美丽动人
发表于 2025-3-21 16:44:44
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弯曲的人
发表于 2025-3-21 23:55:07
Springer Nature Switzerland AG 2016
音的强弱
发表于 2025-3-22 00:49:24
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Meditate
发表于 2025-3-22 06:25:43
ARMA Models,In this chapter we introduce an important parametric family of stationary time series, the autoregressive moving-average, or ARMA, processes. For a large class of autocovariance functions .(⋅ ) it is possible to find an ARMA process {..} with ACVF ..(⋅ ) such that .(⋅ ) is well approximated by ..(⋅ ).
myocardium
发表于 2025-3-22 09:58:17
Nonstationary and Seasonal Time Series Models,In this chapter we shall examine the problem of finding an appropriate model for a given set of observations {.., ., ..} that are not necessarily generated by a stationary time series.
讲个故事逗他
发表于 2025-3-22 16:54:36
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GUISE
发表于 2025-3-22 19:38:37
Multivariate Time Series,ependence within each component series {..} but also interdependence between the different component series {..} and {..}, . ≠ .. Much of the theory of univariate time series extends in a natural way to the multivariate case; however, new problems arise.
subordinate
发表于 2025-3-22 22:27:19
Peter J. Brockwell,Richard A. DavisDesigned for use in full-year courses introducing univariate and multivariate time series and forecasting at the advanced undergraduate and graduate levels.Exercise problems at the end of each chapter
奇思怪想
发表于 2025-3-23 05:08:49
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Pigeon
发表于 2025-3-23 09:31:06
Spectral Analysis,ess, which for some applications may be more illuminating. For example, in the design of a structure subject to a randomly fluctuating load, it is important to be aware of the presence in the loading force of a large sinusoidal component with a particular frequency to ensure that this is not a reson