We propose several new tests for monotonicity of regression functions based on different empirical processes of residuals. The residuals are obtained from recently developed simple kernel based estimators for increasing regression functions based on increasing rearrangements of unconstrained nonparametric estimators. The test statistics are estimated distance measures between the regression function and its increasing rearrangement. We discuss the asymptotic distributions, consistency, and small sample performances of the tests. AMS Classification: 62G10, 62G08, 62G3
We suggest a method for monotonizing general kernel-type estimators, for example local linear estima...
In a recent paper Dette, Neumeyer and Pilz (2005) proposed a new nonparametric estimate of a monoto...
Two new test statistics are introduced to test the null hypotheses that the sampling distri-bution h...
This article provides a test of monotonicity of a regression function. The test is based on the size...
Monotonicity is a key qualitative prediction of a wide array of economic models derived via robust c...
Monotonicity is a key qualitative prediction of a wide array of economic models de-rived via robust ...
A new nonparametric procedure for testing monotonicity of a regression mean is proposed. The test is...
This article proposes a nonparametric test of monotonicity for conditional distributions and its mom...
This article proposes an omnibus test for monotonicity of nonparametric conditional distributions a...
In this paper a nonparametric procedure for testing for monotonicity of a regression mean with guara...
Recently, Dette, Neumeyer and Pilz (2005a) proposed a new monotone estimator for strictly increasing...
This article proposes nonparametric tests for tail monotonicity of bivariate random vectors. The tes...
Abstract. We consider the problem of hypothesis testing within a monotone regression model. We propo...
ABSTRACT. In this article, we develop a test for the null hypothesis that a real-valued function bel...
We consider the problem of hypothesis testing within a monotone regression model. We propose a new t...
We suggest a method for monotonizing general kernel-type estimators, for example local linear estima...
In a recent paper Dette, Neumeyer and Pilz (2005) proposed a new nonparametric estimate of a monoto...
Two new test statistics are introduced to test the null hypotheses that the sampling distri-bution h...
This article provides a test of monotonicity of a regression function. The test is based on the size...
Monotonicity is a key qualitative prediction of a wide array of economic models derived via robust c...
Monotonicity is a key qualitative prediction of a wide array of economic models de-rived via robust ...
A new nonparametric procedure for testing monotonicity of a regression mean is proposed. The test is...
This article proposes a nonparametric test of monotonicity for conditional distributions and its mom...
This article proposes an omnibus test for monotonicity of nonparametric conditional distributions a...
In this paper a nonparametric procedure for testing for monotonicity of a regression mean with guara...
Recently, Dette, Neumeyer and Pilz (2005a) proposed a new monotone estimator for strictly increasing...
This article proposes nonparametric tests for tail monotonicity of bivariate random vectors. The tes...
Abstract. We consider the problem of hypothesis testing within a monotone regression model. We propo...
ABSTRACT. In this article, we develop a test for the null hypothesis that a real-valued function bel...
We consider the problem of hypothesis testing within a monotone regression model. We propose a new t...
We suggest a method for monotonizing general kernel-type estimators, for example local linear estima...
In a recent paper Dette, Neumeyer and Pilz (2005) proposed a new nonparametric estimate of a monoto...
Two new test statistics are introduced to test the null hypotheses that the sampling distri-bution h...