{ "item_title" : "Parameter Estimation and Hypothesis Testing in Spectral Analysis of Stationary Time Series", "item_author" : [" K. Dzhaparidze", "Samuel Kotz "], "item_description" : ". . ) (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 books4,21,22,26,56,77,137,139,140, ]). 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 ( Tare almost always smoothed, i. e., are approximated by values of a certain sufficiently simple function 1 = 1", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/1/46/129/325/1461293251_b.jpg", "price_data" : { "retail_price" : "54.99", "online_price" : "54.99", "our_price" : "54.99", "club_price" : "54.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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