> library(kernlab)
> source("kernelDRest.r")  ## read R-code
> n <- 1000; m <- 1000     ## data size
> de <- matrix(rnorm(n),n,1)               # p_d: normal dist.
> nu <- matrix(runif(m,min=-2,max=2),m,1)  # p_n: uniform dist.
> lambda.list <- (2^seq(-5,5))/min(n,m)^(0.9)  # candicate of lambdas
> # estimate density ratio (DR) by KuLSIF()
> system.time(res <- KuLSIF(de,nu,lambda=lambda.list))   ## compute using single-core
    user       system  
    40.708     0.747     41.472 
> res    ## show results
> ## multi-core
> library(snow)
> ncore <- 24; cluster <- makeCluster(ncore,type="SOCK") ## compute using 24 cores
> system.time(res <- KuLSIF(de,nu,lambda=lambda.list,cluster=cluster)) 
   user       system  
   0.555      0.032     11.455 
> test <- seq(-3,3,l=100)       ## generate test points
> pred_w <- predict(res,test)   ## prediction of DR value
> pred_w    ## show estimated DR values
$r   # DR value
$nr  # normalized DR value