It has been expected that space information networks (SINs), as an extension of terrestrial networks, would provide highspeed, high-capacity, global continuous communication, and data transmission services anywhere for anyone at any time. With the rapid advances in relevant technologies (e.g., satellite miniaturization technology, reusable rocket launch semiconductor technology), low-orbit sate...

This is a major contribution to the expanding field of the history of alternative medicine in Germany. Martin Dinges, historian and archivist of the Homeopathy Archives of the Robert Bosch Institute for the History of Medicine, demands a new approach towards the history of homeopathy in order to overcome the traditional interest, which concentrated mainly on Samuel Hahnemann and the effect of c...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

A new nonparametric test for two sample problem based on order statistics is suggested. This test can be successful in the case of small samples. The probabilities of the statistic are given. Comparisons with KolmogorovSmirnov, Mann Whitney-Wilcoxon, and Wilks’ empty block test for small sample sizes are made by the simulation.

In various statistical model, such as density estimation and estimation of regression curves or hazard rates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametric statistics is to estimate a monotone density function f on a compact interval. A known estimator for density function of f under the restriction that f is decreasing, is Grenander estimator, ...