Oscillating Gaussian processes

Loading...
Thumbnail Image
Journal Title
Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2020-10
Department
Statistics and Mathematical Data Science
Universidad de Valparaíso
Department of Information and Service Management
Department of Mathematics and Systems Analysis
Major/Subject
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.
Description
Keywords
Central limit theorem, Gaussian processes, Oscillating processes, Parameter estimation, Self-similarity, Stationarity
Other note
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