$\beta$-mixing and moments properties of a non-stationary copula-based Markov process
Statistics Theory
2017-04-06 v1 Statistics Theory
Abstract
This paper provides conditions under which a non-stationary copula-based Markov process is -mixing. We introduce, as a particular case, a convolution-based gaussian Markov process which generalizes the standard random walk allowing the increments to be dependent.
Keywords
Cite
@article{arxiv.1704.01458,
title = {$\beta$-mixing and moments properties of a non-stationary copula-based Markov process},
author = {Fabio Gobbi and Sabrina Mulinacci},
journal= {arXiv preprint arXiv:1704.01458},
year = {2017}
}