Do you really need the p-value or do you want to test at one
of the socially acceptable levels (i.e. .05 or .01). If all you want
is the test, use:
quantile(bootsample,c(0.025,0.975))
If the quantile range includes 0 then you decide there is no evidence
that the mean is different from zero, at the .05 level.
If the quantile range does not include 0 then you decide there is evidence
that the mean is different from zero, at the .05 level.
If you wanted to use .01 level then use:
quantile(bootsample,c(0.005,0.995))
Murray M Cooper
Richland Statistics
9800 N 24th St
Richland, MI, USA 49083
Mail: richs...@earthlink.net
----- Original Message -----
From: "Andreas Klein" <klein82...@yahoo.de>
To: <r-help@r-project.org>
Sent: Friday, January 09, 2009 4:36 AM
Subject: [R] How to compute Bootstrap p-values
Hello.
How can I compute the Bootstrap p-value for a two-sided test problem like
H_0: beta=0 vs. H_1: beta!=0 ?
Example for the sample mean:
x <- rnorm(100)
bootsample <- numeric(1000)
for(i in 1:1000) {
idx <- sample(1:100,100,replace=TRUE)
bootsample[i] <- mean(x[idx])
}
How can I compute the Bootstrap p-value for the mean of x?
H_0: "mean of x" = 0 vs. H_1: "mean of x" != 0
Thank you in advance.
Sincerely,
Andreas Klein.
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______________________________________________
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
