Results 11 to 20 of about 2,665,481 (259)
Sensitivity and specificity of information criteria. [PDF]
Brief Bioinform, 2020 Information criteria (ICs) based on penalized likelihood, such as Akaike's Information Criterion (AIC), the Bayesian Information Criterion (BIC), and sample-size-adjusted versions of them, are widely used for model selection in health and biological research.
Dziak JJ +4 more
europepmc +6 more sources
Performance of Information Criteria for Spatial Models. [PDF]
J Stat Comput Simul, 2009 Model choice is one of the most crucial aspect in any statistical data analysis. It is well known that most models are just an approximation to the true data generating process but among such model approximations it is our goal to select the "best" one.
Lee H, Ghosh SK.
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Word2vec Skip-Gram Dimensionality Selection via Sequential Normalized Maximum Likelihood
Entropy, 2021 In this paper, we propose a novel information criteria-based approach to select the dimensionality of the word2vec Skip-gram (SG). From the perspective of the probability theory, SG is considered as an implicit probability distribution estimation under ...
Pham Thuc Hung, Kenji Yamanishi
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On the Disagreement of Forecasting Model Selection Criteria
Forecasting, 2023 Forecasters have been using various criteria to select the most appropriate model from a pool of candidate models. This includes measurements on the in-sample accuracy of the models, information criteria, and cross-validation, among others.
Evangelos Spiliotis +2 more
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Entropy, 2023 Inbreeding depression can reduce the viability of wild populations. Detecting inbreeding depression in the wild is difficult; developing accurate estimates of inbreeding can be time and labor intensive.
John H. Powell +5 more
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The Copula Information Criteria [PDF]
Scandinavian Journal of Statistics, 2014 ABSTRACTWe derive two types of Akaike information criterion (AIC)‐like model‐selection formulae for the semiparametric pseudo‐maximum likelihood procedure. We first adapt the arguments leading to the original AIC formula, related to empirical estimation of a certain Kullback–Leibler information distance.
Grønneberg, Steffen, Hjort, Nils Lid
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Frontiers in Ecology and Evolution, 2021 Scientists need to compare the support for models based on observed phenomena. The main goal of the evidential paradigm is to quantify the strength of evidence in the data for a reference model relative to an alternative model.
Mark L. Taper +6 more
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Journal of Statistical Software, 2021 We introduce the new package dmbc that implements a Bayesian algorithm for clustering a set of binary dissimilarity matrices within a model-based framework.
Sergio Venturini, Raffaella Piccarreta
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Model Selection with Missing Data Embedded in Missing-at-Random Data
Stats, 2023 When models are built with missing data, an information criterion is needed to select the best model among the various candidates. Using a conventional information criterion for missing data may lead to the selection of the wrong model when data are not ...
Keiji Takai, Kenichi Hayashi
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Use of information criteria and detection model methods to select the best linear regression model with application on thalassemia children in Mosul [PDF]
مجلة التربية والعلم, 2012 In this paper we compute Akaike's Information Criteria (AIC), Bayesian Information Criteria (BIC) and Schwarz Bayesian Criteria (SBC) for all possible for independent variables.
Iman Fathy
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