cash: Fit Empirical Bayes Normal Means with Correlated Noise

In LSun/cashalpha: Correlated Adaptive Shrinkage, using Empirical Bayes

Description

This is the main interface for fitting correlated EBNM models based on algorithms proposed by Sun and Stephens. The default behaviour is simply to run the biconvex optimization and return the result and posterior calculations.

Usage

cash(x, s = 1, deltaAt0 = TRUE, gd.order = 10, omega.lambda = 10,
  omega.rho = 0.5, omega.pen = NULL, mixsd.mult = sqrt(2),
  gd.priority = FALSE, control = list(maxiter = 50))

Arguments

x	A p vector of observations
s	A scalar or a p vector of standard deviations.
deltaAt0	Logical, indicating whether to use a point mass at zero as one of components for a mixture distribution of the prior.
gd.priority	Logical, indicating whether to optimizer over prior

LSun/cashalpha documentation built on May 20, 2019, 5:40 p.m.