
\alias{makeplot.pseudo.ess}
\title{Plot the pseudo ESS of tree topologies from MCMC chains.}
\usage{
makeplot.pseudo.ess(chains, burnin = 0, n = 20)
}
\arguments{
\item{chains}{A list of rwty.t... |
2e91835be7d6262a70b348bcc661fe7e3c06d77a | 77572ab0628f675213204e505599a068375da215 | /R/germline_gwas_server.R | 86e5cc6dc3ab3dbf5a583bb36fafeb331808996e | [
"MIT"
] | permissive | CRI-iAtlas/iatlas-app | a61d408e504b00126796b9b18132462c5da28355 | 500c31d11dd60110ca70bdc019b599286f695ed5 | refs/heads/staging | 2023-08-23T11:09:16.183823 | 2023-03-20T21:57:41 | 2023-03-20T21:57:41 | 236,083,844 | 10 | 3 | NOASSERTION | 2023-03-21T21:27:26 | 2020-01-24T21:07:54 | R | UTF-8 | R | false | false | 8,793 | r | germline_gwas_server.R | germline_gwas_server <- function(id, cohort_obj){
shiny::moduleServer(
id,
function(input, output, session) {
ns <- session$ns
if(!dir.exists("tracks"))
dir.create("tracks")
addResourcePath("tracks", "tracks")
gwas_data <- reactive({
iatlasGraphQLClient::query_germli... |
58847032386e54a0075e0beefc27899384724ed7 | f9f9476e77b025583654ab42f0f0e5611f598a75 | /Capstone Project/step6_packagedata.R | c192b8c62e7b420bd57cbc0f1b5d0369a4990a3d | [] | no_license | rsizem2/jhu-data-science | a56d1467f1d6cac1d000e3fcace99e68c105d08a | 4ad9a319ed83d0f8c607ac63f05499102d865075 | refs/heads/master | 2023-01-03T03:04:25.929474 | 2020-10-21T18:38:07 | 2020-10-21T18:38:07 | 275,019,731 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,060 | r | step6_packagedata.R |
# Load Libraries
library(tidytext)
library(tidyr)
library(data.table)
library(dplyr)
library(dtplyr)
## Set project directories
main_directory <- "~/textpredict/"
#main_directory <- dirname(rstudioapi::getSourceEditorContext()$path)
loaddir <- paste(main_directory, "scores/", sep = "")
savedir <- paste(main_director... |
7b0e92285277cc84a93b5bcb235052274b60c2f9 | 577bfd9610409231e81e090a73d11f7b9c4f07cb | /NMFP/Example1/Simplesimulation.R | 56fbcb6aa93b662bc5e2ee841c26a9528e85b537 | [] | no_license | Elric2718/NMFP | b6c7376bb0b3ca435816e684d651853936f8d992 | c7657a31690ec85a25adc490078fd2804fd4306d | refs/heads/master | 2021-06-04T21:04:51.814880 | 2016-09-04T23:03:12 | 2016-09-04T23:03:12 | 64,001,623 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 7,058 | r | Simplesimulation.R | ###############################################################################
######################### NMFP for lowly expressed gene #######################
###############################################################################
###### load package
library(dplyr)
library(compiler)
library(data.table)
library... |
6d3c2b653124e640f3719e255873157697fc30c3 | 9aec8515144a368b070875f20f7027ffbaf03563 | /Rtwitter.R | fdee63dc9dfa754431e1361c44f47f5391f021f8 | [] | no_license | AlessandroPTSN/Analizando-minha-conta-com-Rtweet | 497b6a7b7a984b3447f8cdb76a77ea125ae6237f | 83fa112a79089db75c6fa48f2dd24e57d924cdb5 | refs/heads/master | 2020-12-10T20:32:59.378233 | 2020-01-15T20:07:47 | 2020-01-15T20:07:47 | 233,703,595 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,905 | r | Rtwitter.R | library(rtweet)
# Mude consumer_key, consume_secret, access_token, e
# access_secret baseado nas suas propias chaves
token <- create_token(
app = "Hi",
consumer_key = consumer_key,
consumer_secret = consumer_secret,
access_token = access_token,
access_secret = access_secret)
h=get_timeline("... |
3890530c393158d338913ca6916a19c75b0d9396 | 0b56be1b7df75e97165707c90f772f33b0623743 | /peakPantheR/R scripts/Dementia_Urine_PP_RPOS.R | 9195a324cd43a5e3a3dbb8fb2c305011a189561e | [
"MIT"
] | permissive | phenomecentre/metabotyping-dementia-urine | 68d5b7b249b8c8401c0615453d7039c45a1d8ad7 | e3f7be5ab84cec005e8362683d7823f2a22461ac | refs/heads/master | 2023-05-31T03:48:26.204967 | 2021-06-25T12:42:51 | 2021-06-25T12:42:51 | 279,675,819 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 7,741 | r | Dementia_Urine_PP_RPOS.R | ## ---------------------------------------------------------------------------------------------------------------------------------------------
## Dementia cohort - urine - peakPantheR RPOS assay
## -----------------------------------------------------------------------------------... |
ea5010e55e7289ec85b7c972d5a464110ef0690e | 26cd41d81e252b397e4e997773cc3c02574e32d9 | /Spiderman_Review.R | 098af390676b09939b19f63cafd71fa39b728952 | [] | no_license | joeychoi12/R_Crawling | c6420505b2199308f9a9d590c3c3ee709ef0ee0d | e5b4c25ace8a8f5ba4fd12eb8fec4f028bb2cecb | refs/heads/master | 2020-06-14T07:44:30.289482 | 2019-08-13T08:03:57 | 2019-08-13T08:03:57 | 194,950,923 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,538 | r | Spiderman_Review.R | # NAVER 영화('Spiderman') 일반인 리뷰 크롤링
library(rvest)
library(stringr)
library(dplyr)
trim <- function (x) gsub("^\\s+|\\s+$", "", x)
url_base <- 'https://movie.naver.com'
start_url <- "/movie/bi/mi/point.nhn?code=173123#tab"
url <- paste0(url_base,start_url, encoding="euc-kr")
html <- read_html(url)
html %>%
html_node... |
21cf2c33153caad9ea568ae1e96078f07d33c6d1 | 8d4dfa8b6c11e319fb44e578f756f0fa6aef4051 | /man/isStrippedACs.Rd | e3797e3c54b56957e56bf22bbe6179b7973f8ae3 | [] | no_license | eahrne/SafeQuant | ce2ace309936b5fc2b076b3daf5d17b3168227db | 01d8e2912864f73606feeea15d01ffe1a4a9812e | refs/heads/master | 2021-06-13T02:10:58.866232 | 2020-04-14T10:01:43 | 2020-04-14T10:01:43 | 4,616,125 | 4 | 4 | null | 2015-11-03T20:12:03 | 2012-06-10T15:35:25 | R | UTF-8 | R | false | true | 564 | rd | isStrippedACs.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/IdentificationAnalysis.R
\name{isStrippedACs}
\alias{isStrippedACs}
\title{Check if ACs are in "non-stripped" uniprot format e.g. "sp|Q8CHJ2|AQP12_MOUSE"}
\usage{
isStrippedACs(acs)
}
\arguments{
\item{acs}{accession numbers}
}
\value{
boolea... |
a7ab2e0aef391b9c38b864297cbef765aa3b161d | 9a4c2b70f32e380ad0df3413b607b73117ff4fcd | /man/rescaleVariance.Rd | 795789f559c5be4531bb0ae0086feff5d6a565d3 | [] | no_license | DPCscience/PhenotypeSimulator | 717d617eab3d5feb541152fe7547b908f0fed51b | 79df7d1c2d29296c4636fac24746926249dc4972 | refs/heads/master | 2021-01-20T12:29:22.459120 | 2017-08-05T16:29:28 | 2017-08-05T16:29:28 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 818 | rd | rescaleVariance.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/createphenotypeFunctions.R
\name{rescaleVariance}
\alias{rescaleVariance}
\title{Scale phenotype component.}
\usage{
rescaleVariance(component, propvar)
}
\arguments{
\item{component}{numeric [N x P] phenotype matrix where N are the number of... |
fe78dd013fc7d9ec80fbdc53ccb762eef6c9bf3f | 6923f79f1eaaba0ab28b25337ba6cb56be97d32d | /Gelman_BDA_ARM/arm/3.1.R | d0bb9e195e0eee00157760338ba1027ecb934988 | [] | no_license | burakbayramli/books | 9fe7ba0cabf06e113eb125d62fe16d4946f4a4f0 | 5e9a0e03aa7ddf5e5ddf89943ccc68d94b539e95 | refs/heads/master | 2023-08-17T05:31:08.885134 | 2023-08-14T10:05:37 | 2023-08-14T10:05:37 | 72,460,321 | 223 | 174 | null | 2022-10-24T12:15:06 | 2016-10-31T17:24:00 | Jupyter Notebook | UTF-8 | R | false | false | 280 | r | 3.1.R |
library ("foreign")
iq.data <- read.dta ("../doc/gelman/ARM_Data/child.iq/kidiq.dta")
attach(iq.data)
fit.2 <- lm (kid_score ~ mom_hs )
print (fit.2)
fit.3 <- lm (kid_score ~ mom_hs + mom_iq)
print (fit.3)
fit.4 <- lm (kid_score ~ mom_hs + mom_iq + mom_hs*mom_iq)
print (fit.4)
|
478289896261fa5e439766ef8e1a7e7e9ae6e498 | c9865b8080591efce5b3844bb2d915dc692ce7e5 | /Classification and Regression models.r | 2d751e258ecadff3969931c34161fc6d03cb7353 | [] | no_license | tydra33/Artificial_Intelligence-R_Project | 727f7a327e8947d61eaf02e2b2aec7d941859845 | 7237c8dd6bfff47f57adc7d0e4848423af8232e7 | refs/heads/main | 2023-05-12T19:18:07.291036 | 2021-06-02T20:33:52 | 2021-06-02T20:33:52 | 350,842,019 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 11,374 | r | Classification and Regression models.r | #So we are building classification model based on the variable "Poraba"
modelEval <- function( data, formula, modelFun, evalFun, fType, modelType,
toPrune=F) {
localTrain <- rep(F, times = nrow(goodInfo))
outPut <- vector()
for(i in 1:11) {
cat("ITERATION: ", i, "\n")
flus... |
fb00d915113818573db1aca160f76b9ccf62f3e8 | edf7137cb8ddcb0df058fed72a267459baa75c30 | /Clustering/Dataset2/part3.R | daf38d42268d61058962cd265f997649c970d3d9 | [] | no_license | pwalawal/DataMining | 8f18f5790df70c48796e34570ab7c8e40241d54b | 3a009705e8508fa7c7892c1a18d0b4f58e5d1c45 | refs/heads/master | 2021-04-26T16:04:37.260657 | 2016-10-21T14:32:47 | 2016-10-21T14:32:47 | 71,570,587 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,771 | r | part3.R | install.packages("ggplot2")
library(ggplot2)
install.packages("gdata")
library(gdata)
install.packages("gplots")
library(gplots)
install.packages("class")
library(class)
install.packages("datasets")
library(datasets)
install.packages("Matrix")
library(Matrix)
install.packages("MatrixModels")
library(MatrixModels)
insta... |
934cff57d723016a92c9a3eb2f4deca9ed9a296b | 0500ba15e741ce1c84bfd397f0f3b43af8cb5ffb | /cran/paws.application.integration/man/swf_deprecate_domain.Rd | b1310ad4aa2da899fddf18b30bb516f73e03d0db | [
"Apache-2.0"
] | permissive | paws-r/paws | 196d42a2b9aca0e551a51ea5e6f34daca739591b | a689da2aee079391e100060524f6b973130f4e40 | refs/heads/main | 2023-08-18T00:33:48.538539 | 2023-08-09T09:31:24 | 2023-08-09T09:31:24 | 154,419,943 | 293 | 45 | NOASSERTION | 2023-09-14T15:31:32 | 2018-10-24T01:28:47 | R | UTF-8 | R | false | true | 808 | rd | swf_deprecate_domain.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/swf_operations.R
\name{swf_deprecate_domain}
\alias{swf_deprecate_domain}
\title{Deprecates the specified domain}
\usage{
swf_deprecate_domain(name)
}
\arguments{
\item{name}{[required] The name of the domain to deprecate.}
}
\description{
De... |
e43f3185be686cacd0116ffa784fc4de44957654 | 99b6b013dbfcff93cca1c7bbee22b7f58eec8dc1 | /setpars-bh-joint.R | b13dbd1ecea14c894ab62be5f24d04c34fe6c79f | [] | no_license | spencerwoody/safab-code | 46c5d25349322740ca6e9380c39d625f85c54036 | be9272456f571617229fd13fdf68c283af637c25 | refs/heads/master | 2021-01-05T23:35:53.965902 | 2020-02-17T17:46:52 | 2020-02-17T17:46:52 | 241,168,420 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 584 | r | setpars-bh-joint.R |
## Number of iterations
nMC <- 1000
# Target FDR
qstar <- 0.2
# confidence level
alpha <- 0.10
p <- 0.2
tau <- sqrt(3)
## Number of subjects
Nj <- 2000
## Number of observations per subject
Ni <- 3
## sigma <- 1 * sqrt(Ni - 1)
sigma <- 1 * sqrt(Ni)
## SD for ybar used for confidence intervals
## sigma_mean <-... |
77c61b6b8c9d555a6656a0a9ea9ee7fdcaa1ef9e | 0575a2c951639cfe77812dd33f8f024898b4a932 | /man/make_labels_directions.Rd | f242426c2e320b033af2b9b499900a952eb91bb4 | [
"MIT"
] | permissive | bayesiandemography/demprep | 8f400672fbbee9d92f852056d4ff7cb31a7fc87a | 3aa270ff261ab13570f3ba261629031d38773713 | refs/heads/master | 2021-12-29T04:00:24.929536 | 2021-12-16T22:15:01 | 2021-12-16T22:15:01 | 204,109,024 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,082 | rd | make_labels_directions.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/make_labels.R
\name{make_labels_directions}
\alias{make_labels_directions}
\title{Make Directions labels}
\usage{
make_labels_directions(x)
}
\arguments{
\item{x}{A character vector.}
}
\value{
A character vector
}
\description{
Make labels w... |
d033e35181ab55fb576768c68ea152df72f397b1 | 432a02b2af0afa93557ee16176e905ca00b653e5 | /Misc/estimate_overlap_bases.R | 17f59c6e9176c5f02a5c8da4c79125e39014794f | [] | no_license | obigriffith/analysis-projects-R | 403d47d61c26f180e3b5073ac4827c70aeb9aa6b | 12452f9fc12c6823823702cd4ec4b1ca0b979672 | refs/heads/master | 2016-09-10T19:03:53.720129 | 2015-01-31T19:45:05 | 2015-01-31T19:45:05 | 25,434,074 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 396 | r | estimate_overlap_bases.R |
estimate_loss=function(n,mean,sd){
data=rnorm(n=n,mean=mean,sd=sd)
data_round=round(data)
data_round_lt200=data_round[data_round<200]
data_round_lt200_min50=data_round_lt200
data_round_lt200_min50[data_round_lt200_min50<50]=50
lost_bases=data_round_lt200_min50-200
perc_lost=((sum(lost_bases)*-1)/(1000000*200))*... |
d788d5474ffadfe7b6649f9333d0d1f5bf1daef4 | 0b72c2e836e7ba8590dd9cfd3f8dd67798c5eedc | /script/update/gwas/log/2015-05-17_UpdateDbgap.r | 649c34889a6cbabf46ebb8f023c91a0fee738a87 | [] | no_license | leipzig/rchive | 1fdc5b2b56009e93778556c5b11442f3dbece42c | 8814456b218137eafe57bfb19adda19c0d0d625b | refs/heads/master | 2020-12-24T12:06:15.051730 | 2015-08-06T11:59:08 | 2015-08-06T11:59:08 | 40,312,197 | 2 | 0 | null | 2015-08-06T15:24:31 | 2015-08-06T15:24:31 | null | UTF-8 | R | false | false | 633 | r | 2015-05-17_UpdateDbgap.r | library(devtools);
install_github("zhezhangsh/rchive");
library(rchive);
cat('Downloading dbGaP analyses\n');
meta<-DownloadDbGap();
cat('Retrieve dbGaP p values\n');
RetrieveDbGapStat(rownames(meta), meta[,'study'], stat.name='p value');
cat('Summarize dbGaP metadata\n');
SummarizeDbGap(meta);
cat('Update log\n');
U... |
516556e5d088b1d3231fabe93091dc74411d5d93 | 75d662fac4958ce9f117465ec6203e6cc3fcbaf7 | /dplyr toy script.R | 1905d748cf9db4332194db5cd9279c3795f1a2c1 | [] | no_license | chrisqiqiu/dplyr_toy | 951af4dca9c26f80c855e77bc646d75607c709e3 | 331cdc74c7569c0b4338ba71a76d4dce5d0ae1bb | refs/heads/master | 2021-05-02T10:35:11.568701 | 2019-01-20T10:30:22 | 2019-01-20T10:30:22 | 120,759,795 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 6,342 | r | dplyr toy script.R | #install.packages('R.utils')
library(R.utils)
library(tidyverse)
#i created a folder called Test in working space just to separate the files from my other files
# create a function to download file from a url and unzip it and read the file into memory, return it as dataframe
loadFile<- function(url) {
file... |
b8d24db34a411a27876ef8f5c401118bb2a23098 | 4b659f6e4f18fd333a446087af1861e8664dbb38 | /man/importance_sampling.Rd | 26726177af94abc7066f65d75f5ff78f41941805 | [] | no_license | codatmo/stanIncrementalImportanceSampling | c8f7497a712c05cc658b02abeaa7bfe4ee07a8da | e7dfc892c488f4da77fc7397e66df55f0af5e884 | refs/heads/master | 2023-05-04T18:55:20.389648 | 2021-05-27T13:21:08 | 2021-05-27T13:21:08 | 370,043,519 | 2 | 0 | null | null | null | null | UTF-8 | R | false | true | 1,021 | rd | importance_sampling.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/importance_sampling.R
\name{importance_sampling}
\alias{importance_sampling}
\title{Calculate Importance Weights}
\usage{
importance_sampling(
originalFit,
oldData,
newData,
model_code = originalFit@stanmodel@model_code[1]
)
}
\argume... |
5cbb677b0a47dc6c7444357f20db369bd96934ba | 086e220d2e6b5300b4287e1e3b1518e0aa5641c0 | /rmd-setup.R | f1aef5becf0424ef235fc5bdd74d0c77ac5a39eb | [] | no_license | Gedevan-Aleksizde/tokyor-91-rmd | fae8409d7d6d6a378320dc58820d2439f3050c5f | 6cd2ca46e45d6b863c011f77d5172180a92968be | refs/heads/main | 2023-04-20T06:02:00.765694 | 2021-05-15T09:44:49 | 2021-05-15T09:44:49 | 358,770,557 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 4,466 | r | rmd-setup.R | ##### (1) RStudio のバージョンについて ####
# 1.4.1103 は Windows 版では Python 使用時にエラーが発生します
# もし Python を使いたいなら新しいバージョンが出るまで待つか,
# 以下の daily build のどれかをインストールしてください
# https://dailies.rstudio.com/rstudio/oss/windows/
##### (2) パッケージのインストール ####
# インストール済みであっても最新版にしておいてください
# ダイアログボックスでなにか言われたらNO!
install.packages(
c("tidyverse",... |
b6c5b90c2cbe502362c18144aae6d036e4a02cd9 | 4f74888f3788e1cac6131fcdd9f4ed8c63bf453f | /man/vivid_adj.Rd | bcc70e06f9a72e5ba0f444f312575d4d6a0adeec | [] | no_license | scchess/VividR | c24714142f9ba8892eb09783f53dbe475c4a9b7f | 02daef0ecfb1653d5fd0fb1c0b8bef22c743ffa6 | refs/heads/master | 2023-08-11T15:45:39.583985 | 2021-07-14T08:05:09 | 2021-07-14T08:05:09 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 950 | rd | vivid_adj.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/vivid_adj.R
\name{vivid_adj}
\alias{vivid_adj}
\title{Adjust variables in a VIVID object}
\usage{
vivid_adj(vividObj, minFinalFeatures)
}
\arguments{
\item{vividObj}{An object passed from the vivid() funciton.}
\item{minFinalFeatures}{Intege... |
d19c03aa5a86451d93b1dadf7a41a5bd12f08b2b | d7a8317efa283107d7645b57409c60b53ab7fee8 | /BEP/simulation/number_of_retained_components.R | 89bb3c9685433fd2bfff1396a104306a45d4fc2e | [] | no_license | lucasnijder/LS_BEP_2021 | 85558e598e8a2e3532bfdecfb4e82e1a741616e3 | 57808afe76d753dfc506e3e101cb4400cbe0ff92 | refs/heads/main | 2023-02-20T12:28:28.665971 | 2021-01-17T21:51:11 | 2021-01-17T21:51:11 | 324,770,191 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,555 | r | number_of_retained_components.R | highlight = function(x, pat, color="black", family="") {
x <- substr(x, 3, 3)
ifelse(grepl(pat, x), glue("<b style='font-family:{family}; color:{color}'>{x}</b>"), x)
}
Plot_per_error <- function(total_res, error){
total_res <- total_res %>% arrange(index)
total_res <- total_res[,-11]
if(error == 0.01)... |
eee45c1080a435db0e9583bc05e063fbd010744a | 45cae983b2d3354277ff2f701f600ddb20c05ddd | /subpixel-accuracy/analysis.R | aa4ec731819d927b1e96d0e53b282e83e1d332db | [] | no_license | alessandro-gentilini/alessandro-gentilini.github.io | 8c2b9c963a39fd5b9e8f70c61a153715df29a44c | cc5b42e7e2d104954ae701278f12492754f16b15 | refs/heads/master | 2023-08-09T16:28:09.175160 | 2023-07-30T09:57:50 | 2023-07-30T09:57:50 | 31,064,413 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 321 | r | analysis.R | pdf("R_plot_%d.pdf")
df<-readr::read_csv('data.csv')
for(i in seq(1,nrow(df))){
if(is.na(df$value[i])){
df$value[i]=df$num[i]/df$den[i]
}
}
library(ggplot2)
plot(ggplot(data=df)
+geom_point(aes(x=year,y=value))
+scale_y_continuous(trans="log10",breaks=c(0.001,df$value))
+ylab('Accuracy in pixel (log scale)'))
... |
bfeef26a7c5e0fa6e68b1d49e89ea1ebfa91202e | 4eb5cda5f02f054d64745ce91923dd1fa4ea9095 | /Vuln_Index/eck3.sensitivityGraphs.R | f2c6256229f89be073973517ba3ae53f7a7e32e7 | [] | no_license | mczapanskiy-usgs/WERC-SC | e2e7cb68616ef0492144c0ef97629abb280103ae | caec92b844c9af737dcfc8d6dbb736de79c3e71c | refs/heads/master | 2021-12-02T16:42:16.529960 | 2021-12-01T16:58:20 | 2021-12-01T16:58:20 | 36,815,737 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,103 | r | eck3.sensitivityGraphs.R | ## this script is used to graph the summary scores for population, collision and displacement sensitivity
## box and whisker plots
scores <- read.csv("VulnIndexFinalSensitivityScores.csv") ## matrix of final PS, CS, and DS
library(ggplot2)
# Population Vulnerability
scores$CommonName <- factor(scores$CommonName, lev... |
4fd9047da22e413637a30f7ae7fe2dea0fc3f226 | b2f61fde194bfcb362b2266da124138efd27d867 | /code/dcnf-ankit-optimized/Results/QBFLIB-2018/A1/Database/Basler/terminator/stmt21_79_304/stmt21_79_304.R | 94343ac95fbedf42c4ae693c6ff29ecf6f5358ae | [] | no_license | arey0pushpa/dcnf-autarky | e95fddba85c035e8b229f5fe9ac540b692a4d5c0 | a6c9a52236af11d7f7e165a4b25b32c538da1c98 | refs/heads/master | 2021-06-09T00:56:32.937250 | 2021-02-19T15:15:23 | 2021-02-19T15:15:23 | 136,440,042 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 65 | r | stmt21_79_304.R | 5433401a7397c5b7bd04551097cc9e65 stmt21_79_304.qdimacs 3123 10273 |
8387a93fd767a2838b794b42690f0f7630037ced | a1dbfdc992917085ed55988f955d5065a3aea69a | /R/expTable.R | 2e2d658b9966b03630ad17f54d05f802258495d3 | [] | no_license | rpolicastro/kevin_scRNAseq_shiny | f643d5fe7e04b34ab116989398f818010eeaa43c | 88c6ca89f92b571fca205a100332914ade4d0751 | refs/heads/master | 2022-11-22T08:12:24.511397 | 2020-07-21T01:32:45 | 2020-07-21T01:32:45 | 272,305,592 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,575 | r | expTable.R |
#' Expression Table UI
#'
#' @inheritParams metadataPlotUI
#'
#' @export
expTableUI <- function(
id,
ident = "orig.ident",
clusters = "seurat_clusters"
) {
## Namespace.
ns <- NS(id)
## Get sample choices.
sample_sheet <- con %>%
tbl("samples") %>%
collect
experiments <- unique(sample_sheet... |
0decb11daf049e14af087c50ee2dab29ba8a122f | 1820722c3c8a37ee2b052db65d658085ab786630 | /TP1/Tp1.R | 9ad8db51da762a1a13cd0db1a907cde7a4a96ba2 | [] | no_license | cristianhernan/austral-mcd-aid | 8f0efcb76fc90bf24d92f210ae7fa3636899636c | 99d49f1562624de3525abeaba8783f942d8f910d | refs/heads/main | 2023-06-24T05:33:16.219278 | 2021-07-22T01:14:21 | 2021-07-22T01:14:21 | 376,146,006 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,813 | r | Tp1.R | #deshabilitar la notacion cientifica
options(scipen=999)
rm(list=ls())
gc()
library(dplyr)
library(tidyr)
reca_ene_raw <- read.csv("../../datasets/aid/tp1/RECA_CHAN_01_NEW.csv",header=TRUE, sep = ",")
reca_ene_raw <- select(reca_ene_raw,-RUNID)
reca_ene_filter <- filter(reca_ene_raw,PURCHASEAMOUNT > 0)
reca_feb_raw <... |
beca588a2db258b81b124f9b27dbfdb76af8d3ac | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/AnaCoDa/examples/getTrace.Rd.R | aedb8f509e49b6eeb71970e1bafff1973b9e4f22 | [] | 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 | 777 | r | getTrace.Rd.R | library(AnaCoDa)
### Name: getTrace
### Title: extracts an object of traces from a parameter object.
### Aliases: getTrace
### ** Examples
genome_file <- system.file("extdata", "genome.fasta", package = "AnaCoDa")
genome <- initializeGenomeObject(file = genome_file)
sphi_init <- c(1,1)
numMixtures <- 2
geneAssig... |
c25e0bd48c053c03339cb5a9dc73e3a7c691f5e6 | 0a4e001ae2276a4cab1925226c7120c9fac7867c | /assignment_04.02_PonisserilRadhakrishnan.R | 08cd4182f34fe2278cf1c124d8618bb9c917242c | [] | no_license | prrajeev/DSC520_Assignments | 886fa5468819502f8c3b2610d7058fb4ba975d84 | 1a8b072716e7956b44f283ac0f6c800f7e01401c | refs/heads/main | 2023-07-07T00:20:43.587106 | 2021-08-15T01:30:12 | 2021-08-15T01:30:12 | 378,742,662 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,329 | r | assignment_04.02_PonisserilRadhakrishnan.R | # Assignment: ASSIGNMENT 4.2.2
# Name: Ponisseril, Radhakrishnan
# Date: 2021-07-04
## Load the tidyverse package
install.packages("tidyverse")
library(readxl)
library(lubridate)
## Set the working directory to the root of your DSC 520 directory
setwd("/Users/RajeevP/dsc520")
## Load the housing dataset
housing_df <... |
a7f58f6ac7eeafd058a096e44f22f9ebc030a024 | 696f9432ca70203924ca84851aa1299aafd28530 | /R/Trial.Simulation.R | 49aa297e9ab34b9c07b81f749c3d5950422383cf | [] | no_license | vivienjyin/phase1RMD | ab725ab570056d5aaf9d3953f9f6968e65e99be7 | af32af2e325c455e1531d52da4f96be12fb7d8df | refs/heads/main | 2023-06-10T13:26:44.862333 | 2021-07-03T01:03:17 | 2021-07-03T01:03:17 | 380,626,085 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 55,251 | r | Trial.Simulation.R | ###################################################################################
###########Simulate Data from the Matrix and Do Stage 1-3##########################
###################################################################################
###model: yij = beta0 + beta1xi + beta2tj + ui + epiij##############... |
7b3518ebb9199e19e782991376360f2a4e52b54f | d7d07cc5bf1e5add6e9f66c07a1d63987bad52e9 | /MATH4473carlos2021/man/mycip.Rd | fce254f627252f97d37016720c9774e88b5958e5 | [
"MIT"
] | permissive | Carlos91016/Applied-Regrssion-Analysis | 5a9f8050c4a64034ebfd74cd45e2054874959dc3 | e956cc5ad6c93941d02364a179b2ec9e7ccb01ba | refs/heads/main | 2023-07-14T06:02:22.247429 | 2021-08-26T03:11:08 | 2021-08-26T03:11:08 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 374 | rd | mycip.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mycip.R
\name{mycip}
\alias{mycip}
\title{Confidence interval for p}
\usage{
mycip(x, n, alpha)
}
\arguments{
\item{x}{frequency category}
\item{n}{total frequency}
\item{alpha}{error rate}
}
\value{
list containing ci
}
\description{
Confi... |
c23d343c669816e430e264a76187fb95e0decf73 | fe2cfcf19c0877234603d519117c893e5b9ef1ed | /man/augment.Rd | 299e66df56a9abad6aad8a66bc88813c3224f0c8 | [] | no_license | 123rugby/multiridge | 13e18b59bfbf4e466cc53a806a1de3d1d63e7f20 | cf72cd737f31b59575d09e1cb654a44873ee56da | refs/heads/master | 2023-01-13T15:20:30.354083 | 2020-11-26T14:05:11 | 2020-11-26T14:05:11 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 938 | rd | augment.Rd | \name{augment}
\alias{augment}
%- Also NEED an '\alias' for EACH other topic documented here.
\title{
Augment data with zeros.
}
\description{
This function augments data with zeros to allow pairing of data on the same variables, but from DIFFERENT samples}
\usage{
augment(Xdata1, Xdata2)
}
%- maybe also 'usage' for o... |
87cd25af36c393511516a2e3597c35018d749458 | ffdea92d4315e4363dd4ae673a1a6adf82a761b5 | /data/genthat_extracted_code/specklestar/examples/speckle_ps.Rd.R | 1917082c7b5fe1f61393bc24c58a0a33ee3f8bc8 | [] | 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 | 359 | r | speckle_ps.Rd.R | library(specklestar)
### Name: speckle_ps
### Title: Power spectrum calculation
### Aliases: speckle_ps
### ** Examples
obj_filename <- system.file("extdata", "ads15182_550_2_frames.dat", package = "specklestar")
midd_dark <- matrix(0, 512, 512)
midd_flat <- matrix(1, 512, 512)
pow_spec <- speckle_ps(obj_filename, ... |
b215bcb972c09b687844ec16656df75e543fd2e8 | a510cfcfd7927e5e07a2509601f493c279618d3b | /code/supportingFuns.R | 8d1f1dc90cc86cc1769e6a4361a5d5de911c5c71 | [] | no_license | MFEh2o/limnoEntryTool_TEMPLATE | c70b20cecaec369f1d3efcdc7a1b1db812b2f51d | 14bfde98511cc2543a15e8edc58909f8e9813ef2 | refs/heads/master | 2023-06-08T15:43:14.311889 | 2023-06-07T19:02:38 | 2023-06-07T19:02:38 | 367,421,763 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 22,004 | r | supportingFuns.R | # Supporting functions for limnoEntry.R
# MetadataID for staff gauge samples --------------------------------------
staffGaugeMetadataID <- "Staff.Gauge.Sample.20140319"
# List of retired projectIDs ----------------------------------------------
retiredProjectIDs <- c(1:2, 4:5, 7:12, 14, 16, 18:25, 27:33, 39:40)
# c... |
57837dcdfaaf5bc683b9f6d32425745aa66b80bf | 876ffa84231869e97536430bf1e0efc9810b6d12 | /R/pow.R | e7a377259cb0cbcfdb5b8e6eeb44b20528dd43ec | [] | no_license | cran/sirt | 3f13a159b57926a51425ae0f530b4650fc690ba7 | a3daefdc2db1141263a5d52025eef37894d54a49 | refs/heads/master | 2023-08-31T23:28:39.426909 | 2023-08-11T09:40:02 | 2023-08-11T10:30:54 | 17,699,690 | 4 | 5 | null | null | null | null | UTF-8 | R | false | false | 94 | r | pow.R | ## File Name: pow.R
## File Version: 0.05
pow <- function(x, a)
{
return( x^a )
}
|
f56c2ba9ec5fc14b5ded9fb5ede740fc763f8a3c | 9e6de53388d316b967d16f1dc826b991deddd1e7 | /week4lib.R | 02e4010b13ab721b399f7b40b67efd5b9c4af9a0 | [] | no_license | mbac/courseraweek4 | b7a4fe77739da6a03b0b9f479f9565e64a6e3667 | cb8b93b9cd74b6b082c08273033a6da039b62980 | refs/heads/main | 2023-02-06T02:40:55.006957 | 2020-12-29T19:41:29 | 2020-12-29T19:41:29 | 325,033,238 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,319 | r | week4lib.R | # We define a function which takes a string as argument, builds file names
# from it, reads in data and sets it up for further evaluation.
loadData <- function(suffix, extension = 'txt') {
if ((!is.character(suffix)) | (suffix == ""))
# Throw a fit
stop("Invalid argument; must be a string prefix f... |
d656ef4098e5d6699f6ad30bcf303142b0bcabd2 | 19339d5d540ee6bd736f337cb9993c711b204d7a | /tests/testthat/test-nltt_diff.R | d87bb48c19bca23cd0da099b2876b00d7234db6f | [] | no_license | cran/nLTT | 89876810619711b3fd7568ef186f9cbb3fd7f576 | 9b4db3454f1949a7c975c40357d5313c90c49f6d | refs/heads/master | 2023-08-31T23:27:04.412506 | 2023-08-21T10:50:05 | 2023-08-21T11:30:57 | 29,488,473 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 727 | r | test-nltt_diff.R | context("nltt_diff")
test_that("nltt_diff must signal it cannot handle polytomies, #23", {
phylogeny_1 <- ape::read.tree(text = "(a:1,b:1):1;")
phylogeny_2 <- ape::read.tree(
text = "((d:0.0000001,c:0.0000001):1,b:1,a:1):1;")
phylogeny_3 <- ape::read.tree(
text = "(((d:0.000000001,c:0.000000001):1,b:1):... |
a8831e219bc1f89fb67c748bc5d472e74e6e8c85 | 4b56315bc1671b8e25fce3c5293f270034a3f88c | /scripts/cognitive/GEE_GAMM/gee_gam_example.R | 2069e76ad793460b6def932bf8f903fbf560b49d | [] | no_license | PennBBL/pncLongitudinalPsychosis | fd8895b94bcd0c4910dd5a48019e7d2021993d3a | 006364626ccbddac6197a0e7c5cbe04215601e33 | refs/heads/master | 2023-05-27T00:16:35.264690 | 2021-06-18T13:55:49 | 2021-06-18T13:55:49 | 172,975,758 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 9,328 | r | gee_gam_example.R | # Example using GAM + GEE to test significance on example vertices and in simulated data
library(mgcv)
library(geepack)
# install.packages("doBy")
library(doBy)
library(MASS)
setwd("/home/smweinst/test_vertices_gee_gam/")
## Example vertices ----
# load in example vertices
Long_Motor<-readRDS('LongFormat_MotorVert.r... |
bd4c883e9a00184744a732cf570aec70f778097c | 88c04d94a33b19d0c537e81ffae62018d2a18d34 | /R/ordprob.pair.R | b57dd8645ecf8b009ae82aab30664c19ed54106a | [] | no_license | cran/PLordprob | 4512c18ed79b947878196050e0823e8c252b873c | be3d8d83587847ee4c846a4515141054ded0573e | refs/heads/master | 2020-05-19T11:03:36.748185 | 2018-06-05T15:34:18 | 2018-06-05T15:34:18 | 25,037,091 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 1,273 | r | ordprob.pair.R | ordprob.pair <-
function(param,K,x,ss,data,same.means=FALSE){
if(!is.null(x)){
x = as.matrix(x)
p <- dim(x)[2]
}
else p = 0
data = as.matrix(data)
n = nrow(data)
q = ncol(data)
delta = param[1:(K-2)]
a = delta2a(delta)
beta = param[(1:(p))+(K-2)]
if(same.means){... |
0a39b816690f63be8a2bcbf3388e0677d5dc0037 | 2f87fc27b2d6e10b736cf07f7f991fa4d37873f4 | /tests/testthat/test-commutative-addition.R | 24dd781a6dc8d4262898244424d931abd728cbb9 | [] | no_license | algebraic-graphs/R | 37f7ac5fee5bf8eb49e02a36cac15d1df039bc93 | 8316776a21024b81b2300d1c037a9328a2b92cf9 | refs/heads/master | 2023-08-01T05:48:36.588424 | 2021-09-24T13:51:57 | 2021-09-24T13:51:57 | 409,034,609 | 2 | 0 | null | null | null | null | UTF-8 | R | false | false | 156 | r | test-commutative-addition.R | test_that("Addition is commutative", {
library(tidyverse)
library(tidygraph)
library(ralget)
expect_true(v("a") + v("b") == v("b") + v("a")
)
})
|
3ff68d3d3999192a97dff32d40ad50b84ace61ea | 8455fc20fed9641f65ed8a5b2e065c7e8075e730 | /man/which.max.Rd | 208e77686aa8180024a32487435a52a5d66b78f0 | [] | no_license | andreas50/uts | 0cfb629448886bcee992e6ae8ab453d15fd366ff | f7cea0d2ba074d332a4eb9b5498451fe0bc9a94f | refs/heads/master | 2021-07-24T13:41:29.982215 | 2021-04-05T14:41:04 | 2021-04-05T14:41:04 | 35,902,127 | 16 | 0 | null | null | null | null | UTF-8 | R | false | true | 818 | rd | which.max.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/which.R
\name{which.max}
\alias{which.max}
\alias{which.max.default}
\title{Generic which.max function}
\usage{
which.max(x, ...)
\method{which.max}{default}(x, ...)
}
\arguments{
\item{x}{an \R object.}
\item{\dots}{further arguments passe... |
78b33bbb031b9c9d2771170d76f13370dc444642 | cd6aa9ddbfc6d63d7f66cbc3d4576fb89abfd611 | /building_long-form_tables.R | 05ac1947c61f0564d37fab349bc826b0df456c2b | [] | no_license | genevievekathleensmith/shakespeare-chronordination | 315c8ceb1250c72ecdefed6314154813e75ff7e2 | 5eb69a16c52716c8c3b9e56e5981eccfe04321c7 | refs/heads/master | 2021-01-25T10:39:18.378317 | 2014-04-29T15:53:35 | 2014-04-29T15:53:35 | 17,147,583 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,087 | r | building_long-form_tables.R |
# For the up to date counts, including Arden of Faversham:
#counts = read.csv('~/Documents/shakespeare-chronordination/SH DATA all counts A minus C plus ARD.csv')
#verse = read.csv('~/Documents/shakespeare-chronordination/verse_line_counts plus ARD.csv')
# For the revised version of 1H6:
#counts = read.csv('~/Documen... |
660e9362f0f2d47c7c8ff75c431e4f557c806a60 | 360df3c6d013b7a9423b65d1fac0172bbbcf73ca | /FDA_Pesticide_Glossary/(_-chloroethyl)trime.R | a803729c5e7b8322d3ce32b96de456684471e900 | [
"MIT"
] | permissive | andrewdefries/andrewdefries.github.io | 026aad7bd35d29d60d9746039dd7a516ad6c215f | d84f2c21f06c40b7ec49512a4fb13b4246f92209 | refs/heads/master | 2016-09-06T01:44:48.290950 | 2015-05-01T17:19:42 | 2015-05-01T17:19:42 | 17,783,203 | 0 | 1 | null | null | null | null | UTF-8 | R | false | false | 276 | r | (_-chloroethyl)trime.R | library("knitr")
library("rgl")
#knit("(_-chloroethyl)trime.Rmd")
#markdownToHTML('(_-chloroethyl)trime.md', '(_-chloroethyl)trime.html', options=c("use_xhml"))
#system("pandoc -s (_-chloroethyl)trime.html -o (_-chloroethyl)trime.pdf")
knit2html('(_-chloroethyl)trime.Rmd')
|
734630240d22730a7b865b8b59c380002bdad435 | ae5c61d8ffd1c03eb7ef503c3bd660451df31122 | /run_analysis.R | 0bcd99e664c0e2ffa7fe93e6e24cb468bc376bc3 | [] | no_license | ramithaJHU/WearableHMR | d2655557c4d6180acec27690e62f96bfea9a0bd0 | 40e3e65433ad30b7cfb73673e0aee49a4879ca81 | refs/heads/master | 2020-06-13T16:32:38.412334 | 2019-07-02T02:54:44 | 2019-07-02T02:54:44 | 194,712,300 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,279 | r | run_analysis.R | # This file contains the R-code for generating tidy data out of row data collected from
# Samsung Galaxy S smartphone and the script for performing the analysis
# A group of 30 volunteers within an age bracket of 19-48 years were asked to
# perform six different activities. Their activities were recorded using smartp... |
e3cbf51daafdbaf47959c76b8299f0d380615e07 | 1e42b9829b85bc37d112ec5b8efa1682264297b2 | /man/trace_length.Rd | 80ff01401827429f46f4a4ddb987a2896b1db006 | [] | no_license | strategist922/edeaR | ca83bf91f58e685bc9333f4db3bfea3d8c019343 | ad96118cccfdc90a7bed94f5aef2ee0cfab3aac8 | refs/heads/master | 2021-07-05T04:30:35.286640 | 2017-09-27T12:25:04 | 2017-09-27T12:25:04 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 719 | rd | trace_length.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/trace_length.R
\name{trace_length}
\alias{trace_length}
\title{Metric: Trace length}
\usage{
trace_length(eventlog, level_of_analysis = c("log", "trace", "case"))
}
\arguments{
\item{eventlog}{The event log to be used. An object of class
\cod... |
526c452ff890f63415211d4ae5e54c33d08b918b | ccbed05be4d46205ef49ba1cc472521395c69ad4 | /shiny/wildebeest/ga4_network.R | 08ad7ccd15810a441d4ad86fed6dd712817ad517 | [] | no_license | govau/GAlileo | 4936abc28f2f2e8f0282e8c8e86712723a421b7e | eba52024ca3a930571c53184b5275d80de3e04a9 | refs/heads/develop | 2022-09-18T18:51:46.153133 | 2022-09-05T05:18:18 | 2022-09-05T05:18:18 | 183,550,388 | 9 | 3 | null | 2021-12-03T12:15:00 | 2019-04-26T03:28:49 | Jupyter Notebook | UTF-8 | R | false | false | 3,205 | r | ga4_network.R | # network theory in R
raw_data <- read.csv('~/Documents/network_diagram_ga4/nodes_data.csv')
library(stringr)
# clean up a bit
raw_data$from_hostname <- gsub( "www.", "", raw_data$from_hostname, ignore.case = T)
raw_data$from_hostname <- gsub( "m.facebook.com", "facebook.com", raw_data$from_hostname, ignore.case = T)... |
20e6982604716f2d8bc1a6671e676f2bf114510b | 9753d94f00a9db2bb5dea5a711bf3a976fa19fb7 | /3. Probability/Sapply_2.R | 43555dd0bb59a7c9cb86bb7294699e18cf819bc7 | [] | no_license | praveen556/R_Practice | a3131068011685fd1a945bf75758297a993357a7 | 0fc21f69c0027b16e0bce17ad074eeaa182170bf | refs/heads/master | 2023-02-18T09:11:49.982980 | 2021-01-17T16:07:28 | 2021-01-17T16:07:28 | 293,621,569 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,028 | r | Sapply_2.R | #Validating normal operations on Vectors
num_samp <- seq(1,10)
num_samp2 <- seq(101,110)
num_samp*num_samp2
num_samp*2
sqrt(num_samp)
sapply(num_samp,sqrt)
#sapply on Birthday Problem
n<-60
bth <- sample(1:365,n,replace = TRUE)
any(duplicated(bth))
#Function to calculate probability of shared bdays across n people
co... |
859cc540798f5cc896d3eed028b24c051b5b4125 | a47ce30f5112b01d5ab3e790a1b51c910f3cf1c3 | /A_github/sources/authors/2866/SSDforR/SD2legend.R | 7d6083236406757ad8b765ff16361d8a91c7f8ad | [] | 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 | 188 | r | SD2legend.R | SD2legend <-
function(){
par(mar=c(1, 1, 1, 1))
plot.new()
legend("center", c("behavior","+2sd","mean","-2sd"), col = c("red","black", "green","black"),lwd = 3,ncol=4,bty ="n")
}
|
3ec139a392cd93fc071b86f8422e351c0855674b | 2fb6b59645427f1e05564f15f8badc09b812b45f | /R/TuneMultiCritControlMBO.R | ab7ff80efe97bc7825546782ca4f576971fcedeb | [] | no_license | NamwooPark/mlr | 18cf6023e7bc4b743d40bd8df1070a098b267751 | c08bb0090ec1999b78779a73d0242b45b2dcee42 | refs/heads/master | 2021-05-02T05:26:38.010558 | 2018-02-08T12:58:31 | 2018-02-08T12:58:31 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 1,779 | r | TuneMultiCritControlMBO.R | #' @export
#' @inheritParams makeTuneControlMBO
#' @param n.objectives [\code{integer(1)}]\cr
#' Number of objectives, i.e. number of \code{\link{Measure}}s to optimize.
#' @rdname TuneMultiCritControl
makeTuneMultiCritControlMBO = function(n.objectives = mbo.control$n.objectives,
same.resampling.instance = TRUE, i... |
9b5c89aac5ec3dd6675a5aa8736a562687100ad1 | 175fd850d274f7c47baefb7de0440e14c8d53856 | /T3/R_sintaxes.R | 2217bb6c8d33dafa29cb9e09ab7ff4070be4dd32 | [] | no_license | taisbellini/intro-pacotes-estatisticos | e597dc4ff3aad5a2b7e3277691173ee93dc979fd | 3a64c7f12668781c962f3cccbedc0a60dfe020ef | refs/heads/master | 2020-04-28T22:50:20.844451 | 2019-06-30T13:09:34 | 2019-06-30T13:09:34 | 175,631,674 | 3 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,929 | r | R_sintaxes.R | #### Slide 12 ####
2 * 4
2 *
4
#### Slide 14 ####
sqrt(2)
log(,3)
#### Slide 17 ####
valor <- 2*4
valor
x = 25
x2 = x^2
x2
#### Slide 18 ####
valor
Valor
T
t
#### Slide 19 ####
valor = 2 * 4
valor
nome = "Sexo Feminino"
nome
nome = "Sexo Feminino"
nome
#### Slide 20 ####
valor >= 5 & valor <= 10
#### Sl... |
31e994e8ab923b8afa0b65f86d79a7304c5307a0 | 169874bae167edf16577f6c48a4d976e085935aa | /codes/medical_no_shows.R | f3643dc6db2c3bb632d19128bcacc7be5f734918 | [] | no_license | ArunSudhakaran/Data-Mining-and-Machine-Learning | 818a3c355d6d8d3c8732f44584258fab208597e6 | f88627297723299cdca79c67e5dc4b14ab9cd3a7 | refs/heads/master | 2022-12-19T13:11:24.282894 | 2020-09-22T23:20:23 | 2020-09-22T23:20:23 | 297,795,359 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,780 | r | medical_no_shows.R | ####predicting medical appointment no shows
data<- read.csv("data_mining/no_show_appointments_data.csv")
str(data)
head(data)
summary(data)
###converting to factors
data$Gender <- factor(data$Gender, levels = c("M", "F"))
data$Scholarship<-as.factor(data$Scholarship)
data$Hipertension<-as.factor(data$Hipert... |
0264f840f5477cf2549f373f4ae05438525522bb | 36c06ce1b3f61c75740b80073d0237650a43dd15 | /plot4.R | 7695ae66a561aa5da4b0a26699ed558336635ea3 | [] | no_license | joancarter2000/ExData_Plotting1 | e6c11f290a61f285071e3fb140ddbeb1e36b695a | b51e1c44815c532c17e3d91cd422082d93c1fcfd | refs/heads/master | 2021-01-15T12:36:26.533509 | 2015-04-11T22:04:17 | 2015-04-11T22:04:17 | 33,793,914 | 0 | 0 | null | 2015-04-11T21:52:16 | 2015-04-11T21:52:16 | null | UTF-8 | R | false | false | 1,891 | r | plot4.R | ##course project 1
##read in the entire dataset
epc<-read.table("household_power_consumption.txt", sep=";", header=TRUE, colClasses="character")
head(epc)
str(epc)
##subset 1/2/2007 and 2/2/2007 data from the original dataframe
subepc<-epc[epc$Date=="1/2/2007"|epc$Date=="2/2/2007",]
##change the "global active power"... |
a7bbb99224b3862d4069a1f6f70bfd8adabdbd33 | 2e74c7339c63385172629eaa84680a85a4731ee9 | /alcohol/paf/04_2_assault.R | 22bd8008ec28555b87568f6a70d92a3091c75508 | [] | no_license | zhusui/ihme-modeling | 04545182d0359adacd22984cb11c584c86e889c2 | dfd2fe2a23bd4a0799b49881cb9785f5c0512db3 | refs/heads/master | 2021-01-20T12:30:52.254363 | 2016-10-11T00:33:36 | 2016-10-11T00:33:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 5,199 | r | 04_2_assault.R | ############# This program will compute the Alcohol Attributable Fractions (AAF) for assault injuries
library(foreign)
library(haven)
library(data.table)
if (Sys.info()["sysname"] == "Windows") {
root <- "J:/"
arg <- c(1995, "J:/WORK/05_risk/risks/drugs_alcohol/data/exp/summary_inputs", "/share/gbd/WORK/05_risk/02... |
37a604a0a1d0cfbe39e77b9af038acd2828e8580 | a1a1661d8f42f8005f4a41de6ba333eec0b096a7 | /Correlation.R | 5fb2e102f9c08b96680f9301137168b9b23db76c | [] | no_license | jihadrashid/UsedRcodeForMyWork | 5db49e15b245f29d1f7ea2b76ba0494536e8b1ab | 1b37b9c524464e0fb1b9e87b4a9a4444d494003a | refs/heads/main | 2023-01-31T05:57:38.302766 | 2020-12-15T06:05:05 | 2020-12-15T06:05:05 | 321,569,013 | 0 | 0 | null | null | null | null | WINDOWS-1252 | R | false | false | 1,168 | r | Correlation.R | data=as.data.frame(Dhaka_21H_1col)
rain=as.data.frame(dhaka)
final_data=cbind.data.frame(data,rain)
View(final_data)
windowsFonts(A = windowsFont("Times New Roman"))
library(ggpubr)
library(devtools)
library(ggplot2)
ggscatter(final_data, x="...2", y="dhaka",col="blue",
conf.int = TRUE,cor.coef = T... |
9a08493fd74e4c915b1368b0fec919f217139b5d | 92cbe9dab2a19c975ea9e74a960afc6b9a4513e0 | /info_3010/Homeworks/practice_w2/practice_w2_3.R | 335a87ddea58d6ce4eabc40fc3036c5056160d74 | [] | no_license | Silicon-beep/UNT_coursework | b43e35094c120cb8467ffb7d35ce95fe6552b39c | 1acd54a6aeddd4be1a2e5ca171c75c4e0fabff82 | refs/heads/main | 2023-05-08T19:16:01.410167 | 2021-05-20T00:32:50 | 2021-05-20T00:32:50 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 426 | r | practice_w2_3.R | #course.grades things
course.grades<-c(92,75,46,26,0,100,89,76)
n<-1
while (n<=length(course.grades)) {
print(course.grades[n])
n=n+1
}
n<-1
while (n<=length(course.grades)) {
if (course.grades[n]<60) {
print("failed")
} else {
print("pass")
}
n=n+1
}
#function to compute area of ractangle
#using ... |
ca5b8ce7f4f1fe72c1cfa07384a42cc711d7405f | 66a094ca8e95ce50948276e3bd3d2e5c00cf525e | /ui.R | 8d70731ea06d7ce8259a58cd2fb7eb5ed64ece90 | [] | no_license | eharason/ally_AccessiCity | 297d1fba0401e8e1dfd0188b7fe9034ddd4b1805 | 44e3b183a9247b4c6eff5fec2946681e4f28e2f5 | refs/heads/master | 2016-08-06T23:19:01.629828 | 2015-08-21T13:15:00 | 2015-08-21T13:15:00 | 41,119,805 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 769 | r | ui.R | library(shiny)
library(leaflet)
library(sp)
# Define UI for AccessiCity that draws a map
shinyUI(fluidPage(
# Application title
titlePanel("AccessiCity for Mexico City's General Transit Network"),
# Sidebar with a checkbox and drop-down menu
sidebarLayout(
sidebarPanel(
selectInput("RouteType", ... |
60bc9b3943073a02fcd53cbe1d85d1bda237d0b5 | b4bea34c234d74f8812b23d43bd9dcb0227c048a | /Example_Data/jupyter_lab/analyze_health_and_income.R | fe4112f473eed4503eba30ef9fb1497e023ed8d6 | [] | no_license | nickeubank/data-science-in-julia | 4ff8c686fe8f7f7056cac247ed644854f9d3f686 | fbce77d89dedf6f64fb8572a20c2d03e8384ebd6 | refs/heads/master | 2022-04-17T00:35:25.187628 | 2020-04-07T16:01:47 | 2020-04-07T16:01:47 | 255,151,601 | 2 | 1 | null | null | null | null | UTF-8 | R | false | false | 692 | r | analyze_health_and_income.R | ######################
#
# Import World Development Indicators
# and look at the relationship between income
# and health outcomes across countries
#
######################
# Download World Development Indicators
wdi = read.csv("https://media.githubusercontent.com/media/nickeubank/MIDS_Data/master/World_Development_I... |
5bd047ea62cc9ecad45b2e499ec024dbbac98f5c | 8258ac64f4b1a6afe35c8b86e526148ba15ce4ce | /Master Thesis/R - S. Ambrogio/S.Ambrogio IN/9. SA - 1Q-Ntotin.R | 57473eabf7667698305c877c7bc97e4555efba27 | [] | no_license | maricorsi17/University-Projects | 212bba7462068ad0da5140000acd8a24c965cc57 | f5e9e044ff17dfc47f2002759e19d8c72108f145 | refs/heads/master | 2020-04-23T17:39:21.037187 | 2019-03-02T19:16:18 | 2019-03-02T19:16:18 | 171,339,185 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,800 | r | 9. SA - 1Q-Ntotin.R | # Installare pacchetti
#install.packages("xts")
library("xts")
#install.packages("TTR")
library("TTR")
library("plotrix")
library("hydroTSM")
library("zoo")
# caricare file excel
SAmbrogio<-read.csv2(file="c:/Users/Marianna/Documents/Universita/Tesi/R - S. Ambrogio/S.Ambrogio.CSV", header=TRUE, sep=";")
# Creare time... |
9212ca11998c0d8ff84224462cf8e593a0cd4ba1 | eb214cc7d36c4fc739da8027810a4ff742673714 | /man/mod_donneessup.Rd | c08756298e43307383083cc31d89e094a5326001 | [
"MIT"
] | permissive | forestys54/inventairexy | 0c72e42b27543d256f8eb8d46bcb4ef69644b10d | a322e5cb9e3612eb19e7f34134ffd6f483a8f6c2 | refs/heads/master | 2020-12-30T06:15:34.869998 | 2020-07-23T09:02:42 | 2020-07-23T09:02:42 | 238,888,601 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 471 | rd | mod_donneessup.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/mod_donneessup.R
\name{mod_donneessup_ui}
\alias{mod_donneessup_ui}
\alias{mod_donneessup_server}
\title{mod_donneessup_ui and mod_donneessup_server}
\usage{
mod_donneessup_ui(id)
mod_donneessup_server(input, output, session, rv)
}
\argument... |
30cf25c438cc988eac80a6292662269766456e52 | 9e90a923b49e53e8d402d85d66bee9d02f6a483f | /tests/testthat/test-twin_to_yule_tree.R | cf9f74cdf3946f6b2d0d4044269db4b40b10d231 | [] | no_license | thijsjanzen/pirouette | 7e66c8276a11a18a6184f27dab6cb8ee06abfa28 | 463a2bd61ee9d5ada7c249d803e99391de264b79 | refs/heads/master | 2020-05-25T16:21:22.467232 | 2019-05-07T12:46:27 | 2019-05-07T12:46:27 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 440 | r | test-twin_to_yule_tree.R | context("test-twin_to_yule_tree")
test_that("use", {
phylogeny <- load_tree(tree_model = "mbd", seed = 1)
twinning_params <- create_twinning_params()
twinning_params$rng_seed <- 1
yule_tree <- twin_to_yule_tree(
phylogeny = phylogeny,
twinning_params = twinning_params
)
expect_equal(class(yule_tr... |
d2a6dfb4c9f2e3cc11b7764f5631c04f9e7ab501 | 56bf6691056c3e38aec9c0c9a6bb6094de0a3ca8 | /processing/company_data_product_script.R | 8786b78e898f46b0813aa019171749693e3394ec | [] | no_license | ioanna-toufexi/companies-stream | 1462a3209277f13077790e4ce6cce617e715456c | f7a2ea9f144d71a8db42abbf5f0cc2fec65ffb28 | refs/heads/master | 2022-12-13T06:41:50.723719 | 2020-09-14T10:15:34 | 2020-09-14T10:15:34 | 264,620,903 | 1 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,541 | r | company_data_product_script.R | if(!require("pacman")) install.packages("pacman")
pacman::p_load(readr, htmlwidgets, geojsonio, tigris)
source("data_grouper.R")
source("plotter.R")
source("sic_mappings.R")
source("mapper.R")
# This script has a series of steps to analyse and visualise data from
# the Companies House `Company data product` CSV file.
... |
c83c6de99050725215c0f9817820f1b327399792 | e1f70ac6d5604c3f5bf7dbe02345333dda964642 | /analysis/UniprotAnnotations_NetworkAnalysis/Map2SRlabGOslimsTerms.R | 782f345104accecedda08a285a29f5ddcf5855e2 | [] | no_license | shellywanamaker/OysterSeedProject | 461b90d2dee9a9e2283a3af2fbe91af6a70c05ac | a761b8bd589e80454b83c5099b8dbc65a4e497c2 | refs/heads/master | 2023-01-23T18:30:14.929947 | 2019-10-23T19:34:33 | 2019-10-23T19:34:33 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 2,991 | r | Map2SRlabGOslimsTerms.R | #load libraries
library(plyr)
library(tidyr)
#install.packages("ontologyIndex")
#install.packages("ontologySimilarity")
library(ontologyIndex)
library(ontologySimilarity)
library(GSEABase)
library(reshape2)
#####WITH SR LAB GO SLIMS#####
#load Robert's lab go slim terms
srlabGOSLIM <- read.csv("~/Documents/GitHub/Oys... |
7b41e33db2b2b093b7cf03bc11401651c557a61a | 319c8effd49600b5796cd1759063b0b8f10aeac1 | /workspace/splicing/lung/rmsk/scatterplot.r.2018050611 | 86997b7ff202a1b025f62079c4bddadc11fa8416 | [] | no_license | ijayden-lung/hpc | 94ff6b8e30049b1246b1381638a39f4f46df655c | 6e8efdebc6a070f761547b0af888780bdd7a761d | refs/heads/master | 2021-06-16T14:58:51.056045 | 2021-01-27T02:51:12 | 2021-01-27T02:51:12 | 132,264,399 | 1 | 1 | null | null | null | null | UTF-8 | R | false | false | 464 | 2018050611 | scatterplot.r.2018050611 | #!/usr/bin/env Rscript
library(ggplot2)
args<-commandArgs(T)
pdf(args[2])
data = read.table(args[1],header=TRUE,row.names=1)
#y = log2(data$high_1+data$high_2)
#x = log2(data$low_1+data$low_2)
#reg<-lm(log2(high_1+high_2) ~ log2(low_1+low_2),data,na.action = na.exclude)
#summary(reg)
ggplot(data, aes(x=log2(low_1+low_... |
b21566403f263d9af49ced43c9395e18a3c706f2 | ba5f80c55e710cb253fbcc6d2a638cc1e1c4aaf0 | /run_analysis.R | e9e70b4f2387fd4ae3787d15ad4ac7bf33bf72e6 | [] | no_license | nofacetou/Gettingdata | fb52c461750fa29d6056a94cc40c627218777a64 | 41766018c9be8a89aa3445e05d54bfc7fbd52bbd | refs/heads/master | 2021-01-10T19:48:46.544948 | 2014-04-27T07:41:58 | 2014-04-27T07:41:58 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,028 | r | run_analysis.R | #set the filepath for the input and output files
filepath_X_train <- "D:/Document/My Copy/Copy/Portable Python 2.7.3.2/App/Scripts/getdata-002/UCI HAR Dataset/train/X_train.txt"
filepath_y_train <- "D:/Document/My Copy/Copy/Portable Python 2.7.3.2/App/Scripts/getdata-002/UCI HAR Dataset/train/y_train.txt"
filepath_subj... |
784324070a2184ea1a6b533f44eff9788d4e62b8 | 974d1d8f820c03156ba00b3faf459267ca1d56f1 | /man/output.Rd | cc3668693d462eb96f79655d586f46f945be645d | [] | no_license | aumath-advancedr2019/Sampling | e60f91b9e2fd377f701e2797049435a942075647 | 3c0b4de0e066abb22833a360b65b2153b506d2ff | refs/heads/master | 2020-07-26T23:33:37.322693 | 2019-11-25T13:17:10 | 2019-11-25T13:17:10 | 208,798,058 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 488 | rd | output.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/permutation.R
\name{output}
\alias{output}
\title{output}
\usage{
output(data = data.frame(), null.value = c(),
alternative = "two-sided", method = "Two-sided permutation test",
estimate = c(), data.name = "", statistic = c(),
parameter... |
be7fb3baa986058652d82074e4114562bb53c35c | 625c4159be5b9b4cc2d57f438228b5424423e38a | /R/show.R | ae511bb406fb3ed3e034cc62902da5a11bb1262e | [] | no_license | tintinthong/chessR | e6d936e6cd51b2159a9d28c8b6683602367fd7bb | 60f8e254f30e1cce77d177a558ae26467144841a | refs/heads/master | 2020-04-20T21:52:30.082501 | 2019-02-08T06:32:01 | 2019-02-08T06:32:01 | 169,121,594 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 648 | r | show.R | #show method for displaying S4 objects
#setMethod("show", "board",
# function(object)print(rbind(x = object@x, y=object@y))
#)
#setMethod("show", "game",
# function(object)print(rbind(x = object@x, y=object@y))
#)
#args(show) #args of method has to have same arguments as generic
#show
#setMeth... |
d2ebdd90f71bc7a2efef41d67465d3ffaf1b3d73 | 751570c81bda2218f9a06273613144c9715a8a69 | /grafi.R | fe4724b64395aeb793191c1428bc44de68496be3 | [] | no_license | TinaJ/ProjektMZR | 1b7dbb5a06490c611549288e525893ed30dea91d | 8fe6c74cfb9207b93f413ca92902561178c88332 | refs/heads/master | 2016-09-05T18:03:37.828885 | 2014-01-30T10:05:34 | 2014-01-30T10:05:34 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 4,851 | r | grafi.R | setwd("C:/Users/Tina/Documents/faks/2. letnik magisterija/matematika z računalnikom/ProjektMZR")
library(timeSeries)
## Narišem equity za vse strategije na en graf:
load("./data/equityVseStrategije.rda")
# določim maksimalno in minimalno vrednost, za y os:
# y.max = max(equityVseStrategije)
# y.min = min(equityVseS... |
05df8c64713a26075fdb7afa96b90de4bc038394 | de947d882fa63e5a64f71d58037cc7fcca7f033d | /exploratory.r | 47a1bbbabfcca428bd37665b1285b5322412e6a0 | [] | no_license | krashr-ds/old-r-models | 30e71dcbbc3fbc04d58169bacd4e509f1ec94851 | 179a9367a0faceff5dee22ec4b19cbd0dc7e1510 | refs/heads/master | 2023-02-01T22:32:43.022610 | 2020-12-15T14:20:15 | 2020-12-15T14:20:15 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 21,414 | r | exploratory.r | # Exploratory data analysis; Framingham data
library(dplyr)
library(ggplot2)
library(tidyr)
library(purrr)
library(broom)
# USE frmgham data where each person has 3 entries / periods (9618 rows / 3 = 3206 individuals)
fr_ex <- frmgham %>%
group_by(RANDID) %>%
filter(n()==3)
# GATHER AND RECODE #
#############... |
cf75cf5557569c45fda34873fb6e7818d8599056 | 97932fb906650536ff644f4b57e1b05a74695e1d | /man/sq_list_locations.Rd | 7b683a5f8294918734ed3bef0ca4dff9abe86c89 | [] | no_license | muschellij2/squareupr | 350ed186d711182abfb6ad5dde0c068e5325ee29 | 37bf28750127235c09f7f57278faf484b04aac0d | refs/heads/master | 2021-05-26T23:23:03.404648 | 2019-07-11T20:50:36 | 2019-07-11T20:50:36 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 699 | rd | sq_list_locations.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/locations.R
\name{sq_list_locations}
\alias{sq_list_locations}
\title{List Locations}
\usage{
sq_list_locations(verbose = FALSE)
}
\arguments{
\item{verbose}{logical; do you want informative messages?}
}
\value{
\code{tbl_df} of locations
}
\... |
ae7e4005570ae7a943d3986733187e6377e061f8 | edc6dad2b241a1d0f4a7eef6378bc5e0fe1f57a0 | /man/RR.Rd | c4b3e2a8dd7a472d105cf5f7af4cc7686c4bcbc0 | [] | no_license | ejanalysis/ejanalysis | 5060b1ee3cb65dd5302cc6a42821492501aa334a | 47f6a0fa33ddb4be04da2264eb6e9c7e1ccf99f8 | refs/heads/master | 2023-06-10T18:17:30.239436 | 2023-05-25T23:13:56 | 2023-05-25T23:13:56 | 32,804,966 | 4 | 2 | null | null | null | null | UTF-8 | R | false | true | 8,030 | rd | RR.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/RR.R
\name{RR}
\alias{RR}
\title{Relative Risk (RR) by demographic group by indicator based on Census data}
\usage{
RR(e, d, pop, dref, na.rm = TRUE)
}
\arguments{
\item{e}{Vector or data.frame or matrix with 1 or more environmental indicator... |
9e79b7274c9197eb276c177a57859fcf11371593 | 3d8591a58ee592967b06f296683397189e3fdedb | /R/ParallelKNNCrossValidation_functions.R | 320153f3c8d902aab7cbece9086ebd3f2ccd18ef | [] | no_license | ArdernHB/KnnDist | e390f80b2d1412e7b5816db3a8eda8751f94f8a4 | 06d0587ada12a3e08ce84380e8c782ceabf1ad13 | refs/heads/master | 2023-03-02T03:40:42.845418 | 2021-02-04T14:17:44 | 2021-02-04T14:17:44 | 259,664,220 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 15,792 | r | ParallelKNNCrossValidation_functions.R |
#' K-Nearest Neighbour correct cross-validation with distance input using parallel processing
#'
#' This function takes a square matrix of distances among specimens of known group membership
#' and returns the results of a leave-one-out correct cross validation identification for each
#' specimen to provide a correc... |
09a7905d7dad2287c05ae417f950dbc98f2546b0 | d14f4bc6f62eeb1d109a424f80b1ac0e4c2c687f | /inst/scripts/collect.nomisma.R | e42a60fe87c6bf7573d91ca48e58966e7b2afcb4 | [] | no_license | sfsheath/cawd | 6534598c46dab7c2f91542c499122cb5c161e41b | 928f175f6b48e8d14000cdf7bf1a233570bd0485 | refs/heads/master | 2021-01-17T08:00:18.432209 | 2017-12-21T20:32:26 | 2017-12-21T20:32:26 | 33,830,182 | 12 | 1 | null | null | null | null | UTF-8 | R | false | false | 6,519 | r | collect.nomisma.R | # first go at script to load nomisma.org data into cawd.
library(devtools)
library(sp)
library(SPARQL)
url <- "http://nomisma.org/query"
ns = c('geo','<http://www.w3.org/2003/01/geo/wgs84_pos#>',
'nmo','<http://nomisma.org/ontology#>',
'pleiades','<http://pleiades.stoa.org/places/',
'skos','<http://... |
9cf7080c61d72d2165fce39fd25214b7b50a60a7 | ebd676b6c648b8869101743a5838f300758cc018 | /AmesHousing/AmesHousing.R | e4d56e12f049932c8d3b40b3558f4a65060d5c79 | [] | no_license | khushbup7/AmesHousing-Dataset-Analysis | db86b290a2afc6b9599f76922626d9a92089b4cf | 85bd415d5833e39151e9f17ccb83674b45e58c7c | refs/heads/master | 2021-06-14T15:58:08.459034 | 2017-03-23T02:31:03 | 2017-03-23T02:31:03 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 3,303 | r | AmesHousing.R | myData=as.data.frame(unclass(AmesHousing))
summary(myData)
myData = myData[,-1]
dim(myData)
myData = myData[,c("MS.SubClass","MS.Zoning", "Lot.Frontage","Lot.Area","Lot.Shape"
,"Land.Contour","Lot.Config","Neighborhood","Bldg.Type","House.Style",
"Overall.Qual","Overall.Cond","Ro... |
eecea4550bcc3c22fbfbe58f22871e5dc612dbaa | 4b08dfacf916de2bf5ef0ce4a0d2040b70946794 | /R/simulation.R | 8e09c211c8f9478768c1f6253b1833065ea78461 | [] | no_license | richfitz/diversitree | 7426e13415829e3fc6a37265926a36461d458cc6 | 8869a002f8c978883f5027254f6fbc00ccfa8443 | refs/heads/master | 2023-08-08T23:13:59.081736 | 2023-05-03T14:43:17 | 2023-05-03T14:43:17 | 3,779,673 | 16 | 13 | null | 2023-08-24T14:46:37 | 2012-03-20T20:29:11 | R | UTF-8 | R | false | false | 6,152 | r | simulation.R | ## I need to tidy this up a little bit to allow for different tree
## types. I also cannot use functions beginning with simulate(), as
## this is a standard R generic function.
##
## It might be useful to have the simulations use somthing like the
## equilibrium distribution for characters at the bottom of the tree.
#... |
7f444a0e4b4b4bcb4bb2520e47596b4a059ebadc | 1e36964d5de4f8e472be681bad39fa0475d91491 | /man/SDMXTimeDimension.Rd | b071086375c5e58d21547b107364aa5b74fc5c46 | [] | no_license | cran/rsdmx | ea299980a1e9e72c547b2cca9496b613dcf0d37f | d6ee966a0a94c5cfa242a58137676a512dce8762 | refs/heads/master | 2023-09-01T03:53:25.208357 | 2023-08-28T13:00:02 | 2023-08-28T13:30:55 | 23,386,192 | 0 | 0 | null | null | null | null | UTF-8 | R | false | true | 2,067 | rd | SDMXTimeDimension.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Class-SDMXTimeDimension.R,
% R/SDMXTimeDimension-methods.R
\docType{class}
\name{SDMXTimeDimension}
\alias{SDMXTimeDimension}
\alias{SDMXTimeDimension-class}
\alias{SDMXTimeDimension,SDMXTimeDimension-method}
\title{Class "SDMXTimeD... |
6f6a40546a2f89da717ac5bb2d25e9149d988ab9 | b6631ea332d229c06907963f20bcd543566925f7 | /maininHit.R | 813e084d8b0c88e85add9e47fe56289f9be09146 | [] | no_license | biddyweb/fraudDetectionR | 9554d00a0e2c0093bc041720befc8cabf4793888 | d0b0a9b103fdd0118e014f068bdd8be62e788865 | refs/heads/master | 2021-01-22T11:04:59.413642 | 2014-09-21T07:38:20 | 2014-09-21T07:38:20 | null | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 565 | r | maininHit.R | library("HMM", lib.loc="D:/Program Files (x86)/R-3.1.1/library")
#Die folgenden Sourcedateien liegen im selben ordner
source('C:/Users/User/Desktop/Bachlorarbeit/R-program/createData.R')
source('C:/Users/User/Desktop/Bachlorarbeit/R-program/Cluster.R')
source('C:/Users/User/Desktop/Bachlorarbeit/R-program/Modell.R')
so... |
c34ce53031928884e747392a877e143c5dd27b55 | 5d879a2a106ef99b5ec4af84a49c525835d38361 | /man/elbow_detection.Rd | a8f59f1294faede7ce8d196154f340d12273b502 | [] | no_license | JinmiaoChenLab/uSORT | c32e6ce917a83ad061aad02d9ab0503f203435af | 5b8dbefc55f95525a533ebb4f2340c594eaf033f | refs/heads/master | 2020-04-17T03:17:35.499880 | 2016-10-12T00:47:03 | 2016-10-12T00:47:03 | 67,589,988 | 1 | 0 | null | null | null | null | UTF-8 | R | false | true | 692 | rd | elbow_detection.Rd | % Generated by roxygen2: do not edit by hand
% Please edit documentation in R/uSORT_GeneSelection.R
\name{elbow_detection}
\alias{elbow_detection}
\title{A elbow detection function}
\usage{
elbow_detection(scores, if_plot = FALSE)
}
\arguments{
\item{scores}{A vector of numeric scores.}
\item{if_plot}{Boolean determin... |
d08c0abcb93146d5c8d6b86ebda09a924a30b7cc | 738f3239dbdf6a79ceffe042d3b0c4974d10a088 | /R/stylo2.R | 1a7ef18532b61f0a980ba18b2831f4670c38230e | [
"MIT"
] | permissive | zozlak/styloWorkshop | cd685907824dfeba4250dfe6373c20563d26bfd2 | 9776a25ea3f3f9dd6bb4438f9acc63ac6e3595e7 | refs/heads/master | 2021-01-21T12:53:39.887357 | 2016-05-10T16:17:45 | 2016-05-10T16:17:45 | 49,637,495 | 0 | 0 | null | null | null | null | UTF-8 | R | false | false | 370 | r | stylo2.R | #' runs the stylo() function
#' @description Allows to read configuration from file without using GUI.
#' @param file path to the saved configuration
#' @param ... any other parameters to be passed to the
#' \code{\link{stylo}} function
#' @export
#' @import stylo
stylo2 = function(file = 'stylo_config.txt', ...){
... |
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