Explicit bivariate rate functions for large deviations in AR(1) and MA(1) processes with Gaussian innovations

We investigate the large deviations properties for centered stationary AR(1) and MA(1) processes with independent Gaussian innovations, by giving the explicit bivariate rate functions for the sequence of two-dimensional random vectors [...]. Via the Contraction Principle, we provide the explicit rat...

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Detalles Bibliográficos
Autores: Karling, Maicon Josué, Lopes, Artur Oscar, Lopes, Silvia Regina Costa
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:Brasil
Institución:Universidade Federal do Rio Grande do Sul (UFRGS)
Repositorio:Repositório Institucional da UFRGS
Idioma:inglés
OAI Identifier:oai:www.lume.ufrgs.br:10183/263069
Acceso en línea:http://hdl.handle.net/10183/263069
Access Level:acceso abierto
Palabra clave:Matrizes Toeplitz
Processos auto-regressivos
Covariância
Grandes desvios
Autoregressive processes
Empirical autocovariance
Yule-Walker estimator
Large deviations
Moving average processes
Sample moments
Toeplitz matrices
Descripción
Sumario:We investigate the large deviations properties for centered stationary AR(1) and MA(1) processes with independent Gaussian innovations, by giving the explicit bivariate rate functions for the sequence of two-dimensional random vectors [...]. Via the Contraction Principle, we provide the explicit rate functions for the sample mean and the sample second moment. In the AR(1) case, we also give the explicit rate function for the sequence of two-dimensional random vectors [...], but we obtain an analytic rate function that gives different values for the upper and lower bounds, depending on the evaluated set and its intersection with the respective set of exposed points. A careful analysis of the properties of a certain family of Toeplitz matrices is necessary. The large deviations properties of three particular sequences of one-dimensional random variables will follow after we show how to apply a weaker version of the Contraction Principle for our setting, providing new proofs for two already known results on the explicit deviation function for the sample second moment and Yule-Walker estimators. We exhibit the properties of the large deviations of the first-order empirical autocovariance, its explicit deviation function and this is also a new result.