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.
On the existence of some skew-normal stationary processes
MINOZZO, Marco;
2012
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.
File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
