lmtest (version 0.9-9)

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 (or a fitted "lm" object).

order.by

Either a vector z or a formula with a single explanatory variable like ~ z. The observations in the model are ordered by the size of z. If set to NULL (the default) the observations are assum

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)