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A power comparison between nonparametric regression tests

Zhang, Chunming; Dette, Holger - 2003

In this paper, we consider three major types of nonparametric regression tests that are based on kernel and local polynomial smoothing techniques. Their asymptotic power comparisons are established systematically under the fixed and contiguous alternatives, and are also illustrated through...

Persistent link: https://www.econbiz.de/10010306282

A comparative study of monotone nonparametric kernel estimates

Pilz, Kay F.; Dette, Holger - 2004

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/10010296624

A simple nonparametric estimator of a monotone regression function

Dette, Holger; Neumeyer, Natalie; Pilz, Kay F. - 2003

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/10010306273

Optimal bandwidth choice for the regression discontinuity estimator

Imbens, Guido W.; Kalyanaraman, Karthik - 2009

We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity …, bandwidth choice rule. We illustrate the proposed bandwidth choice using data previously analyzed by Lee (2008), as well as in a …

Persistent link: https://www.econbiz.de/10010274346

Optimal bandwidth choice for the regression discontinuity estimator

Imbens, Guido; Kalyanaraman, Karthik - 2010

We investigate the problem of optimal choice of the smoothing parameter (bandwidth) for the regression discontinuity … optimal bandwidth. This optimal bandwidth depends on unknown functionals of the distribution of the data and we propose … specific, consistent, estimators for these functionals to obtain a fully data-driven bandwidth choice that has the asymptotic …

Persistent link: https://www.econbiz.de/10010288396

Nonparametric Analysis of Covariance : the Case of Inhomogeneous and Heteroscedastic Noise

Scholz, Achim; Neumeyer, Natalie; Munk, Axel - 2004

The purpose of this paper is to propose a procedure for testing the equality of several regression curves fi in nonparametric regression models when the noise is inhomogeneous. This extends work of Dette and Neumeyer (2001) and it is shown that the new test is asymptotically uniformly more...

Persistent link: https://www.econbiz.de/10010296611

Bootstrap tests for the error distribution in linear and nonparametric regression models

Nagel, Eva-Renate; Dette, Holger; Neumeyer, Natalie - 2004

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/10010296621

On the estimation of a monotone conditional variance in nonparametric regression

Dette, Holger; Pilz, Kay F. - 2004

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/10010296626

Specification tests indexed by bandwidths

Dette, Holger; Hetzler, Benjamin - 2004

which are based on kernel methods. In order to circumvent the problem of choosing a bandwidth for the corresponding test … asymptotically optimal bandwidth for the estimation of the regression function. We prove weak convergence of these processes to …

Persistent link: https://www.econbiz.de/10010296632

Estimating a convex function in nonparametric regression

Dette, Holger; Birke, Melanie - 2005

A new nonparametric estimate of a convex regression function is proposed and its stochastic properties are studied. The method starts with an unconstrained estimate of the derivative of the regression function, which is firstly isotonized and then integrated. We prove asymptotic normality of the...

Persistent link: https://www.econbiz.de/10010296683