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fac_density_boot1

Factor density estimation using bootstrapping

CALLING SEQUENCE

res = fac_density_boot1(Z,meth,n_samples)

PARAMETERS

Input

* Z = a (nobs x k) matrix, collecting the variables

* meth = 'stan' if the user wants to perform the analysis on standardized variables

* n_samples = an integer, the number of resamples

Output

* res = a results tlist, with:

   - res('meth') = 'factor density via bootstrapping'

   - res('y') = the (nobs x k) matrix collecting the variables

   - res('standardization') = a boolean, indicating whether variables have been standardized

   - res('# of draws') = an integrer, the # of draws

   - res('factors') = a (nobs x nb_draws) matrix, the factor density

   - res('factors percentiles') = a (nobs x 5) matrix, the percentiles (2.5, 25, 50, 75 and 97.5)

DESCRIPTION

Factor density estimation using cross-section bootstrap.

EXAMPLE

global GROCERDIR 
load(GROCERDIR+'\data\esp_yields.dat')
X=esp_yields('series')
// provides the result of the resampling of a factors estimation by bootstrapping on Spanisk yields data, standardized, with 1000 draws:
res = fac_density_lko(X,'stan',1000)

AUTHOR

Éric Dubois 2022

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