ITSM for Windows

A User's Guide to Time Series Modelling and Forecasting
1994
ISBN: 978-0-387-94337-4
Verlag: Springer

Buch, Englisch, 118 Seiten, Book w. online files / update, Format (B × H): 155 mm x 235 mm, Gewicht: 213 g

The analysis of time series data is an important aspect of data analysis across a wide range of disciplines, including statistics, mathematics, business, engineering, and the natural and social sciences. This package provides both an introduction to time series analysis and an easy-to-use version of a well-known time series computing package called Interactive Time Series Modelling. The programs in the package are intended as a supplement to the text TimeSeries: Theory and Methods, 2nd edition, also by Peter J. Brockwell and Richard A. Davis. Many researchers and professionals will appreciate this straightforward approach enabling them to run desk-top analyses of their time series data. Amongst the many facilities available are tools for: ARIMA modelling, smoothing, spectral estimation, multivariate autoregressive modelling, transfer-function modelling, forecasting, and long-memory modelling. This version is designed to run under Microsoft Windows 3.1 or later. It comes with two diskettes: one suitable for less powerful machines (IBM PC 286 or later with 540K available RAM and 1.1 MB of hard disk space) and one for more powerful machines (IBM PC 386 or later with 8MB of RAM and 2.6 MB of hard disk space available).

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Brockwell, Peter J.

Davis, Richard A.

Weitere Mitwirkende

Hyndman, R.J.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik

Inhaltsverzeichnis

1 Introduction.- 1.1 The Programs.- 1.2 System Requirements.- 1.3 Creating Data Files.- 2 PEST.- 2.1 Getting Started.- 2.2 Preparing Your Data for Modelling.- 2.3 Finding a Model for Your Data.- 2.4 Testing Your Model.- 2.5 Prediction.- 2.6 Model Properties.- 2.7 Nonparametric Spectral Estimation.- 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.- 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.- 6.2 Model Selection with the AICC Criterion.- 6.3 Forecasting with the Fitted Model.- 7 BURG.- 7.1 Introduction.- 8 ARAR.- 8.1 Introduction.- 8.2 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.