Modeling the Extreme Rainfall Data of Several Sites in Sabah using Sandwich Estimator

Autor: Siow Chen Sian, Darmesah Gabda

Publikováno v: Journal of Applied Science and Engineering, Vol 25, Iss 3, Pp 417-420 (2021)

When the extreme data were obtained from several sites in a region, spatial extreme analysis is always been considered. In this paper, we model the annual maximum rainfall data by using generalized extreme value distribution. We fit the model indepen

Externí odkaz: https://doaj.org/article/f30b5cc95dd34b78813c3a5309dd920c

A Comparison of Penalized Maximum Likelihood Estimation and Markov Chain Monte Carlo Techniques for Estimating Confirmatory Factor Analysis Models With Small Sample Sizes

Autor: Oliver Lüdtke, Esther Ulitzsch, Alexander Robitzsch

Publikováno v: Frontiers in Psychology, Vol 12 (2021)

With small to modest sample sizes and complex models, maximum likelihood (ML) estimation of confirmatory factor analysis (CFA) models can show serious estimation problems such as non-convergence or parameter estimates outside the admissible parameter

Externí odkaz: https://doaj.org/article/120a307eeb8f4fed82d72af2ba6ff2cf

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Model selection by penalization in mixture of experts models with a non-asymptotic approach

Autor: Nguyen, Trungtin, Chamroukhi, Faicel, Nguyen, Hien Duy, Forbes, Florence

Publikováno v: JDS 2022-53èmes Journées de Statistique de la Société Française de Statistique (SFdS)
JDS 2022-53èmes Journées de Statistique de la Société Française de Statistique (SFdS), Jun 2022, Lyon, France. pp.1-6

International audience; This study is devoted to the problem of model selection among a collection of Gaussian-gated localized mixtures of experts models characterized by the number of mixture components, and the complexity of Gaussian mean experts,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______165::0e5456786a28654da782f638842bbbce
https://hal.science/hal-03663348/document

Usage of Penalized Maximum Likelihood Estimation Method in Medical Research: An Alternative to Maximum Likelihood Estimation Method

Autor: Ecevit Eyduran

Publikováno v: Journal of Research in Medical Sciences, Vol 13, Iss 6, Pp 325-330 (2008)

The present paper was to reduce biased estimation using new approach (Penalized Maximum Likelihood Estimation Method) in Logistic Regression. It was assumed in the present paper that four various data sets on coronary heart disease (CHD) and smoking

Externí odkaz: https://doaj.org/article/cacc244ac4844fd5820fb2e0e5a885ab