Library: | stats |
See also: | uniform |
Quantlet: | bootstrap | |
Description: | This macro gives bootstrap replications of different kind for models without known distribution of 'eps' |
Usage: | beps = bootstrap(eps,nboot,kind) | |
Input: | ||
eps | n x 1 vector , the sample that has to be bootstraped | |
nbbot | scalar , the wished number of bootstrap replications | |
kind | string , saying what kind of bootstrap is wished: "wild" (using golden cut rule), "permut" (simple permutation), "naive" (naive bootstrap) | |
Output: | ||
beps | n x nb matrix, bootstrap replications |
library("stats") randomize(12345) n = 150 eps = normal(n) beps = bootstrap(eps,99,"wild") beps
Contents of bootstrap replications for eps
Library: | stats |
See also: | uniform |