the form of the true density, f(x) of X. We describe an estimation procedure of non-parametric regression model at a given …), where the regression function m(x) is given by m(x) = E(Yi|Xi = x) with one independent variable. In a nonparametric setting …-Watson and local linear kernel estimators of nonparametric regression with data-driven bandwidths. The sample size was optimized …

time distributions between nonadjacent states. This dissertation extends previous work inthe field by developing estimation … nonparametric method, based on reliability and survival data, are presented in detail. …

and KR21 reliability measures for each matrix. The nonparametric technique of Order Analysis was applied to two sections …

nonparametric estimate of its one-step ahead conditional density. The approach entails examination of conditional moment profiles …

This research develops nonparametric strategies for sequentially monitoring clinical trial data where detecting years …

Semi-parametric and nonparametric modeling and inference have been widely studied duringthe last two decades. In this … manuscript, we do statistical inference based on semi-parametricand nonparametric models in several different scenarios ….Firstly, we develop a semi-parametric additivity test for nonparametric multi-dimensionalmodel. The test statistic can test two or …

In the research area of crop yield density estimation and in particular in risk analysis, little emphasis has been … yields. Using historical county corn yield data for Arkansas and Louisiana and nonparametric methods, this empirical analysis …