>stats:::.makeNamesTsfunction(...){l<-as.list(substitute(list(...)))[-1L]nm<-names(l)fixup<-if(is.null(nm))seq_along(l)elsenm==""dep<-sapply(l[fixup],function(x)deparse(x)[1L])if(is.null(nm))return(dep)if(any(fixup))nm[fixup]<-dep nm}<bytecode:0x38140d0><envi...
workflow data-science r pipeline reproducible-research high-performance-computing make rstats r-package reproducibility targets peer-reviewed r-targetopia Updated Feb 10, 2025 R sparklyr / sparklyr Star 960 Code Issues Pull requests Discussions R interface for Apache Spark machine-learning r spark...
Code Issues Pull requests Discussions H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Sup...
The R stats package was employed to perform Pearson correlation analysis of serial dilutions. The heatmap analysis was directly performed using MetaboAnalystR. Identification and matching of compounds to the list of standards were based on the exact matching of InChIKeys, deviation of retention ...
For example, for the “stats” package, these ways will be: packageDescription("stats") help(package = "stats") Powered By 2. What are R Repositories? A repository is a place where packages are located so you can install them from it. Although you or your organization might have a loc...
package = "ggthemr", palette = "dust", title.text = "Composition of MPAA ratings for different genres" ) ggbarstats 功能类似于ggpiestats,图形非常好康。 set.seed(123) library(ggplot2) # plot ggstatsplot::ggbarstats( data = ggstatsplot::movies_long, ...
stats4 (Built-in) 4.3.3 tools (Built-in) 4.3.3 utils (Built-in) 4.3.3 R packages that are supported in Power BI (non-Premium and non-Fabric backed workspaces) and Sov. Clouds The following table shows which packages are supported in the Power BI service. Expand table PackageVersionLi...
x<-sort.int(x,partial=unique(c(lo,hi)))[lo:hi]}.Internal(mean(x))}<bytecode:0x000000000ec0bbc8><environment:namespace:base>
To perform the chi-squared test in R, we need to use the chisq.test() function of the stats package. The steps are as follows: 1. Create a contingency table with the categorical variables in interest using the table() function of the base R: table = table(df["var_1"], df["var_...
(WRS2) # plot ggstatsplot::ggwithinstats( data = WineTasting, x = Wine, y = Taste, title = "Wine tasting", caption = "Data source: `WRS2` R package", ggtheme = ggthemes::theme_fivethirtyeight(), ggstatsplot.layer = FALSE, messages = FALSE, ggsignif.args = list(textsize = 3...