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freezenik
bamlss: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 (2019) <doi:10.1080/10618600.2017.1407325> and the R package in Umlauf, Klein, Simon, Zeileis (2021) <doi:10.18637/jss.v100.i04>.
Maintained by Nikolaus Umlauf. Last updated 6 months ago.
1 stars 5.76 score 239 scripts 5 dependents
mauriceoconnell
causalPAF:Causal Effect for Population Attributable Fractions (PAF)
Calculates population attributable fraction causal effects. The 'causalPAF' package contains a suite of functions for causal analysis calculations of population attributable fractions (PAF) given a causal diagram which apply both: Pathway-specific population attributable fractions (PS-PAFs) O’Connell and Ferguson (2022) <doi:10.1093/ije/dyac079> and Sequential population attributable fractions Ferguson, O’Connell, and O’Donnell (2020) <doi:10.1186/s13690-020-00442-x>. Results are presentable in both table and plot format.
Maintained by Maurice OConnell. Last updated 3 years ago.
2 stars 3.00 score 1 scripts