R: Helper function to MC3.REG

MC3.REG.logpost {BMA} | R Documentation

## Helper function to MC3.REG

### Description

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

`Y` | the vector of scaled responses.
`X` | the matrix of scaled covariates.
`model.vect` | logical vector indicating which variables are to be included in the model
`p` | number of variables in model.vect
`i` | vector of possible outliers
`K` | a hyperparameter indicating the outlier inflation factor
`nu` | regression hyperparameter. Default value is 2.58 if r2 for the full model is less than 0.9 or 0.2 if r2 for the full model is greater than 0.9.
`lambda` | regression hyperparameter. Default value is 0.28 if r2 for the full model is less than 0.9 or 0.1684 if r2 for the full model is greater than 0.9.
`phi` | regression hyperparameter. Default value is 2.85 if r2 for the full model is less than 0.9 or 9.2 if r2 for the full model is greater than 0.9.

### Value

The log-posterior distribution for the model (up to a constant).

### Note

The implementation here differs from the Splus implentation. The Splus implementation uses global variables to contain the state of the current model and the history of the Markov-Chain. This implentation passes the current state and history to the function and then returns the updated state.

### Author(s)

Jennifer Hoeting jah@AT@stat.colostate.edu with the assistance of Gary Gadbury. Translation from Splus to R by Ian Painter ian.painter@AT@gmail.com.

### 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/

### See Also

`MC3.REG`, `For.MC3.REG`, `MC3.REG.choose`

[Package BMA version 3.18.9 Index]