Least product relative error estimation

Kani Chen, Yuanyuan Lin, Zhanfeng Wang and Zhiliang Ying

Journal of Multivariate Analysis, 2016, vol. 144, issue C, 91-98

Abstract: A least product relative error criterion is proposed for multiplicative regression models. It is invariant under scale transformation of the outcome and covariates. In addition, the objective function is smooth and convex, resulting in a simple and uniquely defined estimator of the regression parameter. It is shown that the estimator is asymptotically normal and that the simple plug-in variance estimation is valid. Simulation results confirm that the proposed method performs well. An application to body fat calculation is presented to illustrate the new method.

Keywords: Multiplicative regression model; Product form; Relative error; Scale invariance; Variance estimation (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (13)

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DOI: 10.1016/j.jmva.2015.10.017

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