grangertest is a generic function for performing
a test for Granger causality.
Usage
## Default S3 method:
grangertest(x, y, order = 1, na.action = na.omit, ...)
## S3 method for class 'formula'
grangertest(formula, data = list(), ...)
Arguments
x
either a bivariate series (in which case y has
to be missing) or a univariate series of observations.
y
a univariate series of observations (if x is
univariate, too).
order
integer specifying th order of lags to include
in the auxiliary regression.
na.action
a function for eliminating NAs
after aligning the series x and y.
...
further arguments passed to waldtest.
formula
a formula specification of a bivariate series like y ~ x.
data
an optional data frame containing the variables in the
model. By default the variables are taken from the environment
which grangertest is called from.
Details
Currently, the methods for the generic function grangertest only
perform tests for Granger causality in bivariate series. The test is simply
a Wald test comparing the unrestricted model—in which y is explained
by the lags (up to order order) of y and x—and the
restricted model—in which y is only explained by the lags of y.
Both methods are simply convenience interfaces to waldtest.
Value
An object of class "anova" which contains the residual degrees of freedom,
the difference in degrees of freedom, Wald statistic and corresponding p value.
See Also
waldtest, ChickEgg
Examples
## Which came first: the chicken or the egg?
data(ChickEgg)
grangertest(egg ~ chicken, order = 3, data = ChickEgg)
grangertest(chicken ~ egg, order = 3, data = ChickEgg)
## alternative ways of specifying the same test
grangertest(ChickEgg, order = 3)
grangertest(ChickEgg[, 1], ChickEgg[, 2], order = 3)