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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
• View all files