Asymptotics and Optimal Bandwidth Selection for Highest Density Region Estimation1 by R. J. Samworth

نویسنده

  • R. J. SAMWORTH
چکیده

We study kernel estimation of highest-density regions (HDR). Our main contributions are two-fold. First, we derive a uniform-in-bandwidth asymptotic approximation to a risk that is appropriate for HDR estimation. This approximation is then used to derive a bandwidth selection rule for HDR estimation possessing attractive asymptotic properties. We also present the results of numerical studies that illustrate the benefits of our theory and methodology.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Determination of optimal bandwidth in upscaling process of reservoir data using kernel function bandwidth

Upscaling based on the bandwidth of the kernel function is a flexible approach to upscale the data because the cells will be coarse-based on variability. The intensity of the coarsening of cells in this method can be controlled with bandwidth. In a smooth variability region, a large number of cells will be merged, and vice versa, they will remain fine with severe variability. Bandwidth variatio...

متن کامل

Bandwidth Selection in Kernel Density Estimation: a Review

Allthough nonparametric kernel density estimation is nowadays a standard technique in explorative data{analysis, there is still a big dispute on how to assess the quality of the estimate and which choice of bandwidth is optimal. The main argument is on whether one should use the Integrated Squared Error or the Mean Integrated Squared Error to deene the optimal bandwidth. In the last years a lot...

متن کامل

On the Equivalence of Exact and Asymptotically Optimal Bandwidths for Kernel Estimation of Density Functionals

Given a density f we pose the problem of estimating the density functional ψr = ∫ f (r)f making use of kernel methods. This is a well-known problem but some of its features remained unexplored. We focus on the problem of bandwidth selection. Whereas all the previous studies concentrate on an asymptotically optimal bandwidth here we study the properties of exact, nonasymptotic ones, and relate t...

متن کامل

Optimal Coding Subgraph Selection under Survivability Constraint

Nowadays communication networks have become an essential and inevitable part of human life. Hence, there is an ever-increasing need for expanding bandwidth, decreasing delay and data transfer costs. These needs necessitate the efficient use of network facilities. Network coding is a new paradigm that allows the intermediate nodes in a network to create new packets by combining the packets recei...

متن کامل

A ug 2 00 7 Importance Tempering

Simulated tempering (ST) is an established Markov Chain Monte Carlo (MCMC) methodology for sampling from a multimodal density π(θ). The technique involves introducing an auxiliary variable k taking values in a finite subset of [0, 1] and indexing a set of tempered distributions, say π k (θ) ∝ π(θ) k. Small values of k encourage better mixing, but samples from π are only obtained when the joint ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2010