Box-Cox and Exponential Transformations
These classes can be used to estimate transformations and apply them to existing and future data
BoxCoxTrans(y, ...) ## Default S3 method: BoxCoxTrans( y, x = rep(1, length(y)), fudge = 0.2, numUnique = 3, na.rm = FALSE, ... ) ## S3 method for class 'BoxCoxTrans' print(x, newdata, digits = 3, ...) ## S3 method for class 'BoxCoxTrans' predict(object, newdata, ...)
y |
a numeric vector of data to be transformed. For |
... |
for |
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 |
na.rm |
a logical value indicating whether |
newdata |
a numeric vector of values to transform. |
digits |
minimal number of significant digits. |
object |
an object of class |
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.
Both functions returns a list of class of either BoxCoxTrans or expoTrans with
elements
lambda |
estimated transformation value |
fudge |
value of |
n |
number of data points used to estimate lambda |
summary |
the results of |
ratio |
|
skewness |
sample skewness statistic |
BoxCoxTrans also returns:
fudge |
value of |
The predict functions returns numeric vectors of transformed values
Max Author
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.
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
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