Multiple event data are frequently encountered in medical follow-up, engineering and other applications when the multiple events are considered as the major outcomes. They may be repetitions of the ...

Nonparametric methods form an important core of statistical techniques and are typically used when data do not meet parametric assumptions. Understanding the foundation of these methods, as well as ...

Jeffrey S. Morris, Naisyin Wang, Joanne R. Lupton, Robert S. Chapkin, Nancy D. Turner, Mee Young Hong and Raymond J. Carroll An important problem in studying the etiology of colon cancer is ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...

Tyrus Berry, Assistant Professor, Mathematical Sciences, will soon begin a project developing semiparametric modeling techniques that optimally leverage the strengths of parametric and nonparametric ...