Akaike Information Criterion (AIC)

and the Schwarz Information Criterion

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*  The Akaike Information Criterion compares an   *
*  improvement (increase) in max log(likelihood)  *
*  against added complexity of the model caused   *
*  by additional parameters (i.e. overfitting).   *
***************************************************

 max log(likelihood): 
    without POD floor or ceiling = -230.49  
    with POD ceiling only        = -206.541 *** 
 Larger maximum likelihood is better. 

 Akaike Information Criterion (AIC): 
    without POD floor or ceiling = 464.979  
    with POD ceiling only        = 419.083 *** 
 Smaller AIC is better. 

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Based on the AIC, using a POD ceiling model
appears to be justified.
************************************************

The Schwarz Criterion (Bayesian Information
Criterion) is more conservative than the AIC.

Schwarz Criterion (BIC): 
without POD floor or ceiling = 473.045 
with POD ceiling only = 431.182 *** 
Smaller BIC is better.


Warning:
Floor/Ceiling models should be based on
a minimum of 150 observations.

Models with Floor AND Ceiling should be
based on a minimum of 300 observations.

Number of observations in this analysis: 417

MIL-HDBK-1823, v7.1.6 (WorkshopMenu, v3.1)
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