Automatic Spectral Analysis: pgain(ar,ma) - File Exchange

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Highlights from
Automatic Spectral Analysis

(X+X')/2; end % end lyap
90*ceil(max(phase)/90); try,...
ARMLfit(rcs,ng,xg,rc0,lag_max... The conditional-likelihood fit.
ARShat_misd(ng,xg,L,lag_max,s... ARSHAT_MISD AR models of increasing order from measurements with missing data
ARhat_misd(ng,xg,rcinit,rc0,l... ARHAT_MISD AR model from measurements with missing data
ARselv(x,Lmax,M,settings) ARselv Parameter estimation and order selection for vector AR models.
KLDiscrepancy(ar_est,ma_est,v... KLDiscrepancy Kullback-Leibler discrepancy.
KLDiscrepancyv(varargin) KLDiscrepancyv Kullback-Leibner discrepancy and index
KLIndex(ar_est,ma_est,varx_es... KLIndex Kullback-Leibler index.
KLIndex_hat(ys,ar,ma,vary) KLINDEX_HAT Estimate of the Kullback-Leibler index
LikelihoodR(ys,ar0,ma0,var0,a... LIKELIHOODR Likelihood ratio between estimated ARMA models
YWoutput(cov,par) function YW_out = YWoutput(cov,par)
[ar,ma,ASAsellog,ASAcontrol]=... ARH2ARMA ARMA model identification
[ar,ma,ASAsellog,ASAcontrol]=... ARMASEL_RS ARMAsel model identification
[cor,gain,ASAcontrol]=arma2co... ARMA2COR_E ARMA parameters to autocorrelations
[mapar,var]=cor2b2(cor,maxite...
[pc,R0,P,Pb]=burgv(x,Lmax) BURGV
ar2arset_e(varargin) AR2ARSET_E AR parameters to optimal lower-order AR models
ar_ma2rc(ar,ma,n_obs) [Used internally by KLDiscrepancy, KLIndex, KLIndex_hat]
arh2ar(varargin) ARH2AR AR model identification
arh2ma(varargin) ARH2MA MA model identification
armafilterv(x,a,b,prev_y); ARMAFILTERV Digital ARMA filter for matrix-valued signals
ch*z;
chol(x)';
cic(varargin) CIC_S Finite sample order selection criterion for segments
complex2real(xc) COMPLEX2REAL Translates complex data into real data
convol_e(varargin) CONVOL_E Convolution sum
convolrev_e(varargin) CONVOLREV_E Convolution sum with one vector reversed
convv(a,b);
cov2pcv(cov)
cumprod([var 1-rc(2:L+1).^2] ...
dets(a)
durbin2(ar_long,ar_ini,ma_ord... function [ar_d2,ma_d2,pe_n] = durbin2(ar_long,ar_ini,ma_order,ASAcontrol)
example_process(name,varargin... EXAMPLE_PROCESS generates an example process
gendata(a,b,n_obs,g,gar)
gendatav(pc,R0,nobs)
irr2grid(ti,xi,T); IRR2GRID Conversion of irregularly sampled data to missing data
iseven(x)
likelihoodR_mod(ys,ar0,ar1,va... LIKELIHOODR Likelihood ratio between estimated ARMA models
ma2covv(ma,Peps,ncov) function cov = ma2covv(ma,Peps,ncov)
mat2sig(xmat); MAT2SIG From matrix representation to signal representation
matmat(linmap,siz,varargin) MATMAT Matrix of a linear mapping from a matrix to a matrix.
missing2seg(tg,xg) MISSING2SEG Extracts segments from missing data.
modeltype(ar,ma) MODELTYPE provides a description for an ARMA-model
moderr_e(varargin) MODERR_E Model error
moderrv(pchat,R0hat,pc,R0,nob... moderrv Vector Model Error for AR models.
par2covv(par,parb,R0)
par2pcv(par,parb,R0)
pc2arset(pc,R0,req_order) PC2ARSET AR partial correlations to AR models
pc2covv(pc,R0,ncov)
pc2parv(pc,R0)
pc2rcv(pc,R0)
pc2resv(pc,R0)
pc2specv(pc,R0,fn,T)
pc2xcovv(pc,R0,a,b,ncov)
pc2xspecv(pc,R0,a,b,fn,T)
pgain(ar,ma) PGAIN Power gain of ARMA process [ar,ma]
prodsumv(a,b);
psd2ar(h,p) PSD2AR Power Spectral Density Function to AR parameters.
rc2parv(rc,rcb)
rc2pcv(rc,R0)
s(dim); end
setfields(struc_in,varargin) function struc_out = setfields(struc_in,checkfields,varargin)
sig2ar_misd(ng,xg,L,varargin)... SIG2AR_MISD Estimation of AR models from measurements with missing data.
sig2mat(xsig); SIG2MAT From signal representation to matrix representation.
spec2covv(h) function cov = spec2covv(h)
sumARMA(varargin) SUMARMA Sum of ARMA-processes
timesv(M,a);
traces(a)
transposeLTI(a) function c = transposeLTI(a)
~nons;
Contents.m
Contents.m
Contents.m
Contents.m
KLI_demo.m
contents.m
data_segments.m
detection_demo.m
misdata_demo.m
prederrAR.m
redstat_demo.m
segments_demo.m
segments_unequal_demo.m
subband_demo.m
vectorsM_demo.m
vectors_demo.m
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from Automatic Spectral Analysis by Stijn de Waele
Automatic spectral analysis for irregular sampling/missing data, analysis of spectral subband.

pgain(ar,ma)

function g = pgain(ar,ma)

%PGAIN Power gain of ARMA process [ar,ma]
%   The power gain is the ratio between the power of input
%   and output for an ARMA-system [ar,ma] when the input
%   is white noise.

[dummy,g] = arma2cor(ar,ma,0);

Highlights from Automatic Spectral Analysis

Highlights from
Automatic Spectral Analysis