bamlss (1.1-0)

0 users

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

http://www.bamlss.org/
http://cran.r-project.org/web/packages/bamlss

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 (2019) and the R package in Umlauf, Klein, Simon, Zeileis (2019) .

Maintainer: Nikolaus Umlauf
Author(s): Nikolaus Umlauf [aut, cre] (<https://orcid.org/0000-0003-2160-9803>), Nadja Klein [aut], Achim Zeileis [aut] (<https://orcid.org/0000-0003-0918-3766>), Meike Koehler [ctb], Thorsten Simon [aut] (<https://orcid.org/0000-0002-3778-7738>), Stanislaus Stadlmann [ctb]

License: GPL-2 | GPL-3

Uses: coda, colorspace, Formula, Matrix, MBA, mgcv, mvtnorm, sp, survival, akima, ff, fields, gamlss, geoR, mapdata, maps, maptools, spatstat, spdep, zoo, glmnet, rjags, BayesX, bit, MASS, raster, ffbase, glogis, knitr, BayesXsrc, R2BayesX, sdPrior, scoringRules, splines2, keras

Released 18 days ago.


5 previous versions

Ratings

Overall:

  (0 votes)

Documentation:

  (0 votes)

Log in to vote.

Reviews

No one has written a review of bamlss yet. Want to be the first? Write one now.


Related packages: BACCO, BMA, BayHaz, BayesTree, BayesValidate, Bolstad, EbayesThresh, HI, Hmisc, LearnBayes, MCMCpack, MNP, MasterBayes, R2WinBUGS, RJaCGH, Runuran, arm, bayesSurv, bayesm, bayesmix(20 best matches, based on common tags.)


Search for bamlss on google, google scholar, r-help, r-devel.

Visit bamlss on R Graphical Manual.