[R-sig-eco] Average Regression and the bootstrap

[Johannes Radinger]

Hej again,

thank you that I know now that this is called parametric bootstrap.

I am very unsure if I am doing right. So I tried to write a bootstrap
script which is now as follows:

data <- data.frame(Y,X1a,X1b,X2)

X1.gen <- function()
{
	X1 <- function()runif(length(X1a), X1a, X1b)
}

statistic <- function()
{
	X1 <- function()runif(length(X1a), X1a, X1b)
	model <- lm(Y~X1())		
}

regression.boot <- boot(data, statistic, R=1000, sim="parametric", ran.gen=X1.gen)



It is somehow incomplete...not sure how to proceed, as I am really new to bootstrap and R. Maybe I am doing totally wrong... not sure at all.
Just to get it clear to me: Bootstrap resamples from the finite dataset with the "dynamic" X1 (170 cases in my example) and during each sampling a new X1 is calculated (runif) for the case? 
Maybe someone can help me here...

thanks to you all
Johannes






-------- Original-Nachricht --------
> Datum: Tue, 30 Aug 2011 07:00:44 -0500
> Von: "Dixon, Philip M [STAT]" <pdixon at iastate.edu>
> An: "r-sig-ecology at r-project.org" <r-sig-ecology at r-project.org>
> Betreff: [R-sig-eco] Average Regression and the bootstrap

> Johannes,
> 
> You are doing what many folks call the parametric bootstrap.  The
> bootstrap that resamples the data is the non-parametric bootstrap.   Often it is
> easier to code by hand, as you have done.  If you want access to all the
> helper functions for the bootstrap, you can use boot() in the boot library and
> specify sim='parametric'.  The details of your random uniform distribution
> go in the function specified in the ran.gen= argument.  Once you've
> generated the bootstrap samples (parametric or nonparametric), there is no
> difference in subsequent processing.
> 
> Best wishes,
> Philip Dixon
> 
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