Recently some authors have introduced in the literature stationary stochastic processes, in the time and in the spatial domains, whose finite-dimensional marginal distributions are multivariate skew-normal. Here we show with a counter-example that the characterizations of these processes are not valid and so that these processes do not exist. In particular, we show through a marginalization argument that the set of finite-dimensional marginal distributions of these processes is not self-coherent. Besides, we point our attention to some valid constructions of stationary stochastic processes which can be used to model skewed data.
Titolo: | On the existence of some skew-normal stationary processes | |
Autori: | ||
Data di pubblicazione: | 2012 | |
Rivista: | ||
Abstract: | Recently some authors have introduced in the literature stationary stochastic processes, in the time and in the spatial domains, whose finite-dimensional marginal distributions are multivariate skew-normal. Here we show with a counter-example that the characterizations of these processes are not valid and so that these processes do not exist. In particular, we show through a marginalization argument that the set of finite-dimensional marginal distributions of these processes is not self-coherent. Besides, we point our attention to some valid constructions of stationary stochastic processes which can be used to model skewed data. | |
Handle: | http://hdl.handle.net/11562/474179 | |
Appare nelle tipologie: | 01.01 Articolo in Rivista |