R: Helper function to MC3.REG

MC3.REG.choose {BMA} | R Documentation

## Helper function to MC3.REG

### Description

Helper function to MC3.REG that chooses the proposal model for a Metropolis-Hastings step.

### Usage

    MC3.REG.choose(M0.var, M0.out)

### Arguments

`M0.var` | a logical vector specifying the variables in the current model.
`M0.out` | a logical vector specifying the outliers in the current model.

### Value

A list representing the proposal model, with components

`var` | a logical vector specifying the variables in the proposal model.
`out` | a logical vector specifying the outliers in the proposal model.

### 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.logpost`

[Package BMA version 3.18.9 Index]