Testing discontinuities in nonparametric regression
نویسندگان
چکیده
منابع مشابه
Testing symmetry in nonparametric regression models
In a recent paper Ahmad and Li (1996) proposed a new test for symmetry of the error distribution in linear regression models and proved asymptotic normality for the distribution of the corresponding test statistic under the null hypothesis and consistency under xed alternatives. The present paper has three purposes. On the one hand we derive the asymptotic distribution of the statistic consider...
متن کاملTesting strict monotonicity in nonparametric regression
A new test for strict monotonicity of the regression function is proposed which is based on a composition of an estimate of the inverse of the regression function with a common regression estimate. This composition is equal to the identity if and only if the “true” regression function is strictly monotone, and a test based on an L2-distance is investigated. The asymptotic normality of the corre...
متن کاملwww.econstor.eu Testing strict monotonicity in nonparametric regression
A new test for strict monotonicity of the regression function is proposed which is based on a composition of an estimate of the inverse of the regression function with a common regression estimate. This composition is equal to the identity if and only if the “true” regression function is strictly monotone, and a test based on an L2-distance is investigated. The asymptotic normality of the corre...
متن کاملTesting for additivity in nonparametric regression
This paper discusses a novel approach for testing for additivity in nonparametric regression. We represent the model using a linear mixedmodel framework and equivalently rewrite the original testing problem as testing for a subset of zero variance components. We propose two testing procedures: the restricted likelihood ratio test and the generalized F test. We develop the finite sample null dis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Applied Statistics
سال: 2017
ISSN: 0266-4763,1360-0532
DOI: 10.1080/02664763.2017.1280004