 # Bootstrap sample

Hell,

I am using Maxboot to compute the bootstrapped estimates of parameters of a maximum likelihood function, but I want to retrieve all the random samples that were used to compute these estimates.

Any help would be appreciated.

Thanks.

Sincerely,

0

With some programming it would only be possible to retrieve the number of times each observation occurred in the re-sampling.

If it is important to look at each sample in the re-sampling, put the call to Maxlik in a loop and generate the bootstrap samples yourself using the GAUSS function exctsmpl():

x0 = {};

for I(1,100,1);

subsample = exctsmpl("originalData","newData",100);

{ x,f,g,cov,ret } = maxlik("newData",0,&lpr,x0);

if ret == 0;

x0 = x0 | x';

endif;

endfor;

print "bootstrap estimate";

print meanc(x0);

print "standard errors";

print sqrt(diag(varcovx(x0))); 0

With some programming it would only be possible to retrieve the number of times each observation occurred in the re-sampling.

If it is important to look at each sample in the re-sampling, put the call to Maxlik in a loop and generate the bootstrap samples yourself using the GAUSS function exctsmpl():

x0 = {};

for I(1,100,1);

subsample = exctsmpl("originalData","newData",100);

{ x,f,g,cov,ret } = maxlik("newData",0,&lpr,x0);

if ret == 0;

x0 = x0 | x';

endif;

endfor;

print "bootstrap estimate";

print meanc(x0);

print "standard errors";

print sqrt(diag(varcovx(x0))); ### Have a Specific Question?

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