| resettest {lmtest} | R Documentation |
Ramsey's RESET test for functional form.
resettest(formula, power = 2:3, type = c("fitted", "regressor",
"princomp"), data = list())
formula |
a symbolic description for the model to be tested
(or a fitted "lm" object). |
power |
integers. A vector of positive integers indicating the powers of the variables that should be included. By default, the test is for quadratic or cubic influence of the fitted response. |
type |
a string indicating whether powers of the fitted response, the regressor variables (factors are left out), or the first principal component of the regressor matrix should be included in the extended model. |
data |
an optional data frame containing the variables in the model.
By default the variables are taken from the environment which resettest
is called from. |
The RESET test is a popular diagnostic for correctness of functional
form. The basic assumption is that under the alternative the model can be
written in the form
y=X * beta + Z * gamma.
Z is generated by taking powers either of the fitted response, the
regressor variables, or the first principal component of X. A standard
F-Test is then applied to determine whether these additional variables have
significant influence. The test statistic under H_0 follows an F
distribution with parameter degrees of freedom.
This function was called reset in previous versions of the package. This
interface is currently still included, but a warning is issued. Please use
resettest instead.
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.
An object of class "htest" containing:
statistic |
the test statistic. |
p.value |
the corresponding p-value. |
parameter |
degrees of freedom. |
method |
a character string with the method used. |
data.name |
a character string with the data name. |
J.B. Ramsey (1969), Tests for Specification Error in Classical Linear Least Squares Regression Analysis. Journal of the Royal Statistical Society, Series B 31, 350–371
W. Krämer & H. Sonnberger (1986), The Linear Regression Model under Test. Heidelberg: Physica
x <- c(1:30) y1 <- 1 + x + x^2 + rnorm(30) y2 <- 1 + x + rnorm(30) resettest(y1 ~ x , power=2, type="regressor") resettest(y2 ~ x , power=2, type="regressor")