Description Usage Arguments Value
Implements the p-variate selection strategy
1 2 3 |
mydata |
A data matrix with observations as rows |
iter |
The number of random orderingsdev for the SUGS algorithm |
p |
The number of variables to select |
numSelect |
The number of times to randomly select variables |
Model |
Character String indicating whether PML, ML or (both) should be computed. Model selection is performed using PML if PML or both is selected, else model selection is performed using ML. |
mu_0 |
The mean hyperparameter, default is the column means of the data matrix. |
lambda_0 |
The variance of the Guassian mean prior, the dafault value is |
nu_0 |
The degrees of freedom hyperparameter, the default value is |
S_0 |
The scale hyperparamter, the deault value is a tenth of the column variance of the data matrix. |
betaHat |
A grid of hyperparameters for the dirichlet concentration parameter, the default is |
a |
The scale of the gamma prior for the dirichlet concentration parameter, the dafault value is |
b |
The rate of the gamma prior for the dirichlet concentration parameter, the default value is |
w |
The prior probability of a variable belong to the irrelevant or relevant partition. The vector must
contain two entries the first entry being the probabiliy of being irreleavnt and the second being the probability of being relevant
The default value is |
BPPARAM |
Support for parallel processing using the
|
A matrix where each row is a binary vector indicating whether that variables belongs to the relevant (1) or irrelevant (0) partition.
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