| 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 |