Box-Cox power transformation for Linear Models

Helps choose a Box-Cox power transformation for a multivariate linear regression.

Assume you are looking at the residuals of [b,bint,r] = regress(y,X) and it seems a transformation is in place. Use:
boxcoxlm(y,X) to find the best lambda for a Box-Cox power transformation (y^lambda, or log(y) for lambda=0)

The function will also plot the Maximum Log-Likelihood as a function of lambda, and a 95% confidence region for the best value of lambda

More control can be obtained using:

[LambdaHat,LambdaInterval]=boxcoxlm(y,X,PlotLogLike,LambdaValues,alpha)

which allows ommiting the plot, a different region or precision, and a different alpha value for the confidence interval

Requirements:

· MATLAB Release: R14SP3