. . ) (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 ...
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. . ) (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
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Add this copy of Parameter Estimation and Hypothesis Testing in Spectral to cart. $27.92, good condition, Sold by Hay-on-Wye Booksellers rated 4.0 out of 5 stars, ships from Hereford, UNITED KINGDOM, published 1985 by Springer.
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Good. Extremities to the book with foxing to the outer edge with a inscription to the intro page but does not affect the content. Sewn binding. Cloth over boards. 324 p. Springer Statistics.
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