HL: Hodges-Lehmann estimate

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/rQCC-Rprogram.R

Description

Calculates the Hodges-Lehmann estimate.

Usage

1
HL(x, method = c("HL1", "HL2", "HL3"), na.rm = FALSE)

Arguments

x

a numeric vector of observations.

method

a character string specifying the estimator, must be one of "HL1" (default), "HL2" and "HL3".

na.rm

a logical value indicating whether NA values should be stripped before the computation proceeds.

Details

HL computes the Hodges-Lehmann estimates (one of "HL1", "HL2", "HL3").

The Hodges-Lehmann (HL1) is defined as

HL1 = median of (Xi+Xj)/2 over i<j

where i, j=1,2,...,n.

The Hodges-Lehmann (HL2) is defined as

HL2 = median of (Xi+Xj)/2 over i ≤ j.

The Hodges-Lehmann (HL3) is defined as

HL3 = median of (Xi+Xj)/2 over all (i,j).

Value

It returns a numeric value.

Author(s)

Chanseok Park and Min Wang

References

Park, C., H. Kim, and M. Wang (2020). Investigation of finite-sample properties of robust location and scale estimators. Communications in Statistics - Simulation and Computation, To appear.
https://doi.org/10.1080/03610918.2019.1699114

Hodges, J. L. and E. L. Lehmann (1963). Estimates of location based on rank tests. Annals of Mathematical Statistics, 34, 598–611.

See Also

mean{base} for calculating sample mean and median{stats} for calculating sample median.

finite.breakdown{rQCC} for calculating the finite-sample breakdown point.

Examples

1
2
x = c(0:10, 50)
HL(x, method="HL2")

rQCC documentation built on March 26, 2020, 7:53 p.m.