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factor_density_lko

CALLING SEQUENCE

[res] = factor_density_lko(arg1,..., argn)

PARAMETERS

Input

* argi = arguments which can be:

  - a time series

  - a string vector, collecting the names of the variables

  - a real (n x k) matrix, collecting the values of the variables

  - nb_draws=xx' where xx is the number of samples drawn (optional; default:1000)

  - 'stan' if the user wants to perform the analysis on standardized variables (optional; default: no standardization)

  - 'tau=xx' with xx is the rejection rate of a variable (optional; default: 0.1)

  - the string 'noprint' if the user doesn't want to plot the results of the regression

Output

* res = a results tlist, with:

   - res('meth') = 'factor density via leave k-out resampling'

   - 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('rejection prob.') = a real, the rejection probability

   - 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)

   - res('k out resampling') = a (nobs x nb_draws) matrix, the number of variables kept at each draw

   - res('namey ') = name of th variables

   - res('prests') = boolean indicating the presence or absence of a time series in the variables list

   - res('bounds') = if there is a timeseries in the regression, the bounds of the regression

DESCRIPTION

Factor density resampling using the leave k-out method (rejection prob.=tau).

EXAMPLE

global GROCERDIR 
load(GROCERDIR+'\data\esp_yields.dat')
// provides the result of the resampling by the leave k-out method on factors estimation on Spanisk yields data, standardized, with 1000 draws and a 0.1 rejection probability:
res = fac_density_lko(esp_yields,'stan');
// provides the result of the resampling by the leave k-out method on factors estimation on Spanisk yields data, standardized, with 10000 draws and a 0.05 rejection probability:
res = fac_density_lko(esp_yields,'stan','tau=0.05','n_draws=10000');

AUTHOR

Éric Dubois 2022

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