Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series

K. Dzhaparidze

ISBN 10: 1461293251 / ISBN 13: 9781461293255

Published by Springer New York, 2011

About this Item

Druck auf Anfrage Neuware - Printed after ordering - . . ) (under the assumption that the spectral density exists). For this reason, a vast amount of periodical and monographic literature is devoted to the nonparametric statistical problem of estimating the function tJ( T) and especially that of leA) (see, for example, the books [4,21,22,26,56,77,137,139,140,]). However, the empirical value t;; of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl' . . . , X , usually depends in n a complicated manner on the cyclic frequency). . This fact often presents difficulties in applying the obtained estimate t;; of the function I to the solution of specific problems rela ted to the process X . Theref ore, in practice, the t obtained values of the estimator t;; (or an estimator of the covariance function tJ~( T' are almost always 'smoothed,' i. e. , are approximated by values of a certain sufficiently simple function 1 = 1.

Seller Inventory # 9781461293255

Bibliographic Details

• Title: Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series
• Publisher: Springer New York
• Publication Date: 2011
• Language: English
• ISBN 10: 1461293251
• ISBN 13: 9781461293255
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 235W x 155H x 19D millimeters 235 millimeters width by 155 millimeters height by 19 millimeters depth
• Weight: 505 grams

About this title

Synopsis

. . ) (under the assumption that the spectral density exists). For this reason, a vast amount of periodical and monographic literature is devoted to the nonparametric statistical problem of estimating the function tJ( T) and especially that of leA) (see, for example, the books [4,21,22,26,56,77,137,139,140,]). However, the empirical value t;; of the spectral density I obtained by applying a certain statistical procedure to the observed values of the variables Xl' . . . , X , usually depends in n a complicated manner on the cyclic frequency). . This fact often presents difficulties in applying the obtained estimate t;; of the function I to the solution of specific problems rela ted to the process X . Theref ore, in practice, the t obtained values of the estimator t;; (or an estimator of the covariance function tJ~( T» are almost always "smoothed," i. e. , are approximated by values of a certain sufficiently simple function 1 = 1

Language Notes

Text: English, German, Russian (translation)