Parameter estimation and hypothesis testing in spectral analysis of stationary time series
Parameter estimation and hypothesis testing in spectral analysis of stationary time series
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平稳时间序列谱分析中的参数估计和假设检验
DOI：
10.1007/978-1-4612-4842-2
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发表时间：
1986
期刊：
影响因子：
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通讯作者：
K. Dzhaparidze
中科院分区：
文献类型：
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作者：
K. Dzhaparidze
..)（假设谱密度存在）。为此，大量的期刊和专题文献致力于估计函数tJ（T），特别是莱亚）的非参数统计问题（例如，参见书籍[4，21，22，26，56，77，137，139，140，]）。然而，通过对变量X1 '..通常以复杂的方式取决于循环频率）。这一事实常常在将所获得的函数I的估计值t1应用于与过程X有关的特定问题的解决方案时带来困难。因此，在实践中，估计量ti（或协方差函数ti（T）的估计量）的t个获得的值几乎总是”平滑的”，即，由某个足够简单的函数1= 1的值近似。
..)(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 na 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," ie, are approximated by values of a certain sufficiently simple function 1= 1