AIC_HY

0th

Percentile

Akaike Information Criterion (AIC)

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<U+2013>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<U+2013>723.

Aliases
  • AIC_HY
Documentation reproduced from package SoilHyP, version 0.1.3, License: GPL (>= 2)

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