hrbrmstr

viridis_pal <- function(alpha=1) {
  function(n) {
    viridis(n, alpha)
  }
}


scale_color_viridis <- function(..., alpha=1, discrete=TRUE) {
  if (discrete) {
    discrete_scale("colour", "viridis", viridis_pal(alpha), ...)

jennybc

#' ---
#' output:
#'   html_document:
#'     keep_md: TRUE
#' ---

#+ include = FALSE
library(dplyr)

#' Responses to [my

meyera

## Curated stuff:
## * MetaCran: http://www.r-pkg.org/
## * List of Packages gathered by Garret G.: https://github.com/rstudio/RStartHere
## * List of popular packages https://awesome-r.com/
## * List of DataScience R tutorials https://github.com/ujjwalkarn/DataScienceR
## * List of machine elearning tutorials by subject: https://ujjwalkarn.github.io/Machine-Learning-Tutorials/

## Reproducible package management for R:
install.packages("devtools")
install.packages("tidyverse")

araastat

#’ Create a Kaplan-Meier plot using ggplot2
#’
#’ @param sfit a \code{\link[survival]{survfit}} object
#’ @param returns logical: if \code{TRUE}, return an ggplot object
#’ @param xlabs x-axis label
#’ @param ylabs y-axis label
#’ @param ystratalabs The strata labels. \code{Default = levels(summary(sfit)$strata)}
#’ @param ystrataname The legend name. Default = “Strata”
#’ @param timeby numeric: control the granularity along the time-axis
#’ @param main plot title