AICc {qpcR} | R Documentation |
Calculates the second-order corrected Akaike Information Criterion for objects of class drc
, lm
, glm
, nls
or any other models where 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.
AICc(object)
object |
a fitted model. |
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.
The second-order corrected AIC value.
Andrej-Nikolai Spiess
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. Biometrika 76, 297-307.
m <- pcrfit(reps, 1, 2, l5()) AICc(m)