Curve Estimation
Abstract
This chapter deals with the problems of estimating a density function, a regression function, and a survival function and the corresponding hazard function when the observations are subject to censoring. Kernel and Nearest-Neighbor estimates of density and regression functions are constructed, and their convergence properties are proved, using only some smoothness conditions. Bandwidth choice for these estimators by cross-validation is discussed. The method of local polynomial for density and regression function is also introduced. For estimating the survival function from data subject to random right-censoring, the Product-Limit Estimator due to Kaplan-Meier is derived, from which as estimator of the integrated ...
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