| 书目名称 | Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series | | 编辑 | K. Dzhaparidze | | 视频video | | | 丛书名称 | Springer Series in Statistics | | 图书封面 |  | | 描述 | . . ) (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 | | 出版日期 | Book 1986 | | 关键词 | Analysis; Estimator; Gaussian distribution; Likelihood; Series; Time; Time series; best fit | | 版次 | 1 | | doi | https://doi.org/10.1007/978-1-4612-4842-2 | | isbn_softcover | 978-1-4612-9325-5 | | isbn_ebook | 978-1-4612-4842-2Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer-Verlag New York Inc. 1986 |
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发表于 2025-3-21 19:14:53
