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We present a method to use samples from simulated predictive distributions for selecting experiments useful for model selection.
Hence our model comparison emphasizes features that can be used to choose or design fit-for-purpose models, and we outline how quantitative data useful for model selection and validation can be obtained from modern systems and ancient deposits.
AIC is particularly useful for model selection with small sample size, and the corrected-version AICc provide better performance than AIC (Hurvich and Tsai 1989).
We have previously defined two mathematical functions, the information density function and information function, which are useful for model selection and optimization of scan time in PET [13].
QIF is useful for model selection and provides more efficient parameter estimates than GEE.
Bayesian model averaging may be useful for model selection but only limited attempts to compare it to stepwise regression have been published.
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Useful information for model selection can be obtained from using AIC and BIC together, particularly from trying as far as possible to find models favoured by both criteria.
As stepwise regression analysis is no useful tool for model selection [ 41], Akaike Information Criterion was used to estimate model fit [ 42, 43].
Multi-model comparison can provide useful information for model selection and improvement.
Meanwhile, CFI, RMSEA, and SRMR are useful in detecting model misspecification, and relative fit indices (e.g., AIC and BIC) are mainly used for model selection (Curran et al. 1996; Fan and Sivo 2005; Ryu 2011).
As Arlot's title, CV is used for model selection.
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useful for model discrimination
useful for model validation
useful for formulation selection
useful for screening selection
useful for marker selection
useful for model model
useful for model assessment
useful for antigen selection
useful for cultivar selection
useful for patient selection
useful for parameter selection
useful for user selection
useful for gene selection
useful for model parameterization
useful for risk selection
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