株式会社極東書店トップ ＞ 商品一覧 ＞ Introduction to Time Series and Forecasting. 3rd ed.
商品詳細
Introduction to Time Series and Forecasting. 3rd ed. P.J.ブロックウェル、R.A.デービス著『入門時系列解析と予測』第3版
・ISBN 978-3-319-29852-8 hard EUR 84.99
￥22,717.- (税込) ※（※）価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
お気に入り
★★★
| 著者・編者 | Brockwell, Peter J. / Davis, R. A., |
|---|---|
| シリーズ | Springer Texts in Statistics |
| 出版社 | (Springer, GW) |
| 出版年月 | 2016 |
| ページ数 | 490 pp. |
| 言語 | ENG |
| ニュース番号 | ＜633-306 633-P785＞ |
解説
This book is aimed at the reader who wishes to gain a working knowledge of time series and forecasting methods as applied to economics, engineering and the natural and social sciences. It assumes knowledge only of basic calculus, matrix algebra and elementary statistics. This third edition contains detailed instructions for the use of the professional version of the Windows-based computer package ITSM2000, now available as a free download from the Springer Extras website. The logic and tools of time series model-building are developed in detail. Numerous exercises are included and the software can be used to analyze and forecast data sets of the user's own choosing. The book can also be used in conjunction with other time series packages such as those included in R. The programs in ITSM2000 however are menu-driven and can be used with minimal investment of time in the computational details.
The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered.
New to this edition:
The core of the book covers stationary processes, ARMA and ARIMA processes, multivariate time series and state-space models, with an optional chapter on spectral analysis. Many additional special topics are also covered.
New to this edition:
- A chapter devoted to Financial Time Series
- Introductions to Brownian motion, Levy processes and Ito calculus
- An expanded section on continuous-time ARMA processes