logshrink: Wavelet shrinkage under logistic prior.

In Alexestat/bayesShrink: Bayesian wavelet shrinkage

Description

Performs bayesian shrinkage under logistic prior on empirical wavelet coefficients.

Usage

logshrink(d, alpha, t, s)

Arguments

d	The empirical wavelet coefficients vector.
alpha	The weight of the point mass at zero function of the prior.
t	The scale parameter of the logistic prior.
s	The standard deviation of the normal random noise.

Value

The shrunk wavelet coefficients vector.

Examples

logshrink(c(0.5,1,2),0.9,1,1)

Alexestat/bayesShrink documentation built on Oct. 6, 2020, 12:42 a.m.