Simple Bayesian linear model with non-informative priors

Description

Given a lm object, the bayesLMRef function fits a simple Bayesian linear model with reference (non-informative) priors.

Usage

1
  bayesLMRef(lm.obj, n.samples, ...)

Arguments

lm.obj

an object returned by lm.

n.samples

the number of posterior samples to collect.

...

currently no additional arguments.

Details

See page 355 in Gelman et al. (2004).

Value

An object of class bayesLMRef, which is a list with at least the following tag:

p.samples

a coda object of posterior samples for the defined parameters.

Author(s)

Sudipto Banerjee sudiptob@biostat.umn.edu,
Andrew O. Finley finleya@msu.edu

References

Gelman, A., Carlin, J.B., Stern, H.S., and Rubin, D.B. (2004). Bayesian Data Analysis. 2nd ed. Boca Raton, FL: Chapman and Hall/CRC Press.

Examples

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## 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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