BoxCoxTrans: Box-Cox and Exponential Transformations

Description Usage Arguments Details Value Author(s) References See Also Examples

Description

These classes can be used to estimate transformations and apply them to existing and future data

Usage

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BoxCoxTrans(y, ...)
expoTrans(y, ...)

## Default S3 method:
BoxCoxTrans(y, x = rep(1, length(y)), 
            fudge = 0.2, numUnique = 3, na.rm = FALSE, ...)
## Default S3 method:
expoTrans(y, na.rm  = TRUE, init = 0, 
     lim = c(-4, 4), method = "Brent",
     numUnique = 3, ...)

## S3 method for class 'BoxCoxTrans'
predict(object, newdata, ...)
## S3 method for class 'expoTrans'
predict(object, newdata, ...)

Arguments

y

a numeric vector of data to be transformed. For BoxCoxTrans, the data must be strictly positive.

x

an optional dependent variable to be used in a linear model.

fudge

a tolerance value: lambda values within +/-fudge will be coerced to 0 and within 1+/-fudge will be coerced to 1.

numUnique

how many unique values should y have to estimate the transformation?

na.rm

a logical value indicating whether NA values should be stripped from y and x before the computation proceeds.

init, lim, method

initial values, limits and optimization method for optim.

...

for BoxCoxTrans: options to pass to boxcox. plotit should not be passed through. For predict.BoxCoxTrans, additional arguments are ignored.

object

an object of class BoxCoxTrans or expoTrans.

newdata

a numeric vector of values to transform.

Details

BoxCoxTrans function is basically a wrapper for the boxcox function in the MASS library. It can be used to estimate the transformation and apply it to new data.

expoTrans estimates the exponential transformation of Manly (1976) but assumes a common mean for the data. The transformation parameter is estimated by directly maximizing the likelihood.

If any(y <= 0) or if length(unique(y)) < numUnique, lambda is not estimated and no transformation is applied.

Value

Both functions returns a list of class of either BoxCoxTrans or expoTrans with elements

lambda

estimated transformation value

fudge

value of fudge

n

number of data points used to estimate lambda

summary

the results of summary(y)

ratio

max(y)/min(y)

skewness

sample skewness statistic

BoxCoxTrans also returns:

fudge

value of fudge

The predict functions returns numeric vectors of transformed values

Author(s)

Max Kuhn

References

Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations (with discussion). Journal of the Royal Statistical Society B, 26, 211-252.

Manly, B. L. (1976) Exponential data transformations. The Statistician, 25, 37 - 42.

See Also

boxcox, preProcess, optim

Examples

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data(BloodBrain)

ratio <- exp(logBBB)
bc <- BoxCoxTrans(ratio)
bc

predict(bc, ratio[1:5])

ratio[5] <- NA
bc2 <- BoxCoxTrans(ratio, bbbDescr$tpsa, na.rm = TRUE)
bc2

manly <- expoTrans(ratio)
manly

caret documentation built on May 2, 2019, 5:47 p.m.