mcmcRun_Normal_DPM: mcmcRun_Normal_DPM: MCMC sampler for IV Analysis with...

In SamAdhikari/BayesIV_0.1: A package to fit Bayesian Instrumental Variable model with latent factors

Description

mcmcRun_Normal_DPM: MCMC sampler for IV Analysis with Dirichlet process mixture prior on the errors and Normal prior on the latent factors

Usage

mcmcRun_Normal_DPM(Yobs, Tr, X, Z, niter, priors = NULL, initialVals = NULL)

Arguments

Yobs	: Input numeric vector of observed outcome of length n, can be binary or continuous.
Tr	: Binary numeric vector of treatment indicator.
X	: numeric matrix of covariates of dimension n-By-p
Z	: numeric vector of instrumental variable of length n
niter	: number of MCMC sampler to be run
priors:	list to specify the parameters for the prior distribution. If NULL, default specification is used.
initialVals:	list of initial values for each parameter. If NULL, default setting for initialization is used.

Value

runModel : list of posterior samples for each parameter

Author(s)

Sam Adhikari

Examples

{ 
obj = mcmcRun_Normal_DPM(Yobs=Yobs,Tr=D,X=X[,-1],Z=Z,niter=10,priors=NULL,initialVals=NULL)
}

SamAdhikari/BayesIV_0.1 documentation built on May 24, 2019, 8:50 a.m.