R: Robust location measures and their standard errors (se).

trimse {WRS2} | R Documentation

## Robust location measures and their standard errors (se).

### 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`.

### Usage

    winmean(x, tr = 0.2, na.rm = FALSE)
    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)

### 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.

### 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 Unpublished PhD thesis, Department of Psychology, University of Southern California.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

    ## 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
    median(self)        ## median
    msmedse(self)       ## se median
    mest(self)          ## Huber M-estimator
    mestse(self)

[Package WRS2 version 0.9-2 Index]