A fast algorithm for computing least-squares cross-validations for nonparametric conditional kernel density functions-Reference-Cited by-同舟云学术

A fast algorithm for computing least-squares cross-validations for nonparametric conditional kernel density functions

Published:2010-12 Issue:12 Volume:54 Page:3404-3410
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Ichimura Tsuyoshi,Fukuda Daisuke

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference20 articles.

1. Bandwidth selection for kernel conditional density estimation;Bashtannyk;Computational Statistics and Data Analysis,2001

2. Efficient kernel density estimation using the fast gauss transform with applications to color modeling and tracking;Elgammal;IEEE Transactions on Pattern Analysis and Machine Intelligence,2003

3. A crossvalidation method for estimating conditional densities;Fan;Biometrika,2004

4. Fosgerau, M., Hjorth, K., Brems, C., Fukuda, D., 2008. Travel time variability: Definition and valuation. Tech. Rep., DTU Transport, Technical University of Denmark

5. Gray, A., Moore, A., 2003. Very fast multivariate kernel density estimation via computational geometry. In: Joint Stat. Meeting

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Research on feature extraction algorithm of rolling bearing fatigue evolution stage based on acoustic emission;Mechanical Systems and Signal Processing;2018-12

2. An evolutionary modeling approach for designing a contractual REDD+ payment scheme;Ecological Indicators;2017-08

3. Converting high-dimensional regression to high-dimensional conditional density estimation;Electronic Journal of Statistics;2017-01-01

4. Valuing travel time variability: Characteristics of the travel time distribution on an urban road;Transportation Research Part C: Emerging Technologies;2012-10

5. 3rd Special issue on matrix computations and statistics;Computational Statistics & Data Analysis;2010-12