parboot GOF test

[Emily Terry]

Hello

I'm not sure if anyone can help, I am running a parametric bootstrap GOF test. I am unable to get more than nsim=99, and I am not sure why? Please see the following: 

This is my goodness of fit test:

(fm <- distsamp(~1 ~ndvi_avg, keyfun="hazard", umf)) 

# Function returning three fit-statistics. 

fitstats <- function(fm) { 

observed <- getY(fm@data) 

expected <- fitted(fm) 

resids <- residuals(fm) 

sse <- sum(resids^2) 

chisq <- sum((observed - expected)^2 / expected) 

freeTuke <- sum((sqrt(observed) - sqrt(expected))^2) 

out <- c(SSE=sse, Chisq=chisq, freemanTukey=freeTuke) 

return(out) } (pb <- parboot(fm, fitstats, nsim=100, report=1))

I can do up to nsim=99, and then I try nsim=100 which results in the following:

> (pb <- parboot(fm, fitstats, nsim=100, report=1)) 

t0 = 103.385 540.1714 70.38591 

 Running in parallel on 3 cores. Bootstrapped statistics not reported.

Am I doing something wrong? 

Many thanks

Emily

[Ken Kellner]

Hi Emily,

You didn't do anything wrong. parboot switches to parallel processing automatically when you have nsim >= 100, and when parallel processing, you can't incrementally report the statistics in the console. The final output should be fine. If you want to avoid this you can set the argument "parallel=FALSE" in your call to parboot().

Ken