Draws values of beta and sigma by Bayesian linear regressionSource:
This function draws random values of beta and sigma under the Bayesian linear regression model as described in Rubin (1987, p. 167). This function can be called by user-specified imputation functions.
Incomplete data vector of length
Vector of missing data pattern (
p) of complete covariates.
Argument that specifies whether
NA's in the coefficients need to be set to zero. Only relevant when
ls.meth = "qr"AND the predictor matrix is rank-deficient.
Other named arguments.
list containing components
coef (least squares estimate),
beta (drawn regression weights) and
sigma (drawn value of the
residual standard deviation).