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
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