株式会社極東書店トップ ＞ 商品一覧 ＞ Methods of Multivariate Statistics.
商品詳細
Methods of Multivariate Statistics. 多変量統計学の方法
・ISBN 978-0-471-22381-8 cloth US$ 203.95
￥47,785.- (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 | Srivastava, Muni S., |
|---|---|
| シリーズ | Wiley Series in Probability and Statistics |
| 出版社 | (Wiley, US) |
| 出版年月 | 2002 |
| ページ数 | 697 pp. |
| 言語 | ENG |
| ニュース番号 | ＜486-228＞ |
解説
Get up-to-speed on the latest methods of multivariate statistics
Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include:
* Missing at-random observations
* "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials
* Bootstrap methods
* Principal component method for predicting a multivariate response vector
* Outlier detection and handling inference when covariance is singular
With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics.
Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and "profile analysis," this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include:
* Missing at-random observations
* "Growth Curve Models" and multivariate one-sided tests applicable in pharmaceutical and medical trials
* Bootstrap methods
* Principal component method for predicting a multivariate response vector
* Outlier detection and handling inference when covariance is singular
With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician's need for a comprehensive investigation of the latest methods in multivariate statistics.