The PCLM method is based on the composite link model, with a penalty added to ensure the smoothness of the target distribution. Estimates are obtained by maximizing a penalized likelihood. This maximization is performed efficiently by a version of the iteratively reweighted least-squares algorithm. Optimal values of the smoothing parameter are chosen by minimizing Bayesian or Akaike’ s Information Criterion [From Rizzi et al. 2015 abstract].
|Author||Maciej J. Danko <[email protected]> <[email protected]>, Marius Pascariu <[email protected]>, Silvia Rizzi <[email protected]>,|
|Maintainer||Marius Pascariu <[email protected]>, Maciej J. Danko <[email protected]> <[email protected]>|
|Package repository||View on GitHub|
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