# coeftest

##### Inference for Estimated Coefficients

`coeftest`

is a generic function for performing
z and (quasi-)t Wald tests of estimated coefficients.
`coefci`

computes the corresponding Wald confidence
intervals.

- Keywords
- htest

##### Usage

`coeftest(x, vcov. = NULL, df = NULL, …)`coefci(x, parm = NULL, level = 0.95, vcov. = NULL, df = NULL, …)

##### Arguments

- 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
`x`

. - df
- 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. - parm
- 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.
- level
- the confidence level required.

##### Details

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.

##### Value

`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.

##### See Also

##### Examples

`library(lmtest)`

```
## 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"))
}
```

*Documentation reproduced from package lmtest, version 0.9-35, License: GPL-2 | GPL-3*