Box-Cox power transformation for Linear Models 1.0

Date Added: April 01, 2013 | Visits: 471

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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 lambdaMore 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: No special requirements

Platforms: Matlab

Keyword: Confidence, Control, Function, Loglikelihood, Maximum, Obtained, Precision, Region

Users rating: 0/10

License: Shareware

Size: 10 KB

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