WAIC: Watanabe-Akaike or Widely Available Information Criterion...
In mtarm: Bayesian Estimation of Multivariate Threshold Autoregressive Models
WAIC R Documentation
Watanabe-Akaike or Widely Available Information Criterion (WAIC)
Description
Computes Watanabe-Akaike or Widely Available Information Criterion (WAIC), an adjusted
within-sample measure of predictive accuracy, for models estimated using Bayesian methods.
Usage
WAIC(...)
Arguments
...
one or more fitted model objects of the same class.
Value
A numeric matrix containing the WAIC values corresponding to each fitted object supplied in ....
References
Watanabe S. (2010). Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in
Singular Learning Theory. The Journal of Machine Learning Research, 11, 3571–3594.
mtarm documentation built on Jan. 12, 2026, 1:07 a.m.
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| WAIC | R Documentation |
Watanabe-Akaike or Widely Available Information Criterion (WAIC)
Description
Computes Watanabe-Akaike or Widely Available Information Criterion (WAIC), an adjusted within-sample measure of predictive accuracy, for models estimated using Bayesian methods.
Usage
WAIC(...)
Arguments
... |
one or more fitted model objects of the same class. |
Value
A numeric matrix containing the WAIC values corresponding to each fitted object supplied in ....
References
Watanabe S. (2010). Asymptotic Equivalence of Bayes Cross Validation and Widely Applicable Information Criterion in Singular Learning Theory. The Journal of Machine Learning Research, 11, 3571–3594.
R Package Documentation
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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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