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Modeling and Inverse Problems in the Presence of Uncertainty
book

Modeling and Inverse Problems in the Presence of Uncertainty

by H. T. Banks, Shuhua Hu, W. Clayton Thompson
April 2014
Intermediate to advanced content levelIntermediate to advanced
405 pages
13h
English
Chapman and Hall/CRC
Content preview from Modeling and Inverse Problems in the Presence of Uncertainty
132 Modeling and Inverse Problems in the Presence of Uncertainty
Null hypothesis testing should not be mixed with the information crite-
rion in reporting the results.
The information criterion is not a “test,” so one s hould avoid use of
“significant” and “not significant,” or “rejected” and “not rejected”
in rep orting results.
One should not use the AIC to rank models in the set and then test
whether the best model is “significantly b etter” than the second-
best model.
All the comp onents in each log-likelihood function should be retained
when comparing models with different probability distr ibutio n forms.
For example, if we want to use the
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Publisher Resources

ISBN: 9781482206432