dglars-package: Differential Geometric Least Angle Regression

In dglars: Differential Geometric Least Angle Regression

Differential Geometric Least Angle Regression

Description

Differential geometric least angle regression method for fitting sparse generalized linear models. In this version of the package, the user can fit models specifying Gaussian, Poisson, Binomial, Gamma and Inverse Gaussian family. Furthermore, several link functions can be used to model the relationship between the conditional expected value of the response variable and the linear predictor. The solution curve can be computed using an efficient predictor-corrector or a cyclic coordinate descent algorithm, as described in the paper linked to via the URL below.

Details

Package:	dglars
Type:	Package
Version:	2.1.7
Date:	2023-10-08
License:	GPL (>=2)

Author(s)

Luigi Augugliaro
Maintainer: Luigi Augugliaro <[e-mail]>

References

Augugliaro L., Mineo A.M. and Wit E.C. (2016) <doi:10.1093/biomet/asw023> A differential-geometric approach to generalized linear models with grouped predictors, Vol 103(3), 563-577.

Augugliaro L., Mineo A.M. and Wit E.C. (2014) <doi:10.18637/jss.v059.i08> dglars: An R Package to Estimate Sparse Generalized Linear Models, Journal of Statistical Software, Vol 59(8), 1-40. https://www.jstatsoft.org/v59/i08/.

Augugliaro L., Mineo A.M. and Wit E.C. (2013) <doi:10.1111/rssb.12000> dgLARS: a differential geometric approach to sparse generalized linear models, Journal of the Royal Statistical Society. Series B., Vol 75(3), 471-498.

Efron B., Hastie T., Johnstone I. and Tibshirani R. (2004) <doi:10.1214/009053604000000067> Least Angle Regression, The Annals of Statistics, Vol. 32(2), 407-499.

Pazira H., Augugliaro L. and Wit E.C. (2018) <doi:10.1007/s11222-017-9761-7> Extended differential-geometric LARS for high-dimensional GLMs with general dispersion parameter, Statistics and Computing, Vol 28(4), 753-774.

dglars documentation built on Oct. 10, 2023, 1:08 a.m.