lm.best: Title: Fitting linear models for the best model
In VariableSelection: Select Variables for Linear Models

lm.best

R Documentation

Title: Fitting linear models for the best model

Description: lm.best is used to fit linear model for the best model provided by modelselect.lm.

lm.best(object, method = "models", threshold = 0.95, x = FALSE, y = FALSE)

`object`	the model selection result from `modelselect.lm`.
`method`	the criteria to do model select. `method = "models"` selects the best model by the highest posterior probabilities. `method = "variables"` selects the variables in the best model by the posterior inclusion probabilities which are larger than the threshold.
`threshold`	The threshold for variable selection. The variables with posterior inclusion probability larger than the threshold are selected in the best model. The default is 0.95.
`x`, `y`	logicals. If `TRUE` the corresponding components (the best model predictor matrix, the response) of the fit are returned.

An object of class "lm", which is a list containing the following components:

coefficients: A named vector of coefficients.
residuals: The residuals, that is the response minus the fitted values.
fitted.values: The fitted mean values.
rank: The numeric rank of the fitted linear model.
df.residual: The residual degrees of freedom.
call: The matched call.
terms: The terms object used.
model: (If requested) the model frame used.
qr: (If requested) the QR decomposition of the design matrix.
xlevels: (If the model formula includes factors) a record of the levels of the factors.
contrasts: (If the model formula includes factors) the contrasts used.
offset: The offset used.
threshold: the threshold used for method = "variables".