Can be performed using bayesglm function of arm package:

**Code:**

> bwdf = mybwdf(F)

> library(arm)

> bayesglm(bwt~., bwdf, family=gaussian)

bayesglm(formula = bwt ~ ., family = gaussian, data = bwdf)

coef.est coef.se

(Intercept) 2926.21 312.78

age -3.52 9.62

lwt 4.35 1.74

race2 -486.55 149.71

race3 -353.95 114.60

smoke1 -351.20 106.36

ptl -48.79 101.88

ht1 -589.32 201.70

ui1 -514.47 138.67

ftv -13.94 46.46

---

n = 189, k = 10

residual deviance = 75702596.9, null deviance = 99969655.8 (difference = 24267058.9)

overdispersion parameter = 422877.8

residual sd is sqrt(overdispersion) = 650.29

References:

Andrew Gelman and Yu-Sung Su (2015). arm: Data Analysis Using Regression and Multilevel/Hierarchical Models. R package version 1.8-6. http://CRAN.R-project.org/package=arm