bamlss statistics

To access cutting-edge analytics on consensus tools, life science contexts and associated fields, you will need to subscribe to our premium service.

Subscribe
info

Citations per year

Citations chart
info

Popular tool citations

chevron_left Single SNP association chevron_right
Popular tools chart
info

Tool usage distribution map

Tool usage distribution map
info

Associated diseases

Associated diseases

bamlss specifications

Information


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
Requirements
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

Versioning


Add your version

Documentation


Maintainers


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

Additional information


https://eeecon.uibk.ac.at/wopec2/repec/inn/wpaper/2017-05.pdf

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 […]


To access a full list of publications, you will need to upgrade to our premium service.

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.

bamlss reviews

star_border star_border star_border star_border star_border
star star star star star

Be the first to review bamlss