Goldfeld-Quandt Test
Goldfeld-Quandt test against heteroskedasticity.
gqtest(formula, point = 0.5, fraction = 0,
alternative = c("greater", "two.sided", "less"),
order.by = NULL, data = list())formula |
a symbolic description for the model to be tested
(or a fitted |
point |
numerical. If |
fraction |
numerical. The number of central observations to be omitted.
If |
alternative |
a character string specifying the alternative hypothesis. The default is to test for increasing variances. |
order.by |
Either a vector |
data |
an optional data frame containing the variables in the model.
By default the variables are taken from the environment which |
The Goldfeld-Quandt test compares the variances of two submodels divided by a specified breakpoint and rejects if the variances differ.
Under H_0 the test statistic of the Goldfeld-Quandt test follows an F
distribution with the degrees of freedom as given in parameter.
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. |
parameter |
degrees of freedom. |
method |
a character string indicating what type of test was performed. |
alternative |
a character string describing the alternative hypothesis. |
p.value |
the p-value of the test. |
data.name |
a character string giving the name(s) of the data. |
S.M. Goldfeld & R.E. Quandt (1965), Some Tests for Homoskedasticity. Journal of the American Statistical Association 60, 539–547
W. Krämer & H. Sonnberger (1986), The Linear Regression Model under Test. Heidelberg: Physica
## generate a regressor x <- rep(c(-1,1), 50) ## generate heteroskedastic and homoskedastic disturbances err1 <- c(rnorm(50, sd=1), rnorm(50, sd=2)) err2 <- rnorm(100) ## generate a linear relationship y1 <- 1 + x + err1 y2 <- 1 + x + err2 ## perform Goldfeld-Quandt test gqtest(y1 ~ x) gqtest(y2 ~ x)
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