```
ncv.test(model, ...)
## S3 method for class 'lm':
ncv.test(model, var.formula, data=NULL, subset, na.action, ...)
## S3 method for class 'glm':
ncv.test(model, ...)
```

model

a weighted or unweighted linear model, produced by

`lm`

.var.formula

a one-sided formula for the error variance; if omitted,
the error variance depends on the fitted values.

data

an optional data frame containing the variables in the model.
By default the variables are taken from the environment from which

`ncv.test`

is called.subset

an optional vector specifying a subset of observations to be used.

na.action

a function that indicates what should happen when the data contain

`NA`

s.
The default is set by the `na.action`

setting of `options`

....

arguments passed down to methods functions.

- The function returns a
`chisq.test`

object, which is usually just printed.

`ncv.test.glm`

is a dummy function to generate an error when a `glm`

model is used.`hccm`

, `spread.level.plot`

ncv.test(lm(interlocks~assets+sector+nation, data=Ornstein)) ## Non-constant Variance Score Test ## Variance formula: ~ fitted.values ## Chisquare = 46.98537 Df = 1 p = 7.151835e-12 ncv.test(lm(interlocks~assets+sector+nation, data=Ornstein), ~ assets+sector+nation, data=Ornstein) ## Non-constant Variance Score Test ## Variance formula: ~ assets + sector + nation ## Chisquare = 74.73535 Df = 13 p = 1.066320e-10

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