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Model selection

Known as: Model comparison 
Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of… 
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Related topics

Related topics

39 relations
Additive modelAkaike information criterionAlgorithmic information theoryAll models are wrong

Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
Highly Cited
2010
Highly Cited
2010
Latent variable graphical model selection via convex optimization
Suppose we have samples of a subset of a collection of random variables. No additional information is provided about the number… 
Highly Cited
2008
Highly Cited
2008
High-Dimensional Graphical Model Selection Using $\ell_1$-Regularized Logistic Regression
We consider the problem of estimating the graph structure associated with a discrete Markov random field. We describe a method… 
Highly Cited
2007
Highly Cited
2007
Spatial autocorrelation and the selection of simultaneous autoregressive models
Aim Spatial autocorrelation is a frequent phenomenon in ecological data and can affect estimates of model coefficients and… 
Highly Cited
2007
Highly Cited
2007
A Simple Distribution-Free Test for Nonnested Model Selection
This paper considers a simple distribution-free test for nonnested model selection. The new test is shown to be asymptotically… 
Highly Cited
2004
Highly Cited
2004
Methods and Criteria for Model Selection
Model selection is an important part of any statistical analysis and, indeed, is central to the pursuit of science in general… 
Highly Cited
2000
Highly Cited
2000
Model Selection and Semiparametric Inference for Bivariate Failure-Time Data
Abstract We propose model selection procedures for bivariate survival models for censored data generated by the Archimedean… 
Highly Cited
1998
Highly Cited
1998
Asymptotic MAP criteria for model selection
The two most popular model selection rules in signal processing literature have been Akaike's (1974) criterion (AIC) and Rissanen… 
Highly Cited
1997
Highly Cited
1997
A comparison of the performance of nine soil organic matter models using datasets from seven long-term experiments
Highly Cited
1996
Highly Cited
1996
Generalised information criteria in model selection
SUMMARY The problem of evaluating the goodness of statistical models is investigated from an information-theoretic point of view… 
Highly Cited
1995
Highly Cited
1995
Bayesian Learning for Neural Networks
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions… 
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