The distribution of a variable observed over a domain depends on the underlying process and also on the geographical locations at which the variable has been measured. In this paper, we fit a model to the distribution supposing that the observations are generated by a stationary strong-mixing random field. Indeed, after estimating the density of the considered variable, we construct a test statistic in order to verify the goodness of fit of the observed spatial data. The proposed class of tests is a generalization of the classical chi-square-test and of the Neyman smooth test. In the framework of increasing domain asymptotics, we analyse the large sample behaviour of the test. The limiting distribution is a linear combination of χ2 r.v.s where the coefficients are the eigenvalues of a matrix Σ essentially related to the spectral density of the random field. Finally some indications about the implementation are provided.

Model testing for spatially correlated data / R. Ignaccolo; N. Ribecco. - In: ANNALES DE L'ISUP. - ISSN 1626-1607. - STAMPA. - LII - 3(2008), pp. 27-42.

Model testing for spatially correlated data

IGNACCOLO, Rosaria;
2008

Abstract

The distribution of a variable observed over a domain depends on the underlying process and also on the geographical locations at which the variable has been measured. In this paper, we fit a model to the distribution supposing that the observations are generated by a stationary strong-mixing random field. Indeed, after estimating the density of the considered variable, we construct a test statistic in order to verify the goodness of fit of the observed spatial data. The proposed class of tests is a generalization of the classical chi-square-test and of the Neyman smooth test. In the framework of increasing domain asymptotics, we analyse the large sample behaviour of the test. The limiting distribution is a linear combination of χ2 r.v.s where the coefficients are the eigenvalues of a matrix Σ essentially related to the spectral density of the random field. Finally some indications about the implementation are provided.
LII - 3
27
42
R. Ignaccolo; N. Ribecco
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.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2318/98455
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact