AICc {Dark} | R Documentation |
Akaike information criterion
Description
The Akaike information criterion corrected for small sample size is a measure of the relative quality of a model. The AICc is calculated from a 'dark' object.
Usage
AICc(obj)
Arguments
obj |
A dark object This object must have at least the following elements:
|
Value
The value returned is an indication of the information lost by fitting a particular model to the data, and is only of merit when compared to the value from another model.
Author(s)
Jeremiah MF Kelly
Faculty of Life Sciences, The University of Manchester, M13 9PL, UK
References
See http://en.wikipedia.org/wiki/Akaike_information_criterion.
K. Burnham and D. Anderson. Model selection and multi-model inference: a practical information- theoretic approach. Springer, 2002.
Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986). Akaike Information Criterion Statistics. D. Reidel Publishing Company.
See Also
Examples
AICc(dark)