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Handling the curse of dimensionality in multivariate kernel density estimation
(2013-07)
Kernel density estimation (KDE) is the most widely-used practical method for accurate nonparametric density estimation. Many works had been done on both the univariate and multivariate cases showing the efficacy, practicality ...
Methods of association for genome data with rare variants and a multinomial response
(2013-05)
Scope and Method of Study:
Nonparametric empirical likelihood density functionals estimation and applications
(2013-12)
Chapter 2 of this dissertation presents a nonparametric empirical likelihood estimation of kernel density functionals (ELKDFE), which are constructed based on a kernel density functional estimation (KDFE) and the concepts ...
Nonparametric ANOVA using kernel methods
(2013-07)
A new approach to one-way and two-way analysis of variance from the nonparametric view point is introduced and studied. It is nonparametric in the sense that no distributional format assumed and the testing pertain to ...