A backward elimination discrete optimization algorithm for model selection in spatio-temporal regression models

Regression models are used in geosciences to extrapolate data and identify significant predictors of a response variable. Criterion approaches based on the residual sum of squares (RSS), such as the Akaike Information Criterion, Bayesian Information Criterion (BIC), Deviance Information Criterion, o...

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Vydáno v:	Environmental modelling & software : with environment data news Ročník 42; s. 88 - 98
Hlavní autoři:	Yadav, Vineet, Mueller, Kimberly L., Michalak, Anna M.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.04.2013 Elsevier
Témata:	Algorithm algorithms Animal, plant and microbial ecology autocorrelation Biological and medical sciences Branch and bound computer software covariance Discrete optimization environmental models Fundamental and applied biological sciences. Psychology General aspects. Techniques geostatistics linear models Methods and techniques (sampling, tagging, trapping, modelling...) Model selection regression analysis Spatio-temporal regression models Discrete optimization Branch and bound Model selection Algorithm Spatio-temporal regression models Regression model Elimination Optimization
ISSN:	1364-8152, 1873-6726
On-line přístup:	Získat plný text
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