bamlss (0.1-2)

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Bayesian Additive Models for Location Scale and Shape (and Beyond).

Infrastructure for estimating probabilistic distributional regression models in a Bayesian framework. The distribution parameters may capture location, scale, shape, etc. and every parameter may depend on complex additive terms (fixed, random, smooth, spatial, etc.) similar to a generalized additive model. The conceptual and computational framework is introduced in Umlauf, Klein, Zeileis (2017) .

Maintainer: Nikolaus Umlauf
Author(s): Nikolaus Umlauf [aut, cre], Nadja Klein [aut], Achim Zeileis [aut], Meike Koehler [aut]

License: GPL-2 | GPL-3

Uses: coda, colorspace, Formula, Matrix, MBA, mgcv, mvtnorm, sp, spam, survival, akima, fields, gamlss, geoR, mapdata, maps, maptools, spatstat, spdep, zoo, rjags, BayesX, bit, raster, BayesXsrc

Released 11 months ago.

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