株式会社極東書店トップ商品一覧Time Series Analysis and Adjustment : Measuring, Modelling and Forecasting for Business and Economics.

商品詳細

Time Series Analysis and Adjustment

Time Series Analysis and Adjustment : Measuring, Modelling and Forecasting for Business and Economics. 時系列分析と調整-ビジネスと経済学のための測定、モデリング、予測-

・ISBN 978-1-4094-4192-2 2014 hard GB£ 171.99

¥54,486.- (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

・ISBN 978-0-367-66948-5 2020 paper GB£ 46.99

¥14,886.- (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

電子版あり 大学・学術機関向け電子ブック(eBook)ISBN 978-1-315-55095-4

著者・編者Bleikh, Haim Y. / Young, W. L.,
出版社(Gower, UK)
ページ数148 pp.
言語ENG
ニュース番号<615-214>

解説

In Time Series Analysis and Adjustment the authors explain how the last four decades have brought dramatic changes in the way researchers analyze economic and financial data on behalf of economic and financial institutions and provide statistics to whomsoever requires them. Such analysis has long involved what is known as econometrics, but time series analysis is a different approach driven more by data than economic theory and focused on modelling. An understanding of time series and the application and understanding of related time series adjustment procedures is essential in areas such as risk management, business cycle analysis, and forecasting. Dealing with economic data involves grappling with things like varying numbers of working and trading days in different months and movable national holidays. Special attention has to be given to such things. However, the main problem in time series analysis is randomness. In real-life, data patterns are usually unclear, and the challenge is to uncover hidden patterns in the data and then to generate accurate forecasts. The case studies in this book demonstrate that time series adjustment methods can be efficaciously applied and utilized, for both analysis and forecasting, but they must be used in the context of reasoned statistical and economic judgment. The authors believe this is the first published study to really deal with this issue of context.