Box-Cox power transformation for Linear Models 1.0

Operating systemsOS : Windows / Linux / Mac OS / BSD / Solaris
Program licensingScript Licensing : Freeware
CreatedCreated : Sep 15, 2007
Size downloadDownloads : 15
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Helps choose a Box-Cox power transformation for a ...

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
Demands:
• MATLAB Release: R14SP3

Box-Cox power transformation for Linear Models 1.0 scripting tags: transformation, confidence, power, linear models, statistics probability, lambda, plot, power transformation. What is new in Box-Cox power transformation for Linear Models 1.0 software script? - Unable to find Box-Cox power transformation for Linear Models 1.0 news. What is improvements are expecting? Newly-made Box-Cox power transformation for Linear Models 1.1 will be downloaded from here. You may download directly. Please write the reviews of the Box-Cox power transformation for Linear Models. License limitations are unspecified.