Non-Parametric Estimation of a Multivariate Probability Density

作者：V. A. Epanechnikov · 发表于：Theory of Probability and Its Applications · 年份：1969 · DOI：10.1137/1114019 · 被引用次数：1860 · 研究领域：Statistical Methods and Inference、Advanced Statistical Methods and Models、Hydrology and Drought Analysis

Previous article Next article Non-Parametric Estimation of a Multivariate Probability DensityV. A. EpanechnikovV. A. Epanechnikovhttps://doi.org/10.1137/1114019PDFBibTexSections ToolsAdd to favoritesExport CitationTrack CitationsEmail SectionsAbout[1] Emanuel Parzen, On estimation of a probability density function and mode, Ann. Math. Statist., 33 (1962), 1065–1076 MR0143282 0116.11302 CrossrefGoogle Scholar[2] Murray Rosenblatt, Remarks on some nonparametric estimates of a density function, Ann. Math. Statist., 27 (1956), 832–837 MR0079873 0073.14602 CrossrefGoogle Scholar[3] G. M. Manija, Remarks on non-parametric estimates of a two-dimensional density function, Soobšč. Akad. Nauk Gruzin. SSR, 27 (1961), 385–390 MR0143303 Google Scholar[4] E. A. Nadaraya, Estimation of a bivariate probability density, Soobshch. Akad. Nauk Gruz. SSR, 36 (1964), 267–268 Google Scholar[5] R. E. Bellman, , I. Glicksberg and , O. A. Gross, Some aspects of the mathematical theory of control processes, Rand Corporation, Santa Monica, Calif., Rep. No. R-313, 1958rm xix+244 MR0094281 0086.11703 Google Scholar Previous article Next article FiguresRelatedReferencesCited byDetails Kernel-based learning of birth process from evolving spatiotemporal RFS data stream in SMC CPHD filter for multi-target trackingSignal Processing, Vol. 203 Cross Ref Assessing spatial connectivity effects on daily streamflow forecasting using Bayesian-based graph neural networkScience of The Total Environment, Vol. 855 Cross ...