From dimitris.rizopoulos at med.kuleuven.be  Fri Feb 23 13:20:24 2007
From: dimitris.rizopoulos at med.kuleuven.be (Dimitris Rizopoulos)
Date: Fri, 23 Feb 2007 13:20:24 +0100
Subject: [Rd] Bootstrapping stepAIC() with glm.nb()
Message-ID: <002601c75744$fea7c930$0540210a@www.domain>

Dear all,

I would like to Boostrap the stepAIC() procedure from package MASS for 
variety of model objects, i.e.,

fn <- function(object, data, B = 2){
    n <- nrow(data)
    res <- vector(mode = "list", length = B)
    index <- sample(n, n * B, replace = TRUE)
    dim(index) <- c(n, B)
    for (i in 1:B) {
        up.obj <- update(object, data = data[index[, i], ])
        res[[i]] <- stepAIC(up.obj, trace = FALSE)
    }
    res
}

####################

library(MASS)


# 'glm' objects
x1 <- runif(100, -4, 4)
x2 <- runif(100, -4, 4)
y <- 1 + 2 * x1 + rnorm(100, sd = 3)
dat <- data.frame(y, x1, x2)
glmFit <- glm(y ~ x1 + x2, data = dat)
fn(glmFit, data = dat)

# 'aov' objects
quine.hi <- aov(log(Days + 2.5) ~ .^4, quine)
fn(quine.hi, data = quine)


However, for "negbin" objects returned by glm.nb() the following 
problem occurs:

quine.nb <- glm.nb(Days ~ .^4, data = quine)
fn(quine.nb, data = quine)


Any hints to overcome this are greatly appreciated.

Thanks in advance,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

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Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm 


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[Rd] Bootstrapping stepAIC() with glm.nb()
Dimitris Rizopoulos