pAIC: Pseudo Akaike Information Criterion
In mcglm: Multivariate Covariance Generalized Linear Models
pAIC R Documentation
Pseudo Akaike Information Criterion
Description
Extract the pseudo Akaike information criterion (pAIC)
for objects of mcglm class.
Usage
pAIC(object, verbose = TRUE)
Arguments
object
an object or a list of objects representing a model
of mcglm class.
verbose
logical. Print or not the pAIC value.
Value
Returns the value of the pseudo Akaike information criterion (pAIC).
Author(s)
Wagner Hugo Bonat, wbonat@ufpr.br
Source
Bonat, W. H. (2018). Multiple Response Variables Regression
Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1–30.
See Also
gof, plogLik, ESS, pKLIC,
GOSHO and RJC.
mcglm documentation built on Sept. 16, 2022, 1:06 a.m.
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| pAIC | R Documentation |
Pseudo Akaike Information Criterion
Description
Extract the pseudo Akaike information criterion (pAIC)
for objects of mcglm class.
Usage
pAIC(object, verbose = TRUE)
Arguments
object |
an object or a list of objects representing a model
of |
verbose |
logical. Print or not the pAIC value. |
Value
Returns the value of the pseudo Akaike information criterion (pAIC).
Author(s)
Wagner Hugo Bonat, wbonat@ufpr.br
Source
Bonat, W. H. (2018). Multiple Response Variables Regression Models in R: The mcglm Package. Journal of Statistical Software, 84(4):1–30.
See Also
gof, plogLik, ESS, pKLIC,
GOSHO and RJC.
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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