AICc: Akaike's second-order corrected Information Criterion
Description
Calculates the second-order corrected Akaike Information Criterion for objects of class pcrfit, nls, lm, glm or any other models from which coefficients and residuals can be extracted. This is a modified version of the original AIC which compensates for bias with small $n$. As qPCR data usually has $\frac{n}{k} < 40$ (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, and $n$ = number of observations. For large $n$, AICc converges to AIC.
References
Akaike Information Criterion Statistics.
Sakamoto Y, Ishiguro M and Kitagawa G.
D. Reidel Publishing Company (1986).
Regression and Time Series Model Selection in Small Samples.
Hurvich CM & Tsai CL.
Biometrika (1989), 76: 297-307.