<p>Plotted are exceedance probabilities for each model (i.e. the probability that each given model is more frequent in the population than any other model in the set). The red line denotes p>95%.</p
<p>(a) Exceedance probabilities and posterior expectations (in parentheses) resulting from the BMS p...
<p>The log-likelihood difference between the simple and complex contagion models. (***) is very stro...
<p>Possible models of HDL-C, LDL-C, TG can contain up to 15 covariables (age, sex, BMI SDS, dominant...
<p>Results of Bayesian model selection (control condition): Posterior model probability or and mode...
AIC: Akaike information criterion; PEP: protected exceedance probability; BIC: Bayesian information ...
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
1<p>degrees of freedom used in the model</p><p>Models were compared across likelihoods and parameter...
Note A. Contrasting AIC vs posterior probability calculated by Bayes-MMI for model selection and mul...
<p>These models have frequencies and . These frequencies refer to the population from which the sub...
Frequencies of estimated via Bayesian information criterion over 50 simulated datasets with the sam...
<p><b>NP</b>: number of parameters. Branch numbers refer to the branches from the tree in <a href="h...
(A) Aspects of linear regression model assessed by model selection and model averaging (see Fig 1A)....
<p>(A-B) Exceedance probability (XP) of the baseline model (BM) non-Bayesian (NB) and Bayesian (B) m...
Modern statistical software and machine learning libraries are enabling semi-automated statistical i...
The goal of this paper is to compare several widely used Bayesian model selection methods in practic...
<p>(a) Exceedance probabilities and posterior expectations (in parentheses) resulting from the BMS p...
<p>The log-likelihood difference between the simple and complex contagion models. (***) is very stro...
<p>Possible models of HDL-C, LDL-C, TG can contain up to 15 covariables (age, sex, BMI SDS, dominant...
<p>Results of Bayesian model selection (control condition): Posterior model probability or and mode...
AIC: Akaike information criterion; PEP: protected exceedance probability; BIC: Bayesian information ...
<p>Models selected by various statistical methods. Columns are individual response variables. All mo...
1<p>degrees of freedom used in the model</p><p>Models were compared across likelihoods and parameter...
Note A. Contrasting AIC vs posterior probability calculated by Bayes-MMI for model selection and mul...
<p>These models have frequencies and . These frequencies refer to the population from which the sub...
Frequencies of estimated via Bayesian information criterion over 50 simulated datasets with the sam...
<p><b>NP</b>: number of parameters. Branch numbers refer to the branches from the tree in <a href="h...
(A) Aspects of linear regression model assessed by model selection and model averaging (see Fig 1A)....
<p>(A-B) Exceedance probability (XP) of the baseline model (BM) non-Bayesian (NB) and Bayesian (B) m...
Modern statistical software and machine learning libraries are enabling semi-automated statistical i...
The goal of this paper is to compare several widely used Bayesian model selection methods in practic...
<p>(a) Exceedance probabilities and posterior expectations (in parentheses) resulting from the BMS p...
<p>The log-likelihood difference between the simple and complex contagion models. (***) is very stro...
<p>Possible models of HDL-C, LDL-C, TG can contain up to 15 covariables (age, sex, BMI SDS, dominant...
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