ITSM for Windows - Brockwell, Peter J.

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Auteur(s) : Brockwell, Peter J. - Davis, Richard A.

Editeur : Springer Us, New York, N.Y.

Langue : Anglais

Parution : 31/07/1994

Format : Moyen, de 350g à 1kg

Nombre de pages : 132

Expédition : 213

Dimensions : 23.5 x 15.5 x 0.8

ISBN : 0387943374

Résumé :
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Biographie:

Peter J. Brockwell and Richard A. Davis are Fellows of the American Statistical Association and the Institute of Mathematical Statistics and elected members of the International Statistics institute. Richard A. Davis is the current President of the Institute of Mathematical Statistics and, with W.T.M. Dunsmuir, winner of the Koopmans Prize. Professors Brockwell and Davis are coauthors of the widely used advanced text, Time Series: Theory and Methods, Second Edition (Springer-Verlag, 1991).

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Sommaire:
1 Introduction.- 1.1 The Programs.- 1.2 System Requirements.- 1.2.1 Installation.- 1.2.2 Running ITSM.- 1.2.3 Printing Graphs.- 1.3 Creating Data Files.- 2 PEST.- 2.1 Getting Started.- 2.1.1 Running PEST.- 2.1.2 PEST Tutorial.- 2.2 Preparing Your Data for Modelling.- 2.2.1 Entering Data.- 2.2.2 Filing Data.- 2.2.3 Plotting Data.- 2.2.4 Transforming Data.- 2.3 Finding a Model for Your Data.- 2.3.1 The ACF and PACF.- 2.3.2 Entering a Model.- 2.3.3 Preliminary Parameter Estimation.- 2.3.4 The AICC Statistic.- 2.3.5 Changing Your Model.- 2.3.6 Parameter Estimation; the Gaussian Likelihood.- 2.3.7 Optimization Results.- 2.4 Testing Your Model.- 2.4.1 Plotting the Residuals.- 2.4.2 ACF/PACF of the Residuals.- 2.4.3 Testing for Randomness of the Residuals.- 2.5 Prediction.- 2.5.1 Forecast Criteria.- 2.5.2 Forecast Results.- 2.5.3 Inverting Transformations.- 2.6 Model Properties.- 2.6.1 ARMA Models.- 2.6.2 Model ACF, PACF.- 2.6.3 Model Representations.- 2.6.4 Generating Realizations of a Random Series.- 2.6.5 Model Spectral Density.- 2.7 Nonparametric Spectral Estimation.- 2.7.1 Plotting the Periodogram.- 2.7.2 Plotting the Cumulative Periodogram.- 2.7.3 Fisher's Test.- 2.7.4 Smoothing to Estimate the Spectral Density.- 3 SMOOTH.- 3.1 Introduction.- 3.2 Moving Average Smoothing.- 3.3 Exponential Smoothing.- 3.4 Removing High Frequency Components.- 4 SPEC.- 4.1 Introduction.- 4.2 Bivariate Spectral Analysis.- 4.2.1 Estimating the Spectral Density of Each Series.- 4.2.2 Estimating the Absolute Coherency Spectrum.- 4.2.3 Estimating the Phase Spectrum.- 5 TRANS.- 5.1 Introduction.- 5.2 Computing Cross Correlations.- 5.3 An Overview of Transfer Function Modelling.- 5.4 Fitting a Preliminary Transfer Function Model.- 5.5 Calculating Residuals from a Transfer Function Model.- 5.6 LS Estimation and Prediction with Transfer Function Models.- 6 ARVEC.- 6.1 Introduction.- 6.1.1 Multivariate Autoregression.- 6.2 Model Selection with the AICC Criterion.- 6.3 Forecasting with the Fitted Model.- 7 BURG.- 7.1 Introduction.- 8 ARAR.- 8.1 Introduction.- 8.1.1 Memory Shortening.- 8.1.2 Fitting a Subset Autoregression.- 8.2 Running the Program.- 9 LONGMEM.- 9.1 Introduction.- 9.2 Parameter Estimation.- 9.3 Prediction.- 9.4 Simulation.- 9.5 Plotting the Model and Sample ACVF.- Appendix A: The Screen Editor WORD6.- A.1 Basic Editing.- A.2 Alternate Keys.- A.3 Printing a File.- A.4 Merging Two or More Files.- A.5 Margins and Left and Centre Justification.- A.6 Tab Settings.- A.7 Block Commands.- A.8 Searching.- A.9 Special Characters.- A.10 Function Keys.- A. 11 Editing Information.- Appendix B: Data Sets.