bamlss statistics

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bamlss specifications


Unique identifier OMICS_20732
Name bamlss
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 1.0-0
Stability Stable
methods, parallel, Matrix, Formula, fields, survival, mvtnorm, mgcv, coda, akima, zoo, colorspace, rjags, maps, mapdata, sp, glmnet, R(≥3.2.3), spdep, bit, BayesX, raster, MBA, gamlss, geoR, BayesXsrc, maptools, spatstat, keras, splines2, sdPrior, glogis
Maintained Yes


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  • person_outline Meike Köhler <>
  • person_outline Nikolaus Umlauf <>

Additional information

Publication for bamlss

bamlss in publication

PMCID: 5488632
PMID: 28713200
DOI: 10.1002/joc.4913

[…] to estimate the nonparametric smooth model as specified in equations – suitable software is required which allows for a zero left‐censored normal distribution. we are using a novel r package ‘bamlss’ () which offers a flexible bayesian framework for additive models for location, scale, and shape (and beyond), and the capability to handle (very) large data sets. other possible software […]

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bamlss institution(s)
Institute of Diabetes Research, Helmholtz Zentrum Munchen, and Forschergruppe Diabetes, Klinikum rechts der Isar, Technische Universitat München, Neuherberg, Germany; Department of Statistics, Faculty of Economics and Statistics, Universitat Innsbruck, Innsbruck, Austria; Forschergruppe Diabetes e.V., Neuherberg, Germany; Department of Statistics, Ludwig-Maximilians-Universitat München, München, Germany
bamlss funding source(s)
Supported by the JDRF (JDRF-2-SRA-2015-13-Q-R); by grants from the German Federal Ministry of Education and Research (BMBF) to the German Center for Diabetes Research; a grant from the Helmholtz International Research Group (HIRG-0018); and the German research foundation (DFG) through Emmy Noether grant GR 3793/1-1.

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