sasp: Shape Adaptive Shrinkage Prior

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

Description

The shape adaptive shrinkage prior of Sillanpää & Mutshinda (2011). This is essentially bridge regression, but with a shape parameter describing the Lp norm that is allowed to vary rather than stay fixed at a single value. The generalized gaussian prior is parameterized in the manner of Mallick & Yi (2018) rather than the method originally described in Sillanpää & Mutshinda (2011). Analytically, this makes no difference, but computationally, it is much faster and more stable.

The benefit of the shape adaptive shrinkage prior is that one need not pick a specific norm. Hence, if there is uncertainty over whether or not one wishes to choose the L1 norm (LASSO) or L2 norm (Ridge), this integrates over a reasonable range of values. The gamma prior for the norm has an expected value of 1.4, which gives a reasonable compromise between the LASSO and Ridge.

Model Specification:



Plugin Pseudo-Variances:

Usage

sasp(formula, data, family = "gaussian", log_lik = FALSE,
  iter = 10000, warmup = 1000, adapt = 2000, chains = 4,
  thin = 1, method = "parallel", cl = makeCluster(2), ...)

Arguments

formula	the model formula
data	a data frame.
family	one of "gaussian", "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 runjags object

References

Mallick, H. & Yi, N. (2018) Bayesian bridge regression, Journal of Applied Statistics, 45:6, 988-1008, DOI: 10.1080/02664763.2017.1324565

Sillanpää, S., & Mutshinda, C., (2011) Bayesian shrinkage analysis of QTLs under shape-adaptive shrinkage priors, and accurate re-estimation of genetic effects. Heredity volume 107, pages 405–412. doi: 10.1038/hdy.2011.37

Examples

sasp()

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