use Rprof to determine where your function is spending time.
What is the problem you are trying to solve?
Sent from my iPhone.
On Jun 23, 2010, at 5:21, li li <hannah....@gmail.com> wrote:
Dear all,
I have the following program for a multiple comparison procedure.
There are two functions for the two steps. First step is to
calculate the
critical values,
while the second step is the actual procedure [see below: program
with two
functions].
This work fine. However, However I want to put them into one
function
for the convenience
of later use [see below: program with one function]. Some how the big
function works extremely
slow. For example I chose
m <- 10
rho <- 0.1
k <- 2
alpha <- 0.05
pvaluessort <- sort(1-pnorm(rnorm(10))
Is there anything that I did wrong?
Thank you!
Hannah
######Program with two functions############
## first step
library(mvtnorm)
cc_f <- function(m, rho, k, alpha) {
cc_z <- numeric(m)
var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T)
for (i in 1:m){
if (i <= k) {cc_z[i] <- qmvnorm((k*(k-1))/(m*(m-1))*alpha,
tail="upper",
sigma=var)$quantile} else
{cc_z[i] <- qmvnorm((k*(k-1))/((m-i+k)*(m-i+k-1))*alpha,
tail="upper", sigma=var)$quantile}
}
cc <- 1-pnorm(cc_z)
return(cc)
}
## second step
pair_kFWER=function(m,crit_cons,pvaluessort){
k=0
while((k <m)&&(crit_cons[m-k] < pvaluessort[m-k])){
k=k+1
}
return(m-k)
}
###########################################
##############Program with one function ##############
pair_kFWER=function(m,alpha,rho,k,pvaluessort){
library(mvtnorm)
cc_z <- numeric(m)
var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T)
for (i in 1:m){
if (i <= k) {cc_z[i] <- qmvnorm((k*(k-1))/(m*(m-1))*alpha,
tail="upper",
sigma=var)$quantile} else
{cc_z[i] <- qmvnorm((k*(k-1))/((m-i+k)*(m-i+k-1))*alpha,
tail="upper", sigma=var)$quantile}
}
crit_cons <- 1-pnorm(cc_z)
k=0
while((k <m)&&(crit_cons[m-k] < pvaluessort[m-k])){
k=k+1
}
return(m-k)
}
#####################################################
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and provide commented, minimal, self-contained, reproducible code.
