Oscillating Gaussian processes

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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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Author
Date
2020-10
Department
Statistics and Mathematical Data Science
Universidad de Valparaíso
Department of Information and Service Management
Department of Mathematics and Systems Analysis
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Mcode
Degree programme
Language
en
Pages
Series
Statistical Inference for Stochastic Processes
Abstract
In this article we introduce and study oscillating Gaussian processes defined by Xt=α+Yt1Yt>0+α-Yt1Yt<0, where α+, α-> 0 are free parameters and Y is either stationary or self-similar Gaussian process. We study the basic properties of X and we consider estimation of the model parameters. In particular, we show that the moment estimators converge in Lp and are, when suitably normalised, asymptotically normal.
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Keywords
Central limit theorem, Gaussian processes, Oscillating processes, Parameter estimation, Self-similarity, Stationarity
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DOI
10.1007/s11203-020-09212-6
Citation
Ilmonen , P , Torres , S & Viitasaari , L 2020 , ' Oscillating Gaussian processes ' , Statistical Inference for Stochastic Processes , vol. 23 , no. 3 , pp. 571-593 . https://doi.org/10.1007/s11203-020-09212-6
Permanent link to this item
https://urn.fi/URN:NBN:fi:aalto-202006013501
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[article-cris] Perustieteiden korkeakoulu / SCI