[R] running Apply takes long time

[Hamid Ghorbani]

Dear users,
Below I  have a  matrix, called *mysim.obs*   (548 row and (1+nsim) columns, which its first column is my observation and the next  columns comprises simulation from the  fitted  model to first column). I want to evaluate *simpsonlognormpval* function on each column of  *mysim.obs*. For this I have used apply function.
Unfortunately, running apply  takes long time (i have several models, log-normal model in the following is just for  explanation).
Many thanks in advance.
Yours,
Hamid
------------

simpsonlognormpval <- function(xx){
    # numerical integral using Simpson's rule
    # assume a < b and n is an even positive integer
          n<-10000
a<-0;b<- 25*max(xx) #because log-normal distribution has heavy tail
meanlog = -0.216
sdlog = 1.4245521
    h <- (b-a)/n
    x <- seq(a, b, by=h)
                y <- (plnorm(x, meanlog = meanlog0 , sdlog =sdlog0 )-ecdf(xx)(x))^2
    if (n == 2) {
        s <- (y[1] + 4*y[2] +y[3])
    } else {
        s <- y[1] + y[n+1] + 2*sum(y[seq(2,n,by=2)]) + 4 *sum(y[seq(3,n-1, by=2)])
    }
    s <- s*h/3
    return(s)
}
 
>meanlog0 = -0.216
>sdlog0 = 1.4245521
>nsim=100000
>my.obs<-rexp( 548,0.5*lambda ) #my.obs is acctually an observed sample, here I just replaced it
>mysim.obs<-cbind(my.obs ,matrix(rlnorm(548*nsim, meanlog = meanlog0, sdlog =sdlog0),548,nsim))

>fsimpsonlognormpval <-apply( mysim.obs, 2,simpsonlognormpval )
> fsimpsonlognormpval[1]
>lognormpval<-mean(fsimpsonlognormpval[2:(nsim+1)]>fsimpsonlognormpval[1])
>lognormpval 
	[[alternative HTML version deleted]]