Multivariate model-based geostatistics refers to the extension of classical multivariate geostatistical techniques, in particular the classical linear model of coregionalization, to the case of non-Gaussian data. Extensions of this kind are still limited in the statistical literature, mainly for the inferential problems they pose, and almost invariably inference is carried out in a Bayesian context. In this work we present some new results on likelihood inference for the unknown parameters of a hierarchical geostatistical factor model. In particular, we show the implementation of some Monte Carlo EM algorithms and discuss their performances, in particular their sampling distributions, mainly through some simulation studies.

Likelihood inference in multivariate model-based geostatistics

FERRARI, Clarissa;MINOZZO, Marco
2011

Abstract

Multivariate model-based geostatistics refers to the extension of classical multivariate geostatistical techniques, in particular the classical linear model of coregionalization, to the case of non-Gaussian data. Extensions of this kind are still limited in the statistical literature, mainly for the inferential problems they pose, and almost invariably inference is carried out in a Bayesian context. In this work we present some new results on likelihood inference for the unknown parameters of a hierarchical geostatistical factor model. In particular, we show the implementation of some Monte Carlo EM algorithms and discuss their performances, in particular their sampling distributions, mainly through some simulation studies.
9788896025123
Cokriging; Generalized linear mixed model; Markov chain Monte Carlo; Monte Carlo EM; Multivariate geostatistics
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/11562/385453
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact