HuberM {DescTools} | R Documentation |

## Safe (generalized) Huber M-Estimator of Location

### Description

(Generalized) Huber M-estimator of location with MAD scale, being
sensible also when the scale is zero where `huber()`

returns an error.

### Usage

```
HuberM(x, k = 1.345, mu = median(x), s = mad(x, center = mu),
na.rm = FALSE, conf.level = NA, ci.type = c("wald", "boot"), ...)
```

### Arguments

`x` |
numeric vector. |

`k` |
positive factor; the algorithm winsorizes at |

`mu` |
initial location estimator. |

`s` |
scale estimator held constant through the iterations. |

`na.rm` |
logical, indicating whether |

`conf.level` |
confidence level of the interval. If set to |

`ci.type` |
The type of confidence interval required. The value should be any subset
of the values |

`...` |
the dots are passed to the function |

### Details

The standard error is computed using the `\tau`

correction factor but no finite sample correction.

The original function is not exported, but can be accessed as `DescTools::.huberM`

.

### Value

If `conf.level`

is set to `NA`

then the result will be

`a` |
single numeric value |

and
if a `conf.level`

is provided, a named numeric vector with 3 elements:

`huberm` |
the estimate for location |

`lwr.ci` |
lower bound of the confidence interval |

`upr.ci` |
upper bound of the confidence interval |

### Author(s)

Martin Maechler, building on the MASS code mentioned.

Andri Signorell <andri@signorell.net> (confidence intervals and interface)

### References

Huber, P. J. (1981)
*Robust Statistics.*
Wiley.

### See Also

`hubers`

(and `huber`

) in package MASS;
`mad`

.

### Examples

```
HuberM(c(1:9, 1000))
mad (c(1:9, 1000))
set.seed(7)
x <- c(round(rnorm(1000), 1), round(rnorm(50, m=10, sd = 10)))
HuberM(x, conf.level=0.95)
## Not run:
# scale zero
HuberM(rep(9, 100))
mad (rep(9, 100))
# bootstrap confidence intervals
HuberM(x, conf.level=0.95, ci.type="boot")
## End(Not run)
```

*DescTools*version 0.99.55 Index]