Description Usage Arguments Details References

View source: R/trans-numeric.r

The Box-Cox transformation is a flexible transformation, often used to transform data towards normality. The modulus transformation generalises Box-Cox to also work with negative values.

1 2 3 | ```
boxcox_trans(p, offset = 0)
modulus_trans(p, offset = 1)
``` |

`p` |
Transformation exponent, |

`offset` |
Constant offset. 0 for Box-Cox type 1,
otherwise any non-negative constant (Box-Cox type 2). |

The Box-Cox power transformation (type 1) requires strictly positive values and
takes the following form for `y > 0`

:

*y^(λ) = (y^λ - 1)/λ*

When `y = 0`

, the natural log transform is used.

The modulus transformation implements a generalisation of the Box-Cox
transformation that works for data with both positive and negative values.
The equation takes the following forms, when `y != 0`

:

*
y^(λ) = sign(y)*((|y|+1)^λ - 1)/λ*

and when `y = 0`

:

*
y^(λ) = sign(y) * ln(|y| + 1)*

Box, G. E., & Cox, D. R. (1964). An analysis of transformations. Journal of the Royal Statistical Society. Series B (Methodological), 211-252. https://www.jstor.org/stable/2984418

John, J. A., & Draper, N. R. (1980). An alternative family of transformations. Applied Statistics, 190-197. http://www.jstor.org/stable/2986305

scales documentation built on Aug. 10, 2018, 1:17 a.m.

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