CUSUM.test: CUSUM Test

In CPAT: Change Point Analysis Tests

Description

Performs the (univariate) CUSUM test for change in mean, as described in \insertCitehorvathricemiller19CPAT. This is effectively an interface to stat_Vn; see its documentation for more details. p-values are computed using pkolmogorov, which represents the limiting distribution of the statistic under the null hypothesis.

Usage

CUSUM.test(x, use_kernel_var = FALSE, stat_plot = FALSE,
  kernel = "ba", bandwidth = "and")

Arguments

x	Data to test for change in mean
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
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)

Value

A htest-class object containing the results of the test

References

\insertAllCited

Examples

CUSUM.test(rnorm(1000))
CUSUM.test(rnorm(1000), use_kernel_var = TRUE, kernel = "bo",
           bandwidth = "nw")

Example output

Package 'CPAT' version 0.1.0
Type citation("CPAT") for citing this R package in publications

	CUSUM Test for Change in Mean

data:  rnorm(1000)
A = 0.66551, p-value = 0.7676
sample estimates:
 t* 
750 


	CUSUM Test for Change in Mean

data:  rnorm(1000)
A = 0.65395, p-value = 0.7859
sample estimates:
 t* 
359 

CPAT documentation built on May 1, 2019, 6:51 p.m.