Generalized Additive models for location scale and shape (GAMLSS) in R

Link to Journal Article Here

Who It’s For: Anyone, with a strong foundation in GLM and GAM, who is interested in modelling more than just the location of the mean by including parameters like the spread and shape of a distribution in R. 

Why We Love It: When deciding what type of regression model to use, it can be helpful to compare the properties of your data with other datasets that use the same model. This article describes each data set and explains why GAMLSS was chosen as the best way to capture relationship between a response variable and its predictors. An R script with examples is also provided.

Citation: Stasinopoulos, D. M., & Rigby, R. A. (2007). Generalized Additive Models for Location Scale and Shape (GAMLSS) in R. Journal of Statistical Software, 23(7), 1–46. https://doi.org/10.18637/jss.v023.i07