منابع مشابه
Uniform-in-Bandwidth Nearest-Neighbor Density Estimation
We are concerned with the nonparametric estimation of the density f(·) of a random variable [rv] X ∈ R by the nearest-neighbor [NN] method. The NN estimators are motivated as follows (see, e.g., Fix and Hodges [17]). Let X1,X2, . . . be independent and identically distributed [iid] random copies of X, with distribution function [df] F(x) := P(X ≤ x), for x ∈ R. Denote the empirical df based upo...
متن کاملNavigation in non-uniform density social networks
Recent empirical investigations suggest a universal scaling law for the spatial structure of social networks. It is found that the probability density distribution of an individual to have a friend at distance d scales as P(d) ∝ d−1. According to this spatial property, a scale invariant friendship (SIF) network model is introduced to deal with the navigation problem with non-uniform population ...
متن کاملDensity estimation in the uniform deconvolution model
We consider the problem of estimating a probability density function based on data that are corrupted by noise from a uniform distribution. The (nonparametric) maximum likelihood estimator for the corresponding distribution function is well defined. For the density function this is not the case. We study two nonparametric estimators for this density. The first is a type of kernel density estima...
متن کاملArea fill synthesis for uniform layout density
Chemical-mechanical polishing (CMP) and other manufacturing steps in very deep submicron VLSI have varying effects on device and interconnect features, depending on local characteristics of the layout. To improve manufacturability and performance predictability, we seek to make a layout uniform with respect to prescribed density criteria, by inserting “area fill” geometries into the layout. In ...
متن کاملUniform Convergence Rates for Kernel Density Estimation
Kernel density estimation (KDE) is a popular nonparametric density estimation method. We (1) derive finite-sample high-probability density estimation bounds for multivariate KDE under mild density assumptions which hold uniformly in x ∈ R and bandwidth matrices. We apply these results to (2) mode, (3) density level set, and (4) class probability estimation and attain optimal rates up to logarit...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Proceedings of the American Mathematical Society
سال: 1964
ISSN: 0002-9939
DOI: 10.2307/2034610