#' mfvb_lm.fit #' #' @param x The x input #' @param y The response #' @param weights weighting #' @param subset subset of data #' @param na.action handling of na #' @param offset Offset term #' @param control Control terms #' #' @return x if all checks pass mfvb_lm.fit <- function( x = stop("no 'x' argument"), y = stop("no 'y' argument"), weights = NULL, subset = NULL, na.action = na.fail, offset = NULL, control = list(), ... ) control <- do.call("mfvb.control", control) x <- check.mfvb.x(x) y <- check.mfvb.y(x, y) mfvb_lm

Source: R/mfvb_lm.R

mfvb_lm.Rd

Fit a linear regression model using mean-field variational Bayes approximation.

Usage

mfvb_lm(
  formula,
  data,
  subset,
  weights,
  na.action,
  prior = NULL,
  contrasts = NULL,
  x = FALSE,
  y = FALSE,
  ...
)

formula: an object of class [stats::formula].
data: an optional data frame, list or environment (or object coercible by as.data.frame to a data frame) containing the variables in the model. If not found in data, the variables are taken from environment(formula), typically the environment from which lm is called.
subset: subset of data
weights: weighting
na.action: handling of na
prior: a list with elements (mu0, Sigma0, a, b) giving the model prior parameters.
contrasts: design contrasts
x: return design matrix
y: return response vector
...: further arguments to `vb_lm`

An `mfvb` object