Abstract

In statistical space-time modeling, the use of non-separable covariance functions is often more realistic than separable models. In the literature, various tests for separability may justify this choice. However, in case of rejection of the separability hypothesis, none of these tests include testing for the type of non-separability of space- time covariance functions. This is an important and further significant step for choosing a class of models. In this paper a method for testing positive and negative non-separability is given; moreover, an approach for testing some well known classes of space-time covariance function models has been proposed. The performance of the tests has been shown using real and simulated data.

Autore Pugliese

• De Iaco Sandra , Posa Donato

Tutti gli autori

• Cappello C. , de Iaco S. , Posa D.

Titolo volume/Rivista

STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Anno di pubblicazione

2018

ISSN

1436-3240

ISBN

Non Disponibile

Numero di citazioni Wos

Nessuna citazione

Ultimo Aggiornamento Citazioni

Non Disponibile

Numero di citazioni Scopus

Non Disponibile

0

Ultimo Aggiornamento Citazioni

25/04/2018

Settori ERC

Non Disponibile

Codici ASJC

Non Disponibile