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Last data update: 2014.03.03

R: Least absolute deviations regression

lad	R Documentation

Least absolute deviations regression

Description

This function is used to fit linear models considering Laplace errors.

Usage

lad(formula, data, method = c("BR", "EM"), subset, na.action,
  control, model = TRUE, x = FALSE, y = FALSE, contrasts = NULL)

Arguments

`formula`	an object of class `"formula"`: a symbolic description of the model to be fitted.
`data`	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 `lad` is called.
`method`	character string specifying the algorithm to use. The default algorithm is the Barrodale and Roberts algorithm `method = "BR"`. Other possible value is `method = "EM"` for an EM algorithm using IRLS.
`subset`	an optional expression indicating the subset of the rows of data that should be used in the fit.
`na.action`	a function that indicates what should happen when the data contain NAs.
`control`	a list of control values for the estimation algorithm to replace the default values returned by the function `l1pack.control`.
`model, x, y`	logicals. If `TRUE` the corresponding components of the fit (the model frame, the model matrix, the response) are returned.
`contrasts`	an optional list. See the `contrasts.arg` of `model.matrix.default`.

Value

an object of class lad representing the linear model fit. Generic function print, show the results of the fit.

Author(s)

The design was inspired by the R function lm.

References

Barrodale, I., and Roberts, F.D.K. (1974). Solution of an overdetermined system of equations in the L1 norm. Communications of the ACM 17, 319-320.

Phillips, R.F. (2002). Least absolute deviations estimation via the EM algorithm. Statistics and Computing 12, 281-285.

Examples

lad(stack.loss ~ ., data = stackloss, method = "EM")

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(L1pack)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/L1pack/lad.Rd_%03d_medium.png", width=480, height=480)
> ### Name: lad
> ### Title: Least absolute deviations regression
> ### Aliases: lad
> ### Keywords: regression
> 
> ### ** Examples
> 
> lad(stack.loss ~ ., data = stackloss, method = "EM")
Call:
lad(formula = stack.loss ~ ., data = stackloss, method = "EM")
Converged in 105 iterations

Coefficients:
 (Intercept)    Air.Flow  Water.Temp  Acid.Conc. 
   -39.6899      0.8319      0.5739     -0.0609 

Degrees of freedom: 21 total; 17 residual
Scale estimate: 2.833893 
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>