Peter J. Brockwell, Richard A. Davis

ITSM for Windows

A User¿s Guide to Time Series Modelling and Forecasting
Mitarbeit:Hyndman, R.J.

• Broschiertes Buch

Produktbeschreibung

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 Time Series: 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 twodiskettes: 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).

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-0-387-94337-4
• 1994
• Seitenzahl: 132
• Erscheinungstermin: 12. August 1994
• Englisch
• Abmessung: 235mm x 155mm x 8mm
• Gewicht: 213g
• ISBN-13: 9780387943374
• ISBN-10: 0387943374
• Artikelnr.: 24489853

Inhaltsangabe

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.

Rezensionen

" Although it has such an easy-to use appearance and a menu driven structure, the programs are surprisingly flexible and many sophisticated time series analyses can be carried out with the package." (Journal of the American Statistical Association)