A complex set of interactions among neighbors influences plant performance and community structure. Understanding their joint operation requires extensive information on species characteristics and individual performance. We evaluated first-year survival of 35719 tropical forest seedlings of 222 species and 15 annual cohorts relative to the density of conspecific and heterospecific neighbors an...

background : kernel smoothing method is a non-parametric or graphical method for statistical estimation. in the present study was used a kernel smoothing method for finding the death hazard rates of patients with acute myocardial infarction. methods : by employing non-parametric regression methods, the curve estimation, may have some complexity.  in this article, four indices of epanechnikov, b...

In their manuscript, Corsaro, Hunt, Kroovand Hipple, and McGarrell (2012, this issue) provide a valuable contribution to the literature regarding focused deterrence with an econometric evaluation of the High Point Drug Market Intervention (DMI). By employing a difference-in-difference Poisson panel regression framework, as well as group-based trajectory analyses, these authors examine the High ...

We develop a general framework for margin-based multicategory classification in metric spaces. The basic work-horse is a margin-regularized version of the nearest-neighbor classifier. We prove generalization bounds that match the state of the art in sample size n and significantly improve the dependence on the number of classes k. Our point of departure is a nearly Bayes-optimal finite-sample r...

We present a randomized algorithm for the approximate nearest neighbor problem in d-dimensional Euclidean space. Given N points {x(j)} in R(d), the algorithm attempts to find k nearest neighbors for each of x(j), where k is a user-specified integer parameter. The algorithm is iterative, and its running time requirements are proportional to T·N·(d·(log d) + k·(d + log k)·(log N)) + N·k(2)·(d + l...