| coeftest {lmtest} | R Documentation |
coeftest is a generic function for performing
z and (quasi-)t tests of estimated coefficients.
coeftest(x, vcov. = NULL, df = NULL, ...)
x |
an object (for details see below). |
vcov. |
a specification of the covariance
matrix of the estimated coefficients. This can be
specified as a matrix or as a function yielding
a matrix when applied to |
df |
the degrees of freedom to be used. If this
is a finite positive number a t test with |
... |
further arguments passed to the methods. |
The generic function coeftest currently has a default
method (which works in particular for "lm" and
"glm" objects) and a method for objects of class
"breakpointsfull"
(as computed by breakpoints.formula).
The default method assumes that a coef methods exists,
such that coef(x) yields the estimated coefficients.
To specify a covariance matrix vcov. to be used, there
are three possibilities:
1. It is pre-computed and supplied in argument vcov..
2. A function for extracting the covariance matrix from
x is supplied, e.g., vcovHC
or vcovHAC from package sandwich.
3. vcov. is set to NULL, then it is assumed that
a vcov method exists, such that vcov(x) yields
a covariance matrix. For illustrations see below.
The degrees of freedom df determine whether a normal
approximation is used or a t distribution with df degrees
of freedoms is used. The default method uses df.residual(x)
and if this is NULL a z test is performed.
An object of class "coeftest" which is essentially
a coefficient matrix with columns containing the estimates,
associated standard errors, test statistics and p values.
## load data and fit model
data(Mandible)
fm <- lm(length ~ age, data=Mandible, subset=(age <= 28))
## the following commands lead to the same tests:
summary(fm)
coeftest(fm)
## a z test (instead of a t test) can be performed by
coeftest(fm, df = Inf)
if(require(sandwich)) {
## a different covariance matrix can be also used:
## either supplied as a function
coeftest(fm, df = Inf, vcov = vcovHC)
## or as a matrix
coeftest(fm, df = Inf, vcov = vcovHC(fm, type = "HC0"))
}