reg: lm

In gragusa/grpack: Utility functions for econometric applications

lm

Description

reg is used to fit linear models. It can be used to carry out regression, single stratum analysis of variance and analysis of covariance (although aov may provide a more convenient interface for these). It extends lm by allowing cluster standard error and by defining a summary method which uses by default heteroskedastic robust standard errors.

Usage

  reg(formula, data, subset, weights, na.action,
    method = "qr", model = TRUE, x = FALSE, y = FALSE,
    qr = TRUE, singular.ok = TRUE, contrasts = NULL,
    offset, cluster, ...)

Arguments

formula	an object of class formula (or one that can be coerced to that class): a symbolic description of the model to be fitted. See lm for details.
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	an optional vector specifying a subset of observations to be used in the fitting process.
weights	an optional vector of weights to be used in the fitting process. Should be NULL or a numeric vector. If non-NULL, weighted least squares is used with weights weights (that is, minimizing sum(w*e^2)); otherwise ordinary least squares is used. See lm for "details".
na.action	a function which indicates what should happen when the data contain NAs. The default is set by the na.action setting of options, and is na.fail if that is unset. The "factory-fresh" default is na.omit. Another possible value is NULL, no action. Value na.exclude can be useful.
method	the method to be used; for fitting, currently only method = "qr" is supported; method = "model.frame" returns the model frame (the same as with model = TRUE, see below).
model,	y, x, qr logical. logicals. If ‘TRUE’ the corresponding components of the fit (the model frame, the model matrix, the response, the QR decomposition) are returned.
singular.ok	logical. If FALSE (the default in S but not in R) a singular fit is an error.
contrasts	an optional list. See the contrasts.arg of model.matrix.default.
offset	this can be used to specify an a priori known component to be included in the linear predictor during fitting. This should be NULL or a numeric vector of length equal to the number of cases. One or more offset terms can be included in the formula instead or as well, and if more than one are specified their sum is used. See model.offset
cluster	a factor specifying at which level clustering of standard error should take place.
...	additional arguments to be passed to the low level regression fitting functions (see lm).

Details

Details are similar to lm.

The only difference is that the factor at which level standard errors are clustered must be specified.

Value

A list similar to the one returned by lm.

Author(s)

Giuseppe Ragusa

gragusa/grpack documentation built on July 6, 2023, 12:07 a.m.