Maximum likelihood estimation for a bivariate Gaussian process under fixed domain asymptotics

We consider maximum likelihood estimation with data from a bivariate Gaussian process with a separable exponential covariance model under fixed domain asymptotics. We first characterize the equivalence of Gaussian measures under this model. Then consistency and asymptotic normality for the maximum l...

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Autores:

Velandia Munoz, Daira Luz
Bachoc, François
Bevilacqua, Moreno
Gendre, Xavier
Loubes, Jean Michel

Tipo de recurso:

Article of journal

Fecha de publicación:

2017

Institución:

Corporación Universidad de la Costa

Repositorio:

REDICUC - Repositorio CUC

Idioma:

eng

OAI Identifier:

oai:repositorio.cuc.edu.co:11323/1878

Acceso en línea:

https://hdl.handle.net/11323/1878
https://doi.org/10.1214/17-EJS1298
https://repositorio.cuc.edu.co/

Palabra clave:

Bivariate exponential model
Equivalent Gaussian measures
Infill asymptotics
Microergodic parameters

Rights

openAccess

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