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specvarma

compute parametric spectral analysis of time series

CALLING SEQUENCE

[rspec]=specvarma(result,arg1,...,argn)

PARAMETERS

Input

* result = tlist estimation result from OLS,VAR or VARMA methods (warning: no constant is allowed !)

* arg1,...,argn = arguments which can be:

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

  - optional arguments that can be the following:

    .'trunc=xx' : lag window size (the default value is k=round(sqrt(T)))

    .'weight=xx' : (N x 1) vector of weights (equal weights by default) for cohesion

    .spec=1' : plot spectrum

    .'cospe=1'     : plot cospectrum

    .'dcorr=1' : plot dynamic correlation

    .'phase=1' : plot phase spectrum

    .'coher=1' : plot coherency

    .'cohes=1' : plot cohesion

    .'ic =1' : performs delta-method estimation of confidence band

 

Output

* rspec = a results tlist with

  - rspec('cospe') = matrix of cospectra

  - rspec('cohes') = matrix of cohesion (if more than one TS)

  - rspec('coher') = matrix of coherence (if more than one TS)

  - rspec('dcorr') = matrix of dynamic correlations (if more than one TS)

  - rspec('phase') = matrix of standardized phase spectrum (if more than one TS)

  - rspec('order') = order of arrival of variable in cross-products

  - rspec('ucohes') = matrix of upper bound for cohesion (compute by block-bootstrap)

  - rspec('lcohes') = matrix of lower bound for cohesion (compute by block-bootstrap)

  - rspec('ucoher') = matrix of upper bound for coherency (compute by block-bootstrap)

  - rspec('lcoher') = matrix of lower bound for coherency (compute by block-bootstrap)

  - rspec('ucospe') = matrix of upper bound for cospectra (compute by block-bootstrap)

  - rspec('lcospe') = matrix of upper bound for cospectra (compute by block-bootstrap)

  - rspec('udcorr') = matrix of upper bound for dynamic correlations (compute by block-bootstrap)

  - rspec('ldcorr') = matrix of lower bound for dynamic correlations (compute by block-bootstrap)

  - rspec('uphase') = matrix of upper bound for phase spectrum (compute by block-bootstrap)

  - rspec('lphase') = matrix of lower bound for phase spectrum (compute by block-bootstrap)

DESCRIPTION

This function provides standard spectral related tools to analyse stationary time series. It performs: spectrum, cospectrum, phase spectrum, coherence, dynamic correlation and cohesion. The method is parametric: the function is based upon the priori estimation of a var or varma model, whose results are taken as an entry of function specvarma.

EXAMPLE

load(GROCERDIR+'\data\specgdp.dat');
 
// get the names of the variables available in the database
lvar =dblist(GROCERDIR+'\data\specgdp.dat');
 
// transforms by log and first difference
// & center data
for i = 1:size(lvar,1)
   execstr('dl'+lvar(i)+' = delts(log('+lvar(i)+'))')
   execstr('dl'+lvar(i)+'_m = dl'+lvar(i)+' - mean(dl'+lvar(i)+')')
end
 
// estimate var(4) model with no constant
rvar = VAR(4,'endo=dlfr_m;dlger_m;dlit_m;dlsp_m','nocte','noprint')
 
// estimates and prints cohesion of var model
// and compute 95% interval confidence band
rspec = specvarma(rvar,'cohes=1','ic=1');
// Example taken from function specvarma_d. A var model is estimated on
// the variations of logarithm of the French, German, Italian and Spanish GDP.
// The cohesion of these 4 series is plotted ('cohes=1') with the confidence band calculated by the mean of the delta method.

AUTHOR

Emmanuel Michaux 2005

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