# Box-Cox power transformation for Linear Models 1.0

OS : Windows / Linux / Mac OS / BSD / Solaris

Script Licensing : Freeware

Created : Sep 15, 2007

Downloads : 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.

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

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

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

**• MATLAB Release: R14SP3**

**Demands:****Box-Cox power transformation for Linear Models 1.0 scripting tags:**transformation, confidence, power, linear models, statistics probability, lambda, plot, power transformation.

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