# Draws values of beta and sigma by Bayesian linear regression

Source:`R/mice.impute.norm.R`

`norm.draw.Rd`

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.

## Arguments

- y
Incomplete data vector of length

`n`

- ry
Vector of missing data pattern (

`FALSE`

=missing,`TRUE`

=observed)- x
Matrix (

`n`

x`p`

) of complete covariates.- rank.adjust
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.