BIC: Bayesian Information Criterion
In BayHap: Bayesian analysis of haplotype association using Markov Chain Monte Carlo
Description
Usage
Arguments
Details
Value
Author(s)
Description
This function computes the Bayesian Information Criterion of a model.
Usage
1
BIC(res)
Arguments
res
An object of class reg returned by the function bayhapReg.
Details
The Bayesian information criterion (BIC) is a criterion for model selection among a class of parametric models with different numbers of parameters. BIC value is computed through the formula
-2 log(L)+klog(n)
where L is the maximized value of the likelihood function for the estimated model, k is the number of terms of the markov chain, i.e. the number of free parameters to be estimated (if the estimated model is a linear regression, k is the number of regressors, including the constant) and n is the sample size.
If several models are runned, you can compare them by using the BIC criterion. The lower the BIC value, the better the model fit.
Value
The value returned is the BIC value.
Author(s)
Raquel Iniesta riniesta@pssjd.org
BayHap documentation built on May 2, 2019, 12:44 a.m.
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Description Usage Arguments Details Value Author(s)
Description
This function computes the Bayesian Information Criterion of a model.
Usage
1 | BIC(res)
|
Arguments
res |
An object of class |
Details
The Bayesian information criterion (BIC) is a criterion for model selection among a class of parametric models with different numbers of parameters. BIC value is computed through the formula -2 log(L)+klog(n) where L is the maximized value of the likelihood function for the estimated model, k is the number of terms of the markov chain, i.e. the number of free parameters to be estimated (if the estimated model is a linear regression, k is the number of regressors, including the constant) and n is the sample size. If several models are runned, you can compare them by using the BIC criterion. The lower the BIC value, the better the model fit.
Value
The value returned is the BIC value.
Author(s)
Raquel Iniesta riniesta@pssjd.org
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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