MARS: selecting basis functions and knots with an empirical Bayes method (Q964645)
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scientific article; zbMATH DE number 5697311
| Language | Label | Description | Also known as |
|---|---|---|---|
| English | MARS: selecting basis functions and knots with an empirical Bayes method |
scientific article; zbMATH DE number 5697311 |
Statements
MARS: selecting basis functions and knots with an empirical Bayes method (English)
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22 April 2010
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A Bayesian approach to multivariate adaptive regression spline (MARS) estimation is considered. It is shown that the Bayesian estimation is equivalent to maximum penalized likelihood estimation. Akaike's Bayes information criterion is used for the selection of the number and combination of basis functions. Applications to real data examples are also considered.
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multivariate adaptive regression splines
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penalized likelihood
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Akaike information criterion
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