groupEnet: Group Elastic Net for Gaussian Likelihood

In abnormally-distributed/Bayezilla: Bayesian Models With JAGS and Several Utilities for Data Exploration and Model Evaluation.

Description

The Bayesian elastic net described by Li and Lin (2010) modified for use as a group selection model, akin to the Group Bayesian LASSO described by Kyung et al. (2010). Group selection is a method described first by Yuan & Lin (2006) for applying shrinkage penalties to coefficients that have some natural grouping, such as refelcting dummy variables of a single factor, or coefficients corresponding to related variables (for example, predictors derived from a single brain region).

The model structure is given below:

Usage

groupEnet(X, y, idx, family = "gaussian", log_lik = FALSE,
  iter = 10000, warmup = 1000, adapt = 2000, chains = 4,
  thin = 1, method = "parallel", cl = makeCluster(2), ...)

Arguments

X	the model matrix. Construct this manually with model.matrix()[,-1]
y	the outcome variable
idx	the group labels. Should be of length = to ncol(model.matrix()[,-1]) with the group assignments for each covariate. Please ensure that you start numbering with 1, and not 0.
family	one of "gaussian" (default), "binomial", or "poisson"
log_lik	Should the log likelihood be monitored? The default is FALSE.
iter	How many post-warmup samples? Defaults to 10000.
warmup	How many warmup samples? Defaults to 1000.
adapt	How many adaptation steps? Defaults to 2000.
chains	How many chains? Defaults to 4.
thin	Thinning interval. Defaults to 1.
method	Defaults to "parallel". For an alternative parallel option, choose "rjparallel" or. Otherwise, "rjags" (single core run).
cl	Use parallel::makeCluster(# clusters) to specify clusters for the parallel methods. Defaults to two cores.
...	Other arguments to run.jags.

Value

A run.jags object

References

Yuan, Ming; Lin, Yi (2006). Model Selection and Estimation in Regression with Grouped Variables. Journal of the Royal Statistical Society. Series B (statistical Methodology). Wiley. 68 (1): 49–67. doi:10.1111/j.1467-9868.2005.00532.x

Kyung, M., Gill, J., Ghosh, M., and Casella, G. (2010). Penalized regression, standard errors, and bayesian lassos. Bayesian Analysis, 5(2):369–411.

Li, Qing; Lin, Nan. The Bayesian elastic net. Bayesian Anal. 5 (2010), no. 1, 151–170. doi:10.1214/10-BA506. https://projecteuclid.org/euclid.ba/1340369796

Examples

groupEnet()

abnormally-distributed/Bayezilla documentation built on Oct. 31, 2019, 1:57 a.m.