Abstract
Let us first consider linear stationary sequences. A sequence of independent, identically distributed real random variables ξj, j = …, -1,0,1,… is given with Eξj = 0, 0 < Eξ 2j = σ2 < ∞. The process xj is obtained by passing this sequence through a linear filter characterized by the real weights, a j , ∑a 2 j < ∞,
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© 2000 Springer Science+Business Media New York
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Rosenblatt, M. (2000). Reversibility and Identifiability. In: Gaussian and Non-Gaussian Linear Time Series and Random Fields. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1262-1_1
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DOI: https://doi.org/10.1007/978-1-4612-1262-1_1
Publisher Name: Springer, New York, NY
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Online ISBN: 978-1-4612-1262-1
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