Nonparametric sequential evaluation of diagnostic biomarkers

Sequential nonparametric density estimation

Sequential Nonparametric Regression

We present algorithms for nonparametric regression in settings where the data are obtained sequentially. While traditional estimators select bandwidths that depend upon the sample size, for sequential data the effective sample size is dynamically changing. We propose a linear time algorithm that adjusts the bandwidth for each new data point, and show that the estimator achieves the optimal mini...

Nonparametric Methods in Sequential Analysis

ABSTRACf Most of the other chapters in this volume are devoted to various parametric models arising in the classical sequential analysis pertaining to statistical decision theory including sequential testing as well as {point and interval} estimation problems. Though of relatively recent origins, various nonparametric models have also been worked out for these tradi tional problems in sequentia...

Sequential design for nonparametric inference

Performance of nonparametric function estimates often depends on the choice of design points. Based on the mean integrated squared error criterion, we propose a sequential design procedure that updates model knowledge and optimal design density sequentially. The methodology is developed under a general framework covering a wide range of nonparametric inference problems, such as conditional mean...

On Nonparametric Sequential Point Estimation