English

Oscillating Gaussian Processes

Probability 2019-05-30 v1

Abstract

In this article we introduce and study oscillating Gaussian processes defined by Xt=α+Yt1Yt>0+αYt1Yt<0X_t = \alpha_+ Y_t {\bf 1}_{Y_t >0} + \alpha_- Y_t{\bf 1}_{Y_t<0}, where α+,α>0\alpha_+,\alpha_->0 are free parameters and YY is either stationary or self-similar Gaussian process. We study the basic properties of XX and we consider estimation of the model parameters. In particular, we show that the moment estimators converge in LpL^p and are, when suitably normalised, asymptotically normal.

Keywords

Cite

@article{arxiv.1905.12031,
  title  = {Oscillating Gaussian Processes},
  author = {Pauliina Ilmonen and Soledad Torres and Lauri Viitasaari},
  journal= {arXiv preprint arXiv:1905.12031},
  year   = {2019}
}
R2 v1 2026-06-23T09:29:56.662Z