Showing 1 - 10 of 228
In this paper a new method for monotone estimation of a regression function is proposed. The estimator is obtained by the combination of a density and a regression estimate and is appealing to users of conventional smoothing methods as kernel estimators, local polynomials, series estimators or...
Persistent link: https://www.econbiz.de/10009295180
For the common binary response model we propose a direct method for the nonparametric estimation of the effective dose level ED? (0 ? 1). The estimator is obtained by the composition of a nonparametric estimate of the quantile response curve and a classical density estimate. The new method...
Persistent link: https://www.econbiz.de/10009295201
A monotone estimate of the conditional variance function in a heteroscedastic, nonpara- metric regression model is proposed. The method is based on the application of a kernel density estimate to an unconstrained estimate of the variance function and yields an esti- mate of the inverse variance...
Persistent link: https://www.econbiz.de/10009216878
In this paper we present a detailed numerical comparison of three monotone nonparametric kernel regression estimates, which isotonize a nonparametric curve estimator. The first estimate is the classical smoothed isotone estimate of Brunk (1958). The second method has recently been proposed by...
Persistent link: https://www.econbiz.de/10009219858
We propose a new test for the comparison of two regression curves, which is based on a difference of two marked empirical processes based on residuals. The large sample behaviour of the corresponding statistic is studied to provide a full nonparametric comparison of regression curves. In...
Persistent link: https://www.econbiz.de/10010955426
Persistent link: https://www.econbiz.de/10010955455
Persistent link: https://www.econbiz.de/10010955497
In the problem of testing the equality of k regression curves from independent samples we discuss three methods using nonparametric estimation techniques of the regression function. The first test is based on a linear combination of estimators for the integrated variance function in the...
Persistent link: https://www.econbiz.de/10010955502
In the common non-parametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes that are obtained from the standardized non-parametric residuals under the null...
Persistent link: https://www.econbiz.de/10005203015
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...
Persistent link: https://www.econbiz.de/10009219820