# linear.hypothesis

From car v1.0-14
by John Fox

##### Test Linear Hypothesis

Test a linear hypothesis for a linear or generalized linear model.

- Keywords
- models, regression, htest

##### Usage

```
linear.hypothesis(model, ...)
lht(...)
## S3 method for class 'lm':
linear.hypothesis(model, hypothesis.matrix, rhs=0,
summary.model=summary(model, corr = FALSE),
white.adjust=FALSE, error.SS, error.df, ...)
## S3 method for class 'glm':
linear.hypothesis(model, hypothesis.matrix, rhs=0,
summary.model=summary(model, corr = FALSE), ...)
## S3 method for class 'chisq.test':
print(x, ...)
## S3 method for class 'F.test':
print(x, ...)
```

##### Arguments

- model
- model object produced by
`lm`

or`glm`

. - hypothesis.matrix
- matrix (or vector) giving linear combinations of coefficients by rows.
- rhs
- right-hand-side vector for hypothesis, with as many entries as
rows in
`hypothesis.matrix`

. - summary.model
- a
`summary`

object for the model; usually specified only when`linear.hypothesis`

is called from another function that has already computed the summary. - white.adjust
- if
`TRUE`

use heteroscedasticity-corrected covariance matrix. - error.SS
- error sum of squares for the hypothesis; if not specified, will be
taken from
`model`

. - error.df
- error degrees of freedom for the hypothesis; if not specified,
will be taken from
`model`

. - x
`chisq.test`

or`F.test`

object.- ...
- aruments to pass down.

##### Details

Computes an F-test for the hypothesis in a linear model, or a Wald test in a generalized linear model.

##### Value

- Returns an
`F.test`

or`chisq.test`

object, with components: SSH sum of squares for hypothesis (for a linear model). SSE error sum of squares (for a linear model). f F-statistic for the hypothesis (for a linear model.) Df degrees of freedom for F or chisquare. p p-value for the hypothesis. ChiSquare chisquare statistic for the hypothesis (for a generalized linear model).

##### References

Fox, J. (1997)
*Applied Regression, Linear Models, and Related Methods.* Sage.

##### See Also

##### Examples

```
data(Davis)
mod<-lm(weight~repwt, data=Davis)
linear.hypothesis(mod, diag(2), c(0,1))
## F-Test
## SS = 245.9738 SSE = 12828.03 F = 1.735312 Df = 2 and 181 p = 0.179266
```

*Documentation reproduced from package car, version 1.0-14, License: GPL version 2 or newer*

### Community examples

Looks like there are no examples yet.