hierMeanReg {Bolstad2}R Documentation

Hierarchical Normal Means Regression Model

Description

fits a hierarchical normal model of the form E[y_{ij}] = μ_{j} + β_{1}x_{i1}+...+β_{p}x_{ip}

Usage

hierMeanReg(design, priorTau, priorPsi, priorVar,
            priorBeta = NULL, steps = 1000, startValue = NULL,
            randomSeed = NULL)

Arguments

design a list with elements y = response vector, group = grouping vector, x = matrix of covariates or NULL if there are no covariates
priorTau a list with elements tau0 and v0
priorPsi a list with elements psi0 and eta0
priorVar a list with elements s0 and kappa0
priorBeta a list with elements b0 and bMat or NULL if x is NULL
steps the number of Gibbs sampling steps to take
startValue a list with possible elements tau, psi, mu, sigmasq and beta. tau, psi and sigmasq must all be scalars. mu and beta must be vectors with as many elements as there are groups and covariates respectively
randomSeed a random seed for the random number generator

Value

A data frame with variables:

tau Samples from the posterior distribution of tau
psi Samples from the posterior distribution of psi
mu Samples from the posterior distribution of mu
beta Samples from the posterior distribution of beta if there are any covariates
sigmaSq Samples from the posterior distribution of σ^2
sigma Samples from the posterior distribution of sigma

Examples

priorTau <- list(tau0 = 0, v0 = 1000)
priorPsi <- list(psi0 = 500, eta0 = 1)
priorVar <- list(s0 = 500, kappa0 = 1)
priorBeta <- list(b0 = c(0,0), bMat = matrix(c(1000,100,100,1000), nc = 2))

data(hiermeanRegTest.df)
data.df <- hiermeanRegTest.df
design <- list(y = data.df$y, group = data.df$group,
               x = as.matrix(data.df[,3:4]))
r<-hierMeanReg(design, priorTau, priorPsi, priorVar, priorBeta)

oldPar <- par(mfrow = c(3,3))
plot(density(r$tau))
plot(density(r$psi))
plot(density(r$mu.1))
plot(density(r$mu.2))
plot(density(r$mu.3))
plot(density(r$beta.1))
plot(density(r$beta.2))
plot(density(r$sigmaSq))
par(oldPar)

## example with no covariates
priorTau <- list(tau0 = 0, v0 = 1000)
priorPsi <- list(psi0 = 500, eta0 = 1)
priorVar <- list(s0 = 500, kappa0 = 1)

data(hiermeanRegTest.df)
data.df <- hiermeanRegTest.df
design <- list(y = data.df$y, group = data.df$group, x = NULL)
r<-hierMeanReg(design, priorTau, priorPsi, priorVar)

oldPar <- par(mfrow = c(3,2))
plot(density(r$tau))
plot(density(r$psi))
plot(density(r$mu.1))
plot(density(r$mu.2))
plot(density(r$mu.3))
plot(density(r$sigmaSq))
par(oldPar)


[Package Bolstad2 version 1.0-26 Index]