AICc: Akaike's second-order Information Criterion for small sample numbers
Description
Calculates the second-order (corrected) Akaike information criterion for 'drc' objects.
This is a modified version of the original AIC which compensates for bias with small n.
As qPCR data usually has n/par < 40 (see original reference), AICc was implemented to correct for this.
Usage
AICc(object)
Arguments
object
an object of class 'drc'.
Value
The second-order AIC value.
Details
Extends the AIC such that $AICc = AIC+\frac{2k(k + 1)}{n - k - 1}$, with k = number of parameters + 1, and n = number of observations.
For large n, AICc converges to AIC.
References
Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986). Akaike Information Criterion Statistics. D. Reidel Publishing Company.
Hurvich CM & Tsai CL (1989) Regression and Time Series Model Selection in Small Samples Biometrika76, 297-307.