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Efficient estimation in the semiparametric normal regression-copula model with a focus on QTL mapping

Bojan Basrak and Chris A. J. Klaassen

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Abstract

The semiparametric normal copula model is studied with a correlation matrix that depends on a covariate. The bivariate version of this regression-copula model has been proposed for statistical analysis of Quantitative Trait Loci (QTL) via twin data. Appropriate linear combinations of Van der Waerden’s normal scores rank correlation coefficients yield $\sqrt{n}$-consistent estimators of the coefficients in the correlation function, i.e. of the regression parameters. They are used to construct semiparametrically efficient estimators of the regression parameters.

Chapter information

Source
Banerjee, M., Bunea, F., Huang, J., Koltchinskii, V., and Maathuis, M. H., eds., From Probability to Statistics and Back: High-Dimensional Models and Processes -- A Festschrift in Honor of Jon A. Wellner, (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2013) , 20-32

Dates
First available in Project Euclid: 8 March 2013

Permanent link to this document
https://projecteuclid.org/euclid.imsc/1362751177

Digital Object Identifier
doi:10.1214/12-IMSCOLL903

Mathematical Reviews number (MathSciNet)
MR3186746

Zentralblatt MATH identifier
1327.62192

Subjects
Primary: 62G05: Estimation 62G20: Asymptotic properties
Secondary: 62P10: Applications to biology and medical sciences

Keywords
Semiparametric inference Van der Waerden $\sqrt{n}$-consistency linkage analysis QTL mapping

Rights
Copyright © 2010, Institute of Mathematical Statistics

Citation

Basrak, Bojan; Klaassen, Chris A. J. Efficient estimation in the semiparametric normal regression-copula model with a focus on QTL mapping. From Probability to Statistics and Back: High-Dimensional Models and Processes -- A Festschrift in Honor of Jon A. Wellner, 20--32, Institute of Mathematical Statistics, Beachwood, Ohio, USA, 2013. doi:10.1214/12-IMSCOLL903. https://projecteuclid.org/euclid.imsc/1362751177


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References

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