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PURPOSE ^

Time Series Analysis (Ver 3.10)

SYNOPSIS ^

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DESCRIPTION ^

 Time Series Analysis (Ver 3.10)
 Schloegl A. (1996-2003,2008) Time Series Analysis - A Toolbox for the use with Matlab. 
 WWW: http://hci.tugraz.at/~schloegl/matlab/tsa/

    $Id: content.m 5090 2008-06-05 08:12:04Z schloegl $
    Copyright (C) 1996-2003,2008 by Alois Schloegl <a.schloegl@ieee.org>

  Time Series Analysis - a toolbox for the use with Matlab
   aar        adaptive autoregressive estimator 
   acovf       (*) Autocovariance function
   acorf (acf)    (*) autocorrelation function    
   pacf    (*) partial autocorrelation function, includes signifcance test and confidence interval
   parcor    (*) partial autocorrelation function
   biacovf    biautocovariance function (3rd order cumulant)
   bispec    Bi-spectrum 
   durlev      (*) solves Yule-Walker equation - converts ACOVF into AR parameters
   lattice     (*) calcultes AR parameters with lattice method
   lpc        (*) calculates the prediction coefficients form a given time series
   invest0    (*) a prior investigation (used by invest1)
   invest1    (*) investigates signal (useful for 1st evaluation of the data)
   selmo    (*) Select Order of Autoregressive model using different criteria
   histo    (*) histogram
   hup         (*) test Hurwitz polynomials
   ucp         (*) test Unit Circle Polynomials   
   y2res    (*) computes mean, variance, skewness, kurtosis, entropy, etc. from data series 
   ar_spa    (*) spectral analysis based on the autoregressive model
   detrend     (*) removes trend, can handle missing values, non-equidistant sampled data       
   flix    floating index, interpolates data for non-interger indices
   quantiles   calculates quantiles 

 Multivariate analysis (planned in future)
   mvar    multivariate (vector) autoregressive estimation 
   mvfilter    multivariate filter
   arfit2    provides compatibility to ARFIT [Schneider and Neumaier, 2001]

CROSS-REFERENCE INFORMATION ^

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