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Mathematics > Statistics Theory

arXiv:1911.01065 (math)
[Submitted on 4 Nov 2019]

Title:Modeling and estimation of multivariate discrete and continuous time stationary processes

Authors:Marko Voutilainen
View a PDF of the paper titled Modeling and estimation of multivariate discrete and continuous time stationary processes, by Marko Voutilainen
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Abstract:In this paper, we give a AR$(1)$ type of characterization covering all multivariate strictly stationary processes indexed by the set of integers. Consequently, we derive continuous time algebraic Riccati equations for the parameter matrix of the characterization providing us with a natural way to define the corresponding estimator under the assumption of square integrability. In addition, we show that the estimator inherits consistency from autocovariances of the stationary process and furthermore, the limiting distribution is given by a linear function of the limiting distribution of the autocovariances. We also present the corresponding existing results of the continuous time setting paralleling them to the discrete case.
Subjects: Statistics Theory (math.ST)
MSC classes: 60G10, 62M10, 62H12, 62G05
Cite as: arXiv:1911.01065 [math.ST]
  (or arXiv:1911.01065v1 [math.ST] for this version)
  https://doi.org/10.48550/arXiv.1911.01065
arXiv-issued DOI via DataCite

Submission history

From: Marko Voutilainen [view email]
[v1] Mon, 4 Nov 2019 07:47:26 UTC (17 KB)
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