We present a new approach to handle dependencies within the general framework of case-control designs, illustrating our approach by a particular application from the field of genetic epidemiology. The method is derived for parent-offspring trios, which will later be relaxed to more general...

We present a new approach to handle dependencies within the general framework of case-control designs, illustrating our approach by a particular application from the field of genetic epidemiology. The method is derived for parent-offspring trios, which will later be relaxed to more general...

Uniform confidence bands for densities f via nonparametric kernel estimates were first constructed by Bickel and Rosenblatt [Ann. Statist. 1, 1071.1095]. In this paper this is extended to confidence bands in the deconvolution problem g = f for an ordinary smooth error density . Under certain...

Uniform confidence bands for densities f via nonparametric kernel estimates were first constructed by Bickel and Rosenblatt [Ann. Statist. 1, 1071.1095]. In this paper this is extended to confidence bands in the deconvolution problem g = f for an ordinary smooth error density . Under certain...

We propose two test statistics for use in inverse regression problems Y = Kcedil; + , where K is a given matrix or operator which cannot be continuously inverted. Thus, only noisy, indirect observations Y for the function cedil; are available. The tests are designed for hypotheses of the form H0...

In this paper we investigate several tests for the hypothesis of a parametric form of the error distribution in the common linear and nonparametric regression model, which are based on empirical processes of residuals. It is well known that tests in this context are not asymptotically...

The aim of this paper is to show that existing estimators for the error distribution in nonparametric regression models can be improved when additional information about the distribution is included by the empirical likelihood method. The weak convergence of the resulting new estimator to a...

In the classical linear regression model the problem of testing for symmetry of the error distribution is considered. The test statistic is a functional of the difference between the two empirical distribution functions of the estimated residuals and their counterparts with opposite signs. The...

The aim of this paper is to show that existing estimators for the error distribution in nonparametric regression models can be improved when additional information about the distribution is included by the empirical likelihood method. The weak convergence of the resulting new estimator to a...