| harvtest {lmtest} | R Documentation |
Harvey-Collier test for linearity.
harvtest(formula, order.by = NULL, tol = 1e-7, data = list())
formula |
a symbolic describtion 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
time series). |
tol |
tolerance when solve is used: the tolerance for detecting
linear dependencies in the columns the matrices passed to
solve. |
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. |
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.
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. |
A. Harvey & P. Collier (1977), Testing for Functional Misspecification in Regression Analysis. Journal of Econometrics 6, 103–119
W. Kraemer & H. Sonnberger (1986), The Linear Regression Model under Test. Heidelberg: Physica
# 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)