## Not run:
# set.seed(1)
#
# n <- 100
# X <- as.matrix(cbind(1, rnorm(n)))
# B <- as.matrix(c(1,5))
# tau.sq <- 0.1
# y <- rnorm(n, X%*%B, sqrt(tau.sq))
#
# lm.obj <- lm(y ~ X-1)
#
# summary(lm.obj)
#
# ##Now with bayesLMRef
# n.samples <- 500
#
# m.1 <- bayesLMRef(lm.obj, n.samples)
#
# summary(m.1$p.beta.tauSq.samples)
# ## End(Not run)
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