Results 11 to 20 of about 108,936 (256)
Heliyon, 2023 Multivariate Adaptive Regression Splines (MARS) is a useful non-parametric regression analysis method that can be used for model selection in high-dimensional data. Since MARS can identify and model complex, non-linear relationships between the dependent
Meryem Bekar Adiguzel, Mehmet Ali Cengiz
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A Focused Bayesian Information Criterion [PDF]
Advances in Statistics, 2014 Myriads of model selection criteria (Bayesian and frequentist) have been proposed in the literature aiming at selecting a single model regardless of its intended use. An honorable exception in the frequentist perspective is the “focused information criterion” (FIC) aiming at selecting a model based on the parameter of interest (focus). This paper takes
Georges Nguefack-Tsague, Ingo Bulla
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A PAC-Bayesian Perspective on the Interpolating Information Criterion
CoRR, 2023 9 ...
Liam Hodgkinson +4 more
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Investigation of the widely applicable Bayesian information criterion [PDF]
Statistics and Computing, 2016 To appear in Statistics and ...
Nial Friel +3 more
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Yantu gongcheng xuebao, 2023 In order to establish an optimal model for estimating the uniaxial compressive strength (UCS) of rocks as well as its reasonable estimation, a fully Bayesian Gaussian process regression method (fB-GPR) is proposed by combining the Gaussian process ...
SONG Chao , ZHAO Tengyuan , XU Ling
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Bayesian model evidence as a practical alternative to deviance information criterion [PDF]
Royal Society Open Science, 2018 While model evidence is considered by Bayesian statisticians as a gold standard for model selection (the ratio in model evidence between two models giving the Bayes factor), its calculation is often viewed as too computationally demanding for many ...
C. M. Pooley, G. Marion
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Knee Point Detection on Bayesian Information Criterion [PDF]
2008 20th IEEE International Conference on Tools with Artificial Intelligence, 2008 The main challenge of cluster analysis is that the number of clusters or the number of model parameters is seldom known, and it must therefore be determined before clustering. Bayesian information criterion (BIC) often serves as a statistical criterion for model selection, which can also be used in solving model-based clustering problems, in particular
Qinpei Zhao, Mantao Xu, Pasi Fränti
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Modeling crude oil price volatility in Nigeria: using GARCH (1,1), EGARCH (1,1), and GJR-GARCH (1,1) models [PDF]
مجلة العلوم التجارية والبيئيةThis study investigates the performance of various GARCH models for volatility forecasting, focusing on the GARCH (1,1), EGARCH (1,1), and GJR-GARCH (1,1) frameworks, each tested with normal and Student’s t-distributions.
Frederick A. Omoruyi +2 more
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BMC Evolutionary Biology, 2010 Background Explicit evolutionary models are required in maximum-likelihood and Bayesian inference, the two methods that are overwhelmingly used in phylogenetic studies of DNA sequence data.
Luo Arong +7 more
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Spatial mixture modeling for analyzing a rainfall pattern: A case study in Ireland
Open Engineering, 2022 This study investigates the spatial heterogeneity in the maximum monthly rainfall amounts reported by stations in Ireland from January 2018 to December 2020. The heterogeneity is modeled by the Bayesian normal mixture model with different ranks.
Hussein Amjad, Kadhem Safaa K.
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