dlprior: Title Simulate the dirichlet laplace shrinkage prior

In dlbayes: Use Dirichlet Laplace Prior to Solve Linear Regression Problem and Do Variable Selection

Description

This function generates random deviates from dirichlet laplace shrinkage prior and can plot the distribution function.

Usage

dlprior(hyper = 1/2, p = 1e+05, plt = TRUE, min = -5, max = 5,
  sigma = 1)

Arguments

hyper	important hyperparameter that related to posterior shrinkage scales and prior distribution
p	number of observations
plt	whether to plot the dirichlet laplace prior. default TRUE means plot the distribution
min	left point of the plot graph
max	right point of the plot graph
sigma	the value equals to normal noises' standard deviations

Value

beta	A p*1 vector. p observations from the distribution

Examples

{theta=dlprior(hyper=1/2,p=100000,plt=TRUE,min=-5,max=5,sigma=1)}

dlbayes documentation built on May 2, 2019, 8:28 a.m.