The Bayesian procedure starts with one warplet in the model and uses the posterior distributions as priors for a more extended model with one more warplet. The model is built with adding one warplet at a time and allows for amplitude variations.
|Author||L. Slaets, G. Claeskens, B.W. Silverman|
|Date of publication||2013-10-11 12:54:06|
|Maintainer||Gerda Claeskens <[email protected]>|
|Package repository||View on CRAN|
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