denet: The elastic net prior distribution

In gren: Adaptive Group-Regularized Logistic Elastic Net Regression

Description

Density function and random number generator for the elastic net prior distribution.

Usage

denet(x, lambda1=1, lambda2=1, log=FALSE)

renet(n, lambda1=1, lambda2=1)

Arguments

x	vector of quantiles
n	number of samples
lambda1	lambda1 parameter value
lambda2	lambda2 parameter value
log	should the logarithm of the density be returned

Details

The elastic net prior density has density:

f(x)=g(λ_1,λ_2) e^[-0.5*(λ_1 |x| + λ_2 x^2)]

Value

denet gives the density of the input x. renet gives a vector of length n of random values.

Author(s)

Magnus M. Münch <[e-mail]>

References

Münch, M.M., Peeters, C.F.W., van der Vaart, A.W., and van de Wiel, M.A. (2018). Adaptive group-regularized logistic elastic net regression. arXiv:1805.00389v1 [stat.ME].

Examples

## Create data
n <- 100
x <- renet(n)
hist(x)

## Calculate density
dens <- denet(x)
plot(sort(x), dens[order(x)])

gren documentation built on May 1, 2019, 7:31 p.m.