HR.test: Rényi-Type Test
In CPAT: Change Point Analysis Tests

Description Usage Arguments Value References Examples

Performs the (univariate) Rényi-type test for change in mean, as described in \insertCitehorvathricemiller19CPAT. This is effectively an interface to stat_Zn; see its documentation for more details. p-values are computed using pZn, which represents the limiting distribution of the test statistic under the null hypothesis, which represents the limiting distribution of the test statistic under the null hypothesis when kn represents a sequence t_T satisfying t_T \to ∞ and t_T/T \to 0 as T \to ∞. (log and sqrt should be good choices.)

1 2	HR.test(x, kn = log, use_kernel_var = FALSE, stat_plot = FALSE, kernel = "ba", bandwidth = "and")

`x`	Data to test for change in mean
`kn`	A function corresponding to the trimming parameter t_T; by default, the square root function
`use_kernel_var`	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{σ}^2_{T,t} = T^{-1}≤ft( ∑_{s = 1}^t ≤ft(X_s - \bar{X}_t\right)^2 + ∑_{s = t + 1}^{T}≤ft(X_s - \tilde{X}_{T - t}\right)^2\right), where \bar{X}_t = t^{-1}∑_{s = 1}^t X_s and \tilde{X}_{T - t} = (T - t)^{-1} ∑_{s = t + 1}^{T} X_s; if `custom_var` is not `NULL`, this argument is ignored
`stat_plot`	Whether to create a plot of the values of the statistic at all potential change points
`kernel`	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)
`bandwidth`	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)