# [R] running Apply takes long time

Hamid Ghorbani h@m|d332000 @end|ng |rom y@hoo@com
Sun Jun 30 11:28:01 CEST 2019

```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
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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 + 4*y +y)
} else {
s <- y + 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
>lognormpval<-mean(fsimpsonlognormpval[2:(nsim+1)]>fsimpsonlognormpval)
>lognormpval
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