coeftest
is a generic function for performing
z and (quasi-)t Wald tests of estimated coefficients.
coefci
computes the corresponding Wald confidence
intervals.
coeftest(x, vcov. = NULL, df = NULL, …)coefci(x, parm = NULL, level = 0.95, vcov. = NULL, df = NULL, …)
an object (for details see below).
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 x
.
the degrees of freedom to be used. If this
is a finite positive number a t test with df
degrees of freedom is performed. In all other cases,
a z test (using a normal approximation) is performed.
By default it tries to use x$df.residual
and performs a z test if this is NULL
.
further arguments passed to the methods
and to vcov.
in the default method.
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered.
the confidence level required.
coeftest
returns an object of class "coeftest"
which
is essentially a coefficient matrix with columns containing the
estimates, associated standard errors, test statistics and p values.
coefci
returns a matrix (or vector) with columns giving
lower and upper confidence limits for each parameter. These will
be labelled as (1-level)/2 and 1 - (1-level)/2 in percent.
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.
The generic function coefci
computes the corresponding
Wald confidence intervals.
# NOT RUN {
## load data and fit model
data("Mandible", package = "lmtest")
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)
## corresponding confidence intervales
coefci(fm)
## which in this simple case is equivalent to
confint(fm)
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 function with additional arguments
coeftest(fm, df = Inf, vcov = vcovHC, type = "HC0")
## or as a matrix
coeftest(fm, df = Inf, vcov = vcovHC(fm, type = "HC0"))
}
# }
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