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

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.