Estimate generalized additive mixed models via a version of
         function gamm() from 'mgcv', using 'lme4' for estimation.

Process in-situ Gamma-Ray Spectrometry for Luminescence
    Dating. This package allows to import, inspect and correct the energy
    shifts of gamma-ray spectra. It provides methods for estimating the
    gamma dose rate by the use of a calibration curve as described in
    Mercier and Falguères (2007). The package only supports Canberra CNF
    and TKA and Kromek SPE files.

Performs Gamma regression, where both mean and shape parameters follows lineal regression structures.

An interface for fitting generalized additive models (GAMs) and generalized additive mixed models (GAMMs) using the 'lme4' package as the computational engine, as described in Helwig (2024) <doi:10.3390/stats7010003>. Supports default and formula methods for model specification, additive and tensor product splines for capturing nonlinear effects, and automatic determination of spline type based on the class of each predictor. Includes an S3 plot method for visualizing the (nonlinear) model terms, an S3 predict method for forming predictions from a fit model, and an S3 summary method for conducting significance testing using the Bayesian interpretation of a smoothing spline.

Uses a slice sampling-based Markov chain Monte Carlo to
        conduct Bayesian fitting and inference for generalized additive
        mixed models.  Generalized linear mixed models and generalized 
        additive models are also handled as special cases of generalized
        additive mixed models. The methodology and software is described 
        in Pham, T.H. and Wand, M.P. (2018). Australian and New Zealand
        Journal of Statistics, 60, 279-330 <DOI:10.1111/ANZS.12241>.

Robust regression via gamma-divergence with L1, elastic net and ridge.

To calculate the relative risk (RR) for the generalized additive model.

Using overlap grouped-lasso penalties, 'gamsel' selects whether a term in a 'gam' is nonzero, linear, or a non-linear spline (up to a specified max df per variable). It fits the entire regularization path on a grid of values for the overall penalty lambda, both for gaussian and binomial families. See  <doi:10.48550/arXiv.1506.03850> for more details.