MC3.REG.logpost {BMA} | R Documentation |
Helper function to MC3.REG that calculates the posterior model probability (up to a constant).
MC3.REG.logpost(Y, X, model.vect, p, i, K, nu, lambda, phi)
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. |
The log-posterior distribution for the model (up to a constant).
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.
Jennifer Hoeting jennifer.hoeting@gmail.com with the assistance of Gary Gadbury. Translation from Splus to R by Ian Painter ian.painter@gmail.com.
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: https://www.stat.colostate.edu/~jah/papers/
MC3.REG
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