Titlebook: Correlation Theory of Stationary and Related Random Functions; Supplementary Notes A. M. Yaglom Book 1987 Springer-Verlag New York Inc. 19

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书目名称Correlation Theory of Stationary and Related Random Functions影响因子(影响力)




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书目名称Correlation Theory of Stationary and Related Random Functions网络公开度学科排名




书目名称Correlation Theory of Stationary and Related Random Functions被引频次




书目名称Correlation Theory of Stationary and Related Random Functions被引频次学科排名




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书目名称Correlation Theory of Stationary and Related Random Functions年度引用学科排名




书目名称Correlation Theory of Stationary and Related Random Functions读者反馈




书目名称Correlation Theory of Stationary and Related Random Functions读者反馈学科排名

动作谜

0172-7397 aling only with the first and second moments of these functions. This theory is a significant part of modern probability theory and offers both intrinsic mathematical interest and many concrete and practical applications. Stationary random functions arise in connection with stationary time series wh

要塞

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Book 1987 with the first and second moments of these functions. This theory is a significant part of modern probability theory and offers both intrinsic mathematical interest and many concrete and practical applications. Stationary random functions arise in connection with stationary time series which are so

Formidable

https://doi.org/10.1007/978-3-319-22584-5e variance σ.(.) of any unbiased estimator . of a parameter . can be determined, and hence the absolute . .(.) = σ.(.)/σ.(.) of . can be evaluated. The estimator . (and the estimate .) is called . if .(.) = 1 and . if .(.) → 1 as . → ∞.

花费

花费

Chapter 2,ation of the result (2.5) in the form .. The last relationship implies the possibility of representing the random sequence .(.) in the form (2.4) by virtue of the so-called theorem on generalized spectral representation of random functions (see the closing part of Note 17 below).

大漩涡

Ahmed Abujoda,Panagiotis Papadimitrioum function arises, usually in an actual physical context. As already emphasized in the Introduction, in order to apply probabilistic methods, we must have an experiment which can be repeated many times under similar conditions and which can lead to different outcomes. The set Ω of all possible outco

CUB

C. Bouras,V. Kapoulas,E. Tsanai consider the more general case of the complex-valued function .(.). Assuming that . = 0 for . > . and . < 0, we can write the corresponding generalization of the result (2.5) in the form .. The last relationship implies the possibility of representing the random sequence .(.) in the form (2.4) by v

混杂人

https://doi.org/10.1007/978-3-319-22584-5stimates thoroughly studied in many statistical texts (see, e.g., Cramér, 1946; Wilks, 1962; Kendall and Stuart, 1966; Silvey, 1970; Zacks, 1971). To compare two different unbiased consistent estimators of ., say, . and ., the .(., .) or . as compared with . is sometimes evaluated by the formula .(.