gq.test: Goldfeld-Quandt Test

In desk: Didactic Econometrics Starter Kit

Goldfeld-Quandt Test

Description

Goldfeld-Quandt test for heteroskedastic errors. The object of test results returned by this command can be plotted using the plot() function.

Usage

gq.test(
  mod,
  data = list(),
  split = 0.5,
  omit.obs = 0,
  ah = c("increasing", "unequal", "decreasing"),
  order.by = NULL,
  sig.level = 0.05,
  details = FALSE,
  hyp = TRUE
)

Arguments

mod	estimated linear model object or formula. If only a model formula is passed then the data argument must be specified.
data	if mod is a formula then the corresponding data frame has to be specified.
split	partitions the data set into two groups. If <= 1 then split is a percentage value such that T*split observations are in the first partition. If split >= 1 it is interpreted as the index of the partitioning observation, i.e. the number of observations in the first group.
omit.obs	the number of central observations to be omitted. Might increase the power of the test. If <= 1 then split is the percentage value of all observations, otherwise it is interpreted as absolute number.
ah	character string specifying the type of the alternative hypothesis: "increasing" (variance increases from group 1 to group 2), "decreasing" (variance decreases from group 1 to group 2), "unequal" (variances are unequal between the groups). The default is to test for increasing variances.
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 assumed to be ordered.
sig.level	significance level. Default value: sig.level = 0.05.
details	logical value indicating whether specific details about the test should be returned.
hyp	logical value indicating whether the Hypotheses should be returned.

Value

A list object including:

hyp	character matrix of hypotheses (if hyp = TRUE).
results	a data frame of basic test results.
hreg1	matrix of regression results in Group I.
stats1	additional statistic of regression in Group I.
hreg2	matrix of regression results in Group II.
stats2	additional statistic of regression in Group II.
nulldist	type of the Null distribution with its parameters.

References

Goldfeld, S.M. & Quandt, R.E. (1965): Some Tests for Homoskedasticity. Journal of the American Statistical Association 60, 539-547.

See Also

wh.test, gqtest.

Examples

## 5 observations in group 1 with the hypothesis that the variance of group 2 is larger
gq.test(rent ~ dist, split = 5, ah = "increasing", data = data.rent)

## Ordered by population size
eu.mod <- ols(expend ~ pop + gdp + farm + votes + mship, data = data.eu)
results <- gq.test(eu.mod, split = 13, order.by = data.eu$pop, details = TRUE)
results

plot(results)

desk documentation built on May 29, 2024, 6:05 a.m.