rivGibbs {bayesm} | R Documentation |
rivGibbs
is a Gibbs Sampler for a linear structural equation with an arbitrary number of instruments.
rivGibbs(Data, Prior, Mcmc)
Data |
list(z,w,x,y) |
Prior |
list(md,Ad,mbg,Abg,nu,V) (optional) |
Mcmc |
list(R,keep) (R required) |
Model:
x=z'delta + e1.
y=beta*x + w'gamma + e2.
e1,e2 ~ N(0,Sigma).
Priors:
delta ~ N(md,Ad^{-1}). vec(beta,gamma) ~ N(mbg,Abg^{-1})
Sigma ~ IW(nu,V)
List arguments contain:
z
y
x
w
md
Ad
mbg
Abg
nu
V
R
keep
a list containing:
deltadraw |
R/keep x dim(delta) array of delta draws |
betadraw |
R/keep x 1 vector of beta draws |
gammadraw |
R/keep x dim(gamma) array of gamma draws |
Sigmadraw |
R/keep x 4 array of Sigma draws |
## if(nchar(Sys.getenv("LONG_TEST")) != 0) {R=2000} else {R=10} set.seed(66) simIV = function(delta,beta,Sigma,n,z,w,gamma) { eps = matrix(rnorm(2*n),ncol=2) %*% chol(Sigma) x = z %*% delta + eps[,1]; y = beta*x + eps[,2] + w%*%gamma list(x=as.vector(x),y=as.vector(y)) } n = 200 ; p=1 # number of instruments z = cbind(rep(1,n),matrix(runif(n*p),ncol=p)) w = matrix(1,n,1) rho=.8 Sigma = matrix(c(1,rho,rho,1),ncol=2) delta = c(1,4); beta = .5; gamma = c(1) simiv = simIV(delta,beta,Sigma,n,z,w,gamma) Mcmc=list(); Prior=list(); Data = list() Data$z = z; Data$w=w; Data$x=simiv$x; Data$y=simiv$y Mcmc$R = R Mcmc$keep=1 out=rivGibbs(Data=Data,Prior=Prior,Mcmc=Mcmc) cat(" deltadraws ",fill=TRUE) mat=apply(out$deltadraw,2,quantile,probs=c(.01,.05,.5,.95,.99)) mat=rbind(delta,mat); rownames(mat)[1]="delta"; print(mat) cat(" betadraws ",fill=TRUE) qout=quantile(out$betadraw,probs=c(.01,.05,.5,.95,.99)) mat=matrix(qout,ncol=1) mat=rbind(beta,mat); rownames(mat)=c("beta",names(qout)); print(mat) cat(" Sigma draws",fill=TRUE) mat=apply(out$Sigmadraw,2,quantile,probs=c(.01,.05,.5,.95,.99)) mat=rbind(as.vector(Sigma),mat); rownames(mat)[1]="Sigma"; print(mat)