hl_test: Hodges-Lehmann Test for Change Points

In robcp: Robust Change-Point Tests

Hodges-Lehmann Test for Change Points

Description

Performs the two-sample Hodges-Lehmann change point test.

Usage

hl_test(x, b_u = "nrd0", method = "kernel", control = list(), tol = 1e-8, 
        plot = FALSE)

Arguments

x	time series (numeric or ts vector).
b_u	bandwidth for u_hat. Either a numeric value or the name of a bandwidth selection function (c.f. bw.nrd0).
method	method for estimating the long run variance.
control	a list of control parameters (cf. lrv).
tol	tolerance of the distribution function (numeric), which is used to compute p-values.
plot	should the test statistic be plotted (cf. plot.cpStat)? Boolean.

Details

The function performs the two-sample Hodges-Lehmann change point test. It tests the hypothesis pair

H_0: \mu_1 = ... = \mu_n

vs.

H_1: \exists k \in \{1, ..., n-1\}: \mu_k \neq \mu_{k+1}

where \mu_t = E(X_t) and n is the length of the time series. k is called a 'change point'.

The test statistic is computed using HodgesLehmann and asymptotically follows a Kolmogorov distribution. To derive the p-value, the function pKSdist is used.

Value

A list of the class "htest" containing the following components:

statistic	value of the test statistic (numeric).
p.value	p-value (numeric).
alternative	alternative hypothesis (character string).
method	name of the performed test (character string).
cp.location	index of the estimated change point location (integer).
data.name	name of the data (character string).

Author(s)

Sheila Görz

References

Dehling, H., Fried, R., and Wendler, M. "A robust method for shift detection in time series." Biometrika 107.3 (2020): 647-660.

See Also

HodgesLehmann, medianDiff, lrv, pKSdist

Examples

#time series with a structural break at t = 20
Z <- c(rnorm(20, 0), rnorm(20, 2))

hl_test(Z, control = list(overlapping = TRUE, b_n = 5, b_u = 0.05))

robcp documentation built on April 11, 2025, 6:18 p.m.