| AIC_HY {SoilHyP} | R Documentation |
Akaike Information Criterion (AIC)
Description
Akaike Information Criterion with or without correction term. Expression from Ye et al. (2008). Correction term by Hurvich and Tsai (1989).
Usage
AIC_HY(Phi, n.data, n.par, corr = TRUE)
Arguments
Phi |
objective function value |
n.data |
number of measured data |
n.par |
number of adjustable parameters |
corr |
correction term TRUE or FALSE (see details) |
Details
corr:
If number of measurements is small compared to the number of parameters, AIC can be extended by a correction term.
References
Ye, M., P.D. Meyer, and S.P. Neuman (2008): On model selection criteria in multimodel analysis. Water Resources Research 44 (3) W03428, doi:10.1029/2008WR006803.
Hurvich, C., and C. Tsai (1989): Regression and time series model selection in small samples. Biometrika 76 (2), 297–307, doi:10.1093/biomet/76.2.297.
Peters and Durner (2015): SHYPFIT 2.0 User's Manual.
Akaike, H. (1974): A new look at statistical model identification, IEEE Trans. Autom. Control, AC-19, 716–723.