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boxcox_trans functions not always valid #103

BenOnEarth opened this issue Oct 7, 2017 · 2 comments

boxcox_trans functions not always valid #103

BenOnEarth opened this issue Oct 7, 2017 · 2 comments


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@BenOnEarth BenOnEarth commented Oct 7, 2017

In boxcox_trans, trans and inv functions include sign() and abs() (maybe for preserving order of values when 0<x<1 ?), but this then passes not totally correct functions to the transformer.

 trans <- function(x) (x^p - 1)/p * sign(x - 1)
inv <- function(x) (abs(x) * p + 1 * sign(x))^(1/p)

Using this form, for data 0 < x < 1, inv(trans(x)) != x

Eliminating those and using the basic formula for Box-Cox Power transformations:

trans <- function(x) (x^p - 1)/p
inv <- function(x) (x * p + 1)^(1/p)

I've confirmed this works for all of my data x>0, and that inv(trans(x)) == x. I've also used this to scale my axes successfully.
I'm new to git, so I'm just reporting this here.

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@statist7 statist7 commented May 17, 2018

trans and inv are wrong - they should be:

trans <- function(x) (x^p - 1)/p * sign(p)
inv <- function(x) (x * p * sign(p) + 1)^(1/p)

With these changes, for all x >= 0, inv(trans(x)) == x.

dpseidel added a commit to dpseidel/scales that referenced this issue Jun 27, 2018
implements Modulus generalization, Closes r-lib#103
@dpseidel dpseidel added wip and removed reprex labels Jun 27, 2018
dpseidel pushed a commit that referenced this issue Jun 29, 2018
Dana Paige Seidel
implements Modulus generalization, Closes #103
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@statist7 statist7 commented Jun 29, 2018

The Box-Cox and modulus transformations are distinct, yet this treats mt as generalising Box-Cox.

Box-Cox uses x^p while mt uses sign(x) * (abs(x) + 1)^p, which for positive x is (x + 1)^p.

So a proper solution should provide Box-Cox and mt as two distinct functions.

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