gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework

Article, Preprint English OPEN
Benjamin Hofner; Andreas Mayr; Matthias Schmid;
(2016)
  • Publisher: Foundation for Open Access Statistics
  • Journal: Journal of Statistical Software (issn: 1548-7660)
  • Publisher copyright policies & self-archiving
  • Related identifiers: doi: 10.18637/jss.v074.i01
  • Subject: Statistics - Computation | high-dimensional data | additive models | prediction intervals | HA1-4737 | additive models; prediction intervals; high-dimensional data | Statistics

Generalized additive models for location, scale and shape are a flexible class of regression models that allow to model multiple parameters of a distribution function, such as the mean and the standard deviation, simultaneously. With the R package gamboostLSS, we provid... View more
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  • Related Research Results (1)
    Inferred
    Boosted Beta Regression (2013)
    73%
  • Metrics
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