This calculates a robust average that is unaffected by outliers.

```
TukeyBiweight(x, const = 9, na.rm = FALSE,
conf.level = NA, ci.type = "bca", R=1000, ...)
```

A `numeric`

mean.

- x
a

`numeric`

vector- const
a constant.

is preassigned a value of 9 according to the Cook reference below but other values are possible.`const`- na.rm
logical, indicating whether

`NA`

values should be stripped before the computation proceeds. Defaults to FALSE.- conf.level
confidence level of the interval. If set to

`NA`

(which is the default) no confidence interval will be calculated.- ci.type
The type of confidence interval required. The value should be any subset of the values

`"basic"`

,`"stud"`

,`"perc"`

,`"bca"`

or simply`"all"`

which will compute all four types of intervals.- R
The number of bootstrap replicates. Usually this will be a single positive integer. For importance resampling, some resamples may use one set of weights and others use a different set of weights. In this case

`R`

would be a vector of integers where each component gives the number of resamples from each of the rows of weights.- ...
the dots are passed to the function

`boot`

, when confidence intervalls are calculated.

Mikko Korpela <mikko.korpela@aalto.fi>

This is a one step computation that follows the Affy whitepaper below,
see page 22.

determines the point at which
outliers are given a weight of 0 and therefore do not contribute to
the calculation of the mean. `const`

sets values roughly
+/-6 standard deviations to 0. `const` = 9

is also used in
tree-ring chronology development. Cook and Kairiukstis (1990) have
further details.`const` = 6

An exact summation algorithm (Shewchuk 1997) is used. When some assumptions about the rounding of floating point numbers and conservative compiler optimizations hold, summation error is completely avoided. Whether the assumptions hold depends on the platform, i.e. compiler and CPU.

Statistical Algorithms Description Document, 2002, Affymetrix.

Cook, E. R. and Kairiukstis, L. A. (1990) *Methods of
Dendrochronology: Applications in the Environmental Sciences*.
Springer. ISBN-13: 978-0792305866.

Mosteller, F. and Tukey, J. W. (1977) *Data Analysis and
Regression: a second course in statistics*. Addison-Wesley.
ISBN-13: 978-0201048544.

Shewchuk, J. R. (1997) Adaptive Precision Floating-Point Arithmetic
and Fast Robust Geometric Predicates. *Discrete and
Computational Geometry*, 18(3):305-363. Springer.

`HuberM`

, `Range`

, `RobScale`