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BAYESIAN ESTIMATION UNDER KULLBACK-LEIBLER DIVERGENCE MEASURE BASED ON EXPONENTIAL DATAESTIMACIÓN BAYESIANA BAJO DIVERGENCIA KULLBACK-LEIBLER MEDIDA BASADA EN DATOS EXPONENCIALES
(Departamento de Matemática Aplicada. Facultad de Matemática y Computación. Universidad de La Habana, 2023)
Partial discharges location in transformer winding using wavelets and Kullback-Leibler divergence
(Elsevier Science Sa, 2016-07)
A new algorithm to partial discharges (PD) location in transformer windings by means of the discrete wavelets transform (DWT) and the Kullback-Leibler (KL) divergence is presented. When the insulation system of transformers ...
A visual EEG epilepsy detection method based on a wavelet statistical representation and the Kullback-Leibler divergence
(Springer Verlag, 2017-04)
This paper presents a statistical signal processing method for the characterization of EEG of patients suffering from epilepsy. A statistical model is proposed for the signals and the Kullback-Leibler divergence is used ...
Addressing non-normality in multivariate analysis using the t-distribution
(2023)
The main aim of this paper is to propose a set of tools for assessing non-normality taking into consideration the class of multivariate t-distributions. Assuming second moment existence, we consider a reparameterized version ...
Análise bayesiana objetiva para as distribuições normal generalizada e lognormal generalizada
(Universidade Federal de São CarlosBRUFSCarPrograma de Pós-Graduação em Estatística - PPGEs, 2014-11-21)
The Generalized Normal (GN) and Generalized lognormal (logGN) distributions are flexible for accommodating features present in the data that are not captured by traditional distribution, such as the normal and the lognormal ...
The zero-inflated Conway-Maxwell-Poisson distribution: Bayesian inference, regression modeling and influence diagnostic
(Elsevier B.V., 2014-11-01)
In this paper we propose the zero-inflated COM-Poisson distribution. We develop a Bayesian analysis for our model via on Markov chain Monte Carlo methods. We discuss regression modeling and model selection, as well as, ...
Estimation and influence diagnostics for zero-inflated hyper-Poisson regression model: full Bayesian analysis
(Taylor & Francis Inc, 2018-01-01)
The purpose of this paper is to develop a Bayesian analysis for the zero-inflated hyper-Poisson model. Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the model and the Bayes estimators are ...
Fully adaptive particle filtering algorithm for damage diagnosis and prognosis
(MDPI, 2018)
A fully adaptive particle filtering algorithm is proposed in this paper which is capable of updating both state process models and measurement models separately and simultaneously. The approach is a significant step toward ...
On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis
(ELSEVIER SCIENCE BV, 2010)
The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian ...