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September 1, 1985Journal of the American Statistical Association1,601 citations

Estimating Optimal Transformations for Multiple Regression and Correlation

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LBLeo BreimanJFJerome H. Friedman

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Abstract

Abstract In regression analysis the response variable Y and the predictor variables X 1 …, Xp are often replaced by functions θ (Y) and Ø1 (X 1), …, Ø p (Xp). We discuss a procedure for estimating those functions θ and Ø1, …, Ø p that minimize e 2 = Eθ (Y) — Σ Ø j (Xj) 2/varθ (Y), given only a sample (yk, xk1, …, xkp), 1 ⩽ k ⩽ N and making minimal assumptions concerning the data distribution or the form of the solution functions. For the bivariate case, p = 1, θ and Ø satisfy ρ = p (θ, Ø) = maxθ, Øρθ (Y), Ø (X), where ρ is the product moment correlation coefficient and ρ is the maximal correlation between X and Y. Our procedure thus also provides a method for estimating the maximal correlation between two variables.

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Cite This Study

Breiman et al. (1985) studied this question.

synapsesocial.com/papers/6a088a8b280cd4e998e8c7f6https://doi.org/10.1080/01621459.1985.10478157
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