# trimse: Robust location measures and their standard errors (se). In WRS2: A Collection of Robust Statistical Methods

## Description

The following functions for estimating robust location measures and their standard errors are provided: `winmean` for the Winsorized mean, `winse` for its se, `trimse` for the trimmend mean se, `msmedse` for the median se, `mest` for the M-estimator with se in `mestse`. The functions `onestep` and `mom` compute the one-step and modified one-step (MOM) M-estimator. The Winsorized variance is implemented in `winvar`.

## Usage

 ```1 2 3 4 5 6 7 8 9``` ```winmean(x, tr = 0.2, na.rm = FALSE, ...) winvar(x, tr = 0.2, na.rm = FALSE, STAND = NULL, ...) winse(x, tr = 0.2, ...) trimse(x, tr = 0.2, na.rm = FALSE, ...) msmedse(x, sewarn = TRUE, ...) mest(x, bend = 1.28, na.rm = FALSE, ...) mestse(x, bend = 1.28, ...) onestep(x, bend = 1.28, na.rm = FALSE, MED = TRUE, ...) mom(x, bend = 2.24, na.rm = TRUE, ...) ```

## Arguments

 `x` a numeric vector containing the values whose measure is to be computed. `tr` trim lor Winsorizing level. `na.rm` a logical value indicating whether NA values should be stripped before the computation proceeds. `sewarn` a logical value indicating whether warnings for ties should be printed. `bend` bending constant for M-estimator. `MED` if `TRUE`, median is used as initial estimate. `STAND` no functionality, kept for WRS compatibility purposes. `...` currently ignored.

## Details

The standard error for the median is computed according to McKean and Shrader (1984).

## References

Wilcox, R. (2012). Introduction to Robust Estimation and Hypothesis Testing (3rd ed.). Elsevier.

McKean, J. W., & Schrader, R. M. (1984). A comparison of methods for studentizing the sample median. Communications in Statistics - Simulation and Computation, 13, 751-773.

Dana, E. (1990). Salience of the self and salience of standards: Attempts to match self to standard. Unpublished PhD thesis, Department of Psychology, University of Southern California.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```## Self-awareness data (Dana, 1990): Time persons could keep a portion of an ## apparatus in contact with a specified range. self <- c(77, 87, 88, 114, 151, 210, 219, 246, 253, 262, 296, 299, 306, 376, 428, 515, 666, 1310, 2611) mean(self, 0.1) ## .10 trimmed mean trimse(self, 0.1) ## se trimmed mean winmean(self, 0.1) ## Winsorized mean (.10 Winsorizing amount) winse(self, 0.1) ## se Winsorized mean winvar(self, 0.1) ## Winsorized variance median(self) ## median msmedse(self) ## se median mest(self) ## Huber M-estimator mestse(self) onestep(self) ## one-step M-estimator mom(self) ## modified one-step M-estimator ```

WRS2 documentation built on July 20, 2021, 9:06 a.m.