lmtest (version 0.9-5)

harvtest: Harvey-Collier Test

Description

Harvey-Collier test for linearity.

Usage

harvtest(formula, order.by = NULL, data = list())

Arguments

formula

a symbolic description for the model to be tested.

order.by

formula. A formula with a single explanatory variable like ~ x. The observations in the model are ordered by the size of x. If set to NULL (the default) the observations are assumed to be ordered (e.g. a

data

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

Value

• A list with class "htest" containing the following components:
• statistic
  the value of the test statistic.
• p.value
  the p-value of the test.
• parameter
  degrees of freedom.
• method
  a character string indicating what type of test was performed.
• data.name
  a character string giving the name(s) of the data.

Details

The Harvey-Collier test performs a t-test (with parameter degrees of freedom) on the recursive residuals. If the true relationship is not linear but convex or concave the mean of the recursive residuals should differ from 0 significantly.

Examples can not only be found on this page, but also on the help pages of the data sets bondyield, currencysubstitution, growthofmoney, moneydemand, unemployment, wages.

References

A. Harvey & P. Collier (1977), Testing for Functional Misspecification in Regression Analysis. Journal of Econometrics 6, 103--119

W. Kr�mer & H. Sonnberger (1986), The Linear Regression Model under Test. Heidelberg: Physica

See Also

lm

Examples

# generate a regressor and dependent variable
x <- 1:50
y1 <- 1 + x + rnorm(50)
y2 <- y1 + 0.3*x^2

## perform Harvey-Collier test
harv <- harvtest(y1 ~ x)
harv
## calculate critical value vor 0.05 level
qt(0.95, harv$parameter)
harvtest(y2 ~ x)