Open Access
November, 1988 Monotone Regression Splines in Action
J. O. Ramsay
Statist. Sci. 3(4): 425-441 (November, 1988). DOI: 10.1214/ss/1177012761

Abstract

Piecewise polynomials or splines extend the advantages of polynomials to include greater flexibility, local effects of parameter changes and the possibility of imposing useful constraints on estimated functions. Among these constraints is monotonicity, which can be an important property in many curve estimation problems. This paper shows the virtues of monotone splines through a number of statistical applications, including response variable transformation in nonlinear regression, transformation of variables in multiple regression, principal components and canonical correlation, and the use of monotone splines to model a dose-response function and to perform item analysis. Computational and inferential issues are discussed and illustrated.

Citation

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J. O. Ramsay. "Monotone Regression Splines in Action." Statist. Sci. 3 (4) 425 - 441, November, 1988. https://doi.org/10.1214/ss/1177012761

Information

Published: November, 1988
First available in Project Euclid: 19 April 2007

Digital Object Identifier: 10.1214/ss/1177012761

Keywords: Dose-response , Eckart-Young approximation , item regression function , monotone transformation , non-linear regression , regression splines , semiparametric principal components analysis

Rights: Copyright © 1988 Institute of Mathematical Statistics

Vol.3 • No. 4 • November, 1988
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