Performs the (univariate) Darling-Erd<U+00F6>s test for change in mean, as described
in horvathricemiller19CPAT. This is effectively an interface
to stat_de; see its documentation for more details. p-values
are computed using pdarling_erdos, which represents the
limiting distribution of the test statistic under the null hypothesis when
a and b are chosen appropriately. (Change those parameters at
your own risk!)
DE.test(x, a = log, b = log, use_kernel_var = FALSE,
stat_plot = FALSE, kernel = "ba", bandwidth = "and")Data to test for change in mean
The function that will be composed with \(l(x) = (2 \log x)^{1/2}\)
The function that will be composed with \(u(x) = 2 \log x + \frac{1}{2} \log \log x - \frac{1}{2} \log \pi\)
Set to TRUE to use kernel methods for long-run
variance estimation (typically used when the data is
believed to be correlated); if FALSE, then the
long-run variance is estimated using
\(\hat{\sigma}^2_{T,t} = T^{-1}\left(
\sum_{s = 1}^t \left(X_s - \bar{X}_t\right)^2 +
\sum_{s = t + 1}^{T}\left(X_s -
\tilde{X}_{T - t}\right)^2\right)\), where
\(\bar{X}_t = t^{-1}\sum_{s = 1}^t X_s\) and
\(\tilde{X}_{T - t} = (T - t)^{-1}
\sum_{s = t + 1}^{T} X_s\)
Whether to create a plot of the values of the statistic at all potential change points
If character, the identifier of the kernel function as used in
cointReg (see getLongRunVar); if
function, the kernel function to be used for long-run variance
estimation (default is the Bartlett kernel in cointReg)
If character, the identifier for how to compute the
bandwidth as defined in cointReg (see
getBandwidth); if function, a function
to use for computing the bandwidth; if numeric, the bandwidth
value to use (the default is to use Andrews' method, as used in
cointReg)
A htest-class object containing the results of the test
# NOT RUN {
DE.test(rnorm(1000))
DE.test(rnorm(1000), use_kernel_var = TRUE, kernel = "bo", bandwidth = "nw")
# }
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