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We consider a two-stage procedure (TSP) for estimating an inverse regression function at a given point, where isotonic regression is used at stage one to obtain an initial estimate and a local linea...
In regression analysis one wants to estimate the regression function from a data. In this paper we consider the rate of convergence for the nearest neighbor estimator in case that the regression funct...
It has been recently shown that nonparametric estimators of the additive regression function could be obtained in the presence of right censoring by coupling the marginal integration method with initi...
It has been recently shown that nonparametric estimators of the additive regression function could be obtained in the presence of right censoring by coupling the marginal integration method with ini...
In this paper we study the estimation of the regression function. We establish a law ofthe iterated logarithm for the random window-width kernel estimator and, as an application, for a nearest neighbo...
Research on jump regression functions has not been adequate yet According to the information about the number of jumps, their positions and jump magnitudes, jump regression functions can be classified...
The quality parameters of electronic components and devices usually depend on the parameters of the materials. In many cases one does not know the theoretical relationship between the parameters, and ...

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