AICc {qpcR}R Documentation

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 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.

Usage

  AICc(object)

Arguments

object a fitted model.

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.

Value

The second-order corrected AIC value.

Author(s)

Andrej-Nikolai Spiess

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. Biometrika 76, 297-307.

See Also

AIC, logLik.

Examples

m <- pcrfit(reps, 1, 2, l5())
AICc(m)

[Package qpcR version 1.1-8 Index]