This function is used to fit linear models considering heavy-tailed errors.
heavyLm(formula, data, family = Student(df = 4), subset, na.action, control, model = TRUE, x = FALSE, y = FALSE, contrasts = NULL)
- an object of class
"formula": a symbolic description of the model to be fitted.
- an optional 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
- a description of the error distribution to be used in the model. By default the Student-t distribution with 4 degrees of freedom is considered.
- an optional expression indicating the subset of the rows of data that should be used in the fitting process.
- a function that indicates what should happen when the data contain NAs.
- a list of control values for the estimation algorithm to replace the default values returned by the function
- model, x, y
- logicals. If
TRUEthe corresponding components of the fit (the model frame, the model matrix, the response) are returned.
- an optional list. See the
Dempster, A.P., Laird, N.M., and Rubin, D.B. (1980). Iteratively reweighted least squares for linear regression when errors are Normal/Independent distributed. In P.R. Krishnaiah (Ed.), Multivariate Analysis V, p. 35-57. North-Holland.
Documentation reproduced from package heavy, version 0.2-3. License: GPL (>= 2)