AICc: Corrected AIC
In gamlr: Gamma Lasso Regression
AICc R Documentation
Corrected AIC
Description
Corrected AIC calculation.
Usage
AICc(object, k=2)
Arguments
object
Some model object that you can call logLik on (such as a gamlr or glm fit).
k
The usual AIC complexity penalty. k defaults to 2.
Details
This works just like usual AIC, but instead calculates the small sample (or high dimensional) corrected version from Hurvich and Tsai
AICc = -2\log LHD + k*df*\frac{n}{n-df-1}.
Value
A numeric value for every model evaluated.
Author(s)
Matt Taddy mataddy@gmail.com
References
Hurvich, C. M. and C-L Tsai, 1989. "Regression and Time Series Model Selection in Small Samples", Biometrika 76.
See Also
gamlr, hockey
gamlr documentation built on April 17, 2023, 1:06 a.m.
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| AICc | R Documentation |
Corrected AIC
Description
Corrected AIC calculation.
Usage
AICc(object, k=2)
Arguments
object |
Some model object that you can call |
k |
The usual |
Details
This works just like usual AIC, but instead calculates the small sample (or high dimensional) corrected version from Hurvich and Tsai
AICc = -2\log LHD + k*df*\frac{n}{n-df-1}.
Value
A numeric value for every model evaluated.
Author(s)
Matt Taddy mataddy@gmail.com
References
Hurvich, C. M. and C-L Tsai, 1989. "Regression and Time Series Model Selection in Small Samples", Biometrika 76.
See Also
gamlr, hockey
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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