Results 11 to 20 of about 6,440,632 (323)
Comparing Genomic Prediction Models by Means of Cross Validation
Frontiers in Plant Science, 2021 In the two decades of continuous development of genomic selection, a great variety of models have been proposed to make predictions from the information available in dense marker panels.
Matías F. Schrauf +4 more
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Frontiers in Plant Science, 2023 IntroductionDynamic crop growth models are an important tool to predict complex traits, like crop yield, for modern and future genotypes in their current and evolving environments, as those occurring under climate change. Phenotypic traits are the result
George A. K. van Voorn +11 more
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Analysis of Testing-Based Forward Model Selection [PDF]
, 2020 This paper introduces and analyzes a procedure called Testing-based forward model selection (TBFMS) in linear regression problems. This procedure inductively selects covariates that add predictive power into a working statistical model before estimating ...
Kozbur, Damian
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Comparing Model Selection Criteria to Distinguish Truncated Operational Risk Models
Frontiers in Applied Mathematics and Statistics, 2020 In this paper three information criteria are employed to assess the truncated operational risk models. The performances of the three information criteria on distinguishing the models are compared.
Daoping Yu
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Trends in Growth Modeling in Fisheries Science
Fishes, 2021 Growth models estimate life history parameters (e.g., growth rates and asymptotic size) that are used in the management of fisheries stocks. Traditionally in fisheries science, it was common to fit one growth model—the von Bertalanffy growth model—to ...
Shane A. Flinn, Stephen R. Midway
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Bootstrap for neural model selection [PDF]
, 2002 Bootstrap techniques (also called resampling computation techniques) have introduced new advances in modeling and model evaluation. Using resampling methods to construct a series of new samples which are based on the original data set, allows to estimate
Cottrell, Marie +2 more
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Journal of the Royal Statistical Society Series B: Statistical Methodology, 1995 SUMMARY We consider the problem of selecting one model from a large class of plausible models. A predictive Bayesian viewpoint is advocated to avoid the specification of prior probabilities for the candidate models and the detailed interpretation of the parameters in each model.
Laud, Purushottam W., Ibrahim, Joseph G.
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Spherical Minimum Description Length
Entropy, 2018 We consider the problem of model selection using the Minimum Description Length (MDL) criterion for distributions with parameters on the hypersphere.
Trevor Herntier +4 more
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On Zero-Inflated Alternative Hyper-Poisson Distribution
Statistica, 2022 Here we develop a zero-inflated version of the alternative hyper-Poisson distribution and discuss its important statistical properties such as probability generating function, expressions for mean, variance, factorial moments, skewness, kurtosis ...
Satheesh Kumar, Rakhi Ramachandran
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Adaptive Covariance Estimation with model selection [PDF]
, 2012 We provide in this paper a fully adaptive penalized procedure to select a covariance among a collection of models observing i.i.d replications of the process at fixed observation points. For this we generalize previous results of Bigot and al.
A. G. Journel +12 more
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