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+% Time Series Analysis - A toolbox for the use with Matlab and Octave.
+%\r
+% $Id: contents.m 5090 2008-06-05 08:12:04Z schloegl $
+% Copyright (C) 1996-2004,2008 by Alois Schloegl <a.schloegl@ieee.org>\r% WWW: http://hci.tugraz.at/~schloegl/matlab/tsa/
+%\r
+% This program is free software: you can redistribute it and/or modify
+% it under the terms of the GNU General Public License as published by
+% the Free Software Foundation, either version 3 of the License, or
+% (at your option) any later version.
+%
+% This program is distributed in the hope that it will be useful,
+% but WITHOUT ANY WARRANTY; without even the implied warranty of
+% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
+% GNU General Public License for more details.
+%
+% You should have received a copy of the GNU General Public License
+% along with this program. If not, see <http://www.gnu.org/licenses/>.
+% \r
+%
+% 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)
+% rmle AR estimation using recursive maximum likelihood function
+% 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
+%
+%
+% Multivariate analysis
+% adim adaptive information matrix (inverse correlation matrix)
+% mvar multivariate (vector) autoregressive estimation
+% mvaar multivariate adaptvie autoregressive estimation using Kalman filtering
+% mvfilter multivariate filter
+% mvfreqz multivariate spectra
+% arfit2 provides compatibility to ARFIT [Schneider and Neumaier, 2001]
+%
+%
+% Conversions between Autocorrelation (AC), Autoregressive parameters (AR),
+% prediction polynom (POLY) and Reflection coefficient (RC)
+% ac2poly (*) transforms autocorrelation into prediction polynom
+% ac2rc (*) transforms autocorrelation into reflexion coefficients
+% ar2rc (*) transforms autoregressive parameters into reflection coefficients
+% rc2ar (*) transforms reflection coefficients into autoregressive parameters
+% poly2ac (*) transforms polynom to autocorrelation
+% poly2ar (*) transforms polynom to AR
+% poly2rc (*)
+% rc2ac (*)
+% rc2poly (*)
+% ar2poly (*)
+%
+% Utility functions
+% sinvest1 shows the parameter calculated by INVEST1
+%
+% Test suites
+% tsademo demonstrates INVEST1 on EEG data
+% invfdemo demonstration of matched, inverse filtering
+% bisdemo demonstrates bispectral estimation
+%
+% (*) indicates univariate analysis of multiple data series (each in a row) can be processed.
+% (-) indicates that these functions will be removed in future
+%
+% REFERENCES (sources):
+% http://www.itl.nist.gov/
+% http://mathworld.wolfram.com/
+% P.J. Brockwell and R.A. Davis "Time Series: Theory and Methods", 2nd ed. Springer, 1991.
+% O. Foellinger "Lineare Abtastsysteme", Oldenburg Verlag, Muenchen, 1986.
+% F. Gausch "Systemtechnik", Textbook, University of Technology Graz, 1993.
+% M.S. Grewal and A.P. Andrews "Kalman Filtering" Prentice Hall, 1993.
+% S. Haykin "Adaptive Filter Theory" 3ed. Prentice Hall, 1996.
+% E.I. Jury "Theory and Application of the z-Transform Method", Robert E. Krieger Publishing Co., 1973.
+% M.S. Kay "Modern Spectal Estimation" Prentice Hall, 1988.
+% Ch. Langraf and G. Schneider "Elemente der Regeltechnik", Springer Verlag, 1970.
+% S.L. Marple "Digital Spetral Analysis with Applications" Prentice Hall, 1987.
+% C.L. Nikias and A.P. Petropulu "Higher-Order Spectra Analysis" Prentice Hall, 1993.
+% M.B. Priestley "Spectral Analysis and Time Series" Academic Press, 1981.
+% T. Schneider and A. Neumaier "Algorithm 808: ARFIT - a matlab package for the estimation of parameters and eigenmodes of multivariate autoregressive models"
+% ACM Transactions on Mathematical software, 27(Mar), 58-65.
+% C.E. Shannon and W. Weaver "The mathematical theory of communication" University of Illinois Press, Urbana 1949 (reprint 1963).
+% W.S. Wei "Time Series Analysis" Addison Wesley, 1990.
+%
+%
+% REFERENCES (applications):
+% [1] A. Schlögl, B. Kemp, T. Penzel, D. Kunz, S.-L. Himanen,A. Värri, G. Dorffner, G. Pfurtscheller.
+% Quality Control of polysomnographic Sleep Data by Histogram and Entropy Analysis.
+% Clin. Neurophysiol. 1999, Dec; 110(12): 2165 - 2170.
+% [2] Penzel T, Kemp B, Klösch G, Schlögl A, Hasan J, Varri A, Korhonen I.
+% Acquisition of biomedical signals databases
+% IEEE Engineering in Medicine and Biology Magazine 2001, 20(3): 25-32
+% [3] Alois Schlögl (2000)
+% The electroencephalogram and the adaptive autoregressive model: theory and applications
+% Shaker Verlag, Aachen, Germany,(ISBN3-8265-7640-3).
+%
+% Features:
+% - Multiple Signal Processing
+% - Efficient algorithms
+% - Model order selection tools
+% - higher (3rd) order analysis
+% - Maximum entropy spectral estimation
+% - can deal with missing values (NaN's)
git://git.creatis.insa-lyon.fr / CreaPhase.git / blobdiff