getEstimator {BayesSUR}

extract the posterior mean of parameters

Description

Extract the posterior mean of the parameters of a BayesSUR class object.

Usage

getEstimator(object, estimator = "gamma", Pmax = 0, beta.type = "marginal")

Arguments

object

an object of class BayesSUR

estimator

the name of one estimator. Default is the latent indicator estimator "gamma". Other options "beta", "Gy", "CPO" and "logP" correspond the marginal (conditional) coefficient matrix if beta.type="marginal"("conditional"), response graph and conditional predictive ordinate (CPO) respectively

Pmax

threshold that truncate the estimator "gamma" or "Gy". Default is 0. If Pmax=0.5 and beta.type="conditional", it gives median probability model betas

beta.type

the type of output beta. Default is marginal, giving marginal beta estimation. If beta.type="conditional", it gives beta estimation conditional on gamma=1

Value

Return the estimator from an object of class BayesSUR. It is a matrix if the length of argument marginal is greater than 1. Otherwise, it is a list

Examples

data("exampleEQTL", package = "BayesSUR")
hyperpar <- list(a_w = 2, b_w = 5)

set.seed(9173)
fit <- BayesSUR(
  Y = exampleEQTL[["blockList"]][[1]],
  X = exampleEQTL[["blockList"]][[2]],
  data = exampleEQTL[["data"]], outFilePath = tempdir(),
  nIter = 10, burnin = 0, nChains = 1, gammaPrior = "hotspot",
  hyperpar = hyperpar, tmpFolder = "tmp/"
)

## check output
# extract the posterior mean of the coefficients matrix
beta_hat <- getEstimator(fit, estimator = "beta")