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Cited by 1,710

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Estimating Optimal Transformations for Multiple Regression and Correlation

Breiman, Leo, Friedman, Jerome H.·1985·Journal of the American Statistical Association
DOI 10.1080/01621459.1985.10478157
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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 = E{[θ(Y) — Σ Ø j (Xj )]2}/var[θ(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,Øρ[θ(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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Research works printed but not linked: 35

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Cited by

Metadata

Authors
Breiman, L., & Friedman, J. H.
Venue
Journal of the American Statistical Association
Publisher
Informa UK Limited
Published
1985-09
Volume
80
Issue
391
Pages
580-598
ISSN
  • 0162-1459 (ISSN-L)
  • 1537-274X
DOI
10.1080/01621459.1985.10478157
OpenAlex
W2030748132
Cited by
1,710
References
2
FWCI
21.95
Type
journal article
Language
en
Open access
closed

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