Kit Baum has already replied on the assumption that
you want to estimate the parameter in this transformation
by maximum likelihood, in which case his advice is in
effect change the parts of -boxcox- that do not apply
to this transformation until they do apply.
On a quite different point: I think the assumption in
your post is dubious. Given the percent flavour, you
may need a generalisation of the logit-and-folded-power
family, not a generalisation of power-and-logarithm family.
But that depends on your data generation process.
Nick
[email protected]
Rajiv Sabherwal
How can I perform Yeo-Johnson Power transformation in STATA? It is
similar to Box-Cox transformation, but can be used with negative
variables as well, unlike Box-Cox transformation which can only be
used for positive variables. Please see
www.stat.umn.edu/arc/yjpower.pdf and
rweb.stat.umn.edu/R/library/alr3/html/powtran.html.
My dependent variable is a percentage that varies from -100 to +100,
and hence Box-Cox transformation would be inappropriate, but Yeo-
Johnson Power transformation would be perfect.
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