WAIC: Watanabe–Akaike information criterion
In DouglasMesquita/RASCO: An R Package to Alleviate Spatial Confounding
WAIC R Documentation
Watanabe–Akaike information criterion
Description
Get the Watanabe–Akaike information criterion (WAIC) from a model
Usage
WAIC(object)
Arguments
object
a object from ?rsglmm, ?rscm or ?rsfm. Do not forget to add control.compute = list(waic = TRUE, dic = TRUE) to your call.
Value
WAIC
References
Watanabe, S. (2010). "Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory". Journal of Machine Learning Research, 11, 3571-3594.
DouglasMesquita/RASCO documentation built on Nov. 16, 2022, 9:42 p.m.
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.
| WAIC | R Documentation |
Watanabe–Akaike information criterion
Description
Get the Watanabe–Akaike information criterion (WAIC) from a model
Usage
WAIC(object)
Arguments
object |
a object from ?rsglmm, ?rscm or ?rsfm. Do not forget to add control.compute = list(waic = TRUE, dic = TRUE) to your call. |
Value
WAIC
References
Watanabe, S. (2010). "Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory". Journal of Machine Learning Research, 11, 3571-3594.
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.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.