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ITSM

Author: Peter J Brockwell; Richard A Davis
Publisher: New York : Springer-Verlag, ©1991.
Edition/Format:   Computer file : 5.25 in. disc : Program : English : Version 3.0
Summary:
Interactive time series modelling evolved from the programs for the IBM PC written to accompany the book, Time series: theory and methods. The analysis of time series data is an important aspect of data analysis across a wide range of disciplines, including statistics, economics, engineering, and the biological sciences. This package provides an introduction to time series anaysis along with the programs.
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Details

Genre/Form: Software
Material Type: Program
Document Type: Computer File
All Authors / Contributors: Peter J Brockwell; Richard A Davis
ISBN: 0387974822 9780387974828 3540974822 9783540974826
OCLC Number: 33277836
Notes: Title from disk label.
Same software on one 3 1/2 in. and two 5 1/4 in. disks.
Description: 3 computer discs ; 3 1/2-5 1/4 in. + 1 user's guide
Details: System requirements: IBM-compatible PC, PC/XT, or PC/AT (mathematics co-processor recommended); 540K RAM minimum for applications; MS-DOS; CGA, EGA, VGA, or Hercules graphics card.
Contents: 1 Introduction.- 1.1 The Programs.- 1.2 System Requirements.- 1.2.1 Hard Disk Installation.- 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.- 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 ARAR.- 7.1 Introduction.- 7.1.1 Memory Shortening.- 7.1.2 Fitting a Subset Autoregression.- 7.2 Running the Program.- A Word6: A Screen Editor.- A.1 Basic Editing.- A.2 Alternate Keys.- A.3 Printing a File.- A.4 Merging Two or More Files.- A.5 Margins 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.- B Data Sets.
Other Titles: ITSM, an interactive time series modelling package for the PC
Responsibility: by Peter J. Brockwell and Richard A. Davis.
More information:

Abstract:

Designed for the analysis of linear time series and the practical modelling and prediction of data collected sequentially in time. - Easy to use menu system - Accessible to those with little or no  Read more...

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