MDL Returns Rissanen's Minimum Description Length.
m=model that has been estimated using System Identification toolbox.
This function requires System Identification toolbox to work. Plug-compatible with built-in functions aic(m) and fpe(m).
MDL can be used like AIC or FPE to compare models of different complexities. Choose model with lowest MDL or AIC or FPE. Pintelon & Schoukens (2001) pp. 329,550 say MDL is better than AIC because AIC tends to select a too-complex model.
Minimum Description Length = V*(1+d*log(N)/N)
where V=loss function, d=number of fitted model parameters, and N=number of data points.
Cite As
William Rose (2024). mdl(m) (https://www.mathworks.com/matlabcentral/fileexchange/56300-mdl-m), MATLAB Central File Exchange. Retrieved .
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- Control Systems > System Identification Toolbox >
- Control Systems > System Identification Toolbox > Linear Model Identification >
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