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This paper proposes a nonparametric test of the non-convexity of a smooth regression function based on least squares or hybrid splines. By a simple formulation of the convexity hypothesis in the class of all polynomial cubic splines, we build a test which has an asymptotic size equal to the...
Persistent link: https://www.econbiz.de/10009578020
A procedure for testing equality across nonparametric regressions is proposed. The procedure allows for any dimension of the explanatory variables and for any number of subsamples. We consider the case of random explanatory variables and allow the designs of the regressors and the number of...
Persistent link: https://www.econbiz.de/10009578576
We consider the partially linear model relating a response Y to predictors (X,T) with mean function XT β + g(T) when the T's are measured with additive error. We derive an estimator of β by modification local-likelihood method. The resulting estimator of β is shown to be asymptotically...
Persistent link: https://www.econbiz.de/10009657894
Persistent link: https://www.econbiz.de/10009659060
We develop inference tools in a semiparametric regression model with missing response data. A semiparametric regression imputation estimator and an empirical likelihood based one for the mean of the response variable are defined. Both the estimators are proved to be asymptotically normal, with...
Persistent link: https://www.econbiz.de/10009620774
Couples from Western countries tend to delay their pregnancies, which may affect their ability to obtain a live birth. We assessed the association between male age and the risk of spontaneous abortion taking into account woman's age. We performed telephone interviews on a ross-sectional random...
Persistent link: https://www.econbiz.de/10009621414
Persistent link: https://www.econbiz.de/10009624851
In this work, we introduce a smoothed influence function that constitute a theoretical tool for studying the outliers robustness properties of a large class of nonparametric estimators. With this tool, we first show the nonrobustness of the Nadaraya-Watson estimator of regression. Then we show...
Persistent link: https://www.econbiz.de/10009626684
Additive modelling has been widely used in nonparametric regression to circumvent the "curse of dimensionality", by reducing the problem of estimating a multivariate regression function to the estimation of its univariate components. Estimation of these univariate functions, however, can suffer...
Persistent link: https://www.econbiz.de/10009626746
Additive modelling is known to be useful for multivariate nonparametric regression as it reduces the complexity of problem to the level of univariate regression. This usefulness could be compromised if the data set was contaminated by outliers whose detection and removal are particularly...
Persistent link: https://www.econbiz.de/10009627283