AICc: Akaike's second-order corrected Information Criterion for small sample sizes
Description
Calculates the second-order corrected Akaike Information Criterion for objects of class drc, lm, glm, nls
or any other models from which coefficients and residuals can be extacted.
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
a fitted model.
Value
The second-order corrected 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.