Helper function to MC3.REG that calculates the posterior model probability (up to a constant).
Usage
MC3.REG.logpost(Y, X, model.vect, p, i, K, nu, lambda, phi)
Arguments
Value
The log-posterior distribution for the model (up to a constant).
References
Bayesian Model Averaging for Linear Regression Models
Adrian E. Raftery, David Madigan, and Jennifer A. Hoeting (1997).
Journal of the American Statistical Association, 92, 179-191.
A Method for Simultaneous Variable and Transformation Selection in Linear Regression
Jennifer Hoeting, Adrian E. Raftery and David Madigan (2002).
Journal of Computational and Graphical Statistics 11 (485-507)
A Method for Simultaneous Variable Selection and Outlier Identification in Linear Regression
Jennifer Hoeting, Adrian E. Raftery and David Madigan (1996).
Computational Statistics and Data Analysis, 22, 251-270
Earlier versions of these papers are available via the World Wide Web using the url:
http://www.stat.colostate.edu/~jah/papers/