Local asymptotic mixed normality of transformed Gaussian models for random fields

Tomonari Sei

doi:10.1016/j.spa.2006.08.007

Local asymptotic mixed normality of transformed Gaussian models for random fields

Tomonari Sei

Research output: Contribution to journal › Article › peer-review

Abstract

Local asymptotic mixed normality (LAMN) of a class of transformed Gaussian models for discretely observed random fields is proved. The original Gaussian random field is assumed to be the product of a deterministic process and a process with independent increments. The transformed process is observed only on discrete lattice points in the unit cube and fixed domain asymptotics is investigated. This model is useful for modeling random fields with non-Gaussian marginal distributions.

Original language	English
Pages (from-to)	375-398
Number of pages	24
Journal	Stochastic Processes and their Applications
Volume	117
Issue number	3
DOIs	https://doi.org/10.1016/j.spa.2006.08.007
Publication status	Published - 2007 Mar
Externally published	Yes

Keywords

Brownian sheet
Discrete observation
Fixed domain asymptotics
Local asymptotic mixed normality
Multiparameter process
Ornstein-Uhlenbeck sheet
Random field
Transformed Gaussian model

ASJC Scopus subject areas

Statistics and Probability
Modelling and Simulation
Applied Mathematics

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10.1016/j.spa.2006.08.007

Cite this

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title = "Local asymptotic mixed normality of transformed Gaussian models for random fields",

abstract = "Local asymptotic mixed normality (LAMN) of a class of transformed Gaussian models for discretely observed random fields is proved. The original Gaussian random field is assumed to be the product of a deterministic process and a process with independent increments. The transformed process is observed only on discrete lattice points in the unit cube and fixed domain asymptotics is investigated. This model is useful for modeling random fields with non-Gaussian marginal distributions.",

keywords = "Brownian sheet, Discrete observation, Fixed domain asymptotics, Local asymptotic mixed normality, Multiparameter process, Ornstein-Uhlenbeck sheet, Random field, Transformed Gaussian model",

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year = "2007",

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AB - Local asymptotic mixed normality (LAMN) of a class of transformed Gaussian models for discretely observed random fields is proved. The original Gaussian random field is assumed to be the product of a deterministic process and a process with independent increments. The transformed process is observed only on discrete lattice points in the unit cube and fixed domain asymptotics is investigated. This model is useful for modeling random fields with non-Gaussian marginal distributions.

KW - Brownian sheet

KW - Discrete observation

KW - Fixed domain asymptotics

KW - Local asymptotic mixed normality

KW - Multiparameter process

KW - Ornstein-Uhlenbeck sheet

KW - Random field

KW - Transformed Gaussian model

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VL - 117

SP - 375

EP - 398

JO - Stochastic Processes and their Applications

JF - Stochastic Processes and their Applications

IS - 3

ER -

Local asymptotic mixed normality of transformed Gaussian models for random fields

Abstract

Keywords

ASJC Scopus subject areas

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