Nothing
##########################################################
# Compare weighted unbiased variance C version with R code
library(carSurv)
# Standard R-Funktion
weightSelfCovar <- function(x, y, w) {
meanX <- mean(x=x)
wMeanY <- weighted.mean(x=y, w=w)
firstSum <- sum(w*(x-meanX)*(y-wMeanY))
sumW <- sum(w)
firstSum / sumW
}
# Simple example:
# Does Rcpp version have identical results with R-Version Function?
set.seed(1)
response <- rnorm(250)
set.seed(5)
response2 <- rnorm(250)
set.seed(2)
weightResp <- runif(249)
weightResp <- weightResp / sum(weightResp)
weightResp[250] <- 1-sum(weightResp)
check1 <- all.equal(weightedCovarRcpp(x=response, y=response2, w=weightResp),
weightSelfCovar(x=response, y=response2, w=weightResp))
stopifnot(check1)
# Is Rcpp version faster than the regular variant?
library(microbenchmark)
microBench1 <- microbenchmark(weightedCovarRcpp(x=response, y=response2, w=weightResp),
weightSelfCovar(x=response, y=response2, w=weightResp),
times=25)
check2 <- summary(microBench1)$expr [which.min(summary(microBench1)$mean)]==
summary(microBench1)$expr[1]
stopifnot(check2)
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.