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題名 Kernel density estimation for random fields (density estimation for random fields)
作者 吳柏林
Carbon, Michel ; Tran, Lanh Tat ; Wu, Berlin
日期 1997
上傳時間 24-十二月-2008 13:30:42 (UTC+8)
摘要 Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimensional lattice points space are investigated. Sufficient conditions for kernel estimators to converge uniformly are obtained. The estimators can attain the optimal rates L∞ of convergence. The results apply to a large class of spatial processes.
關聯 Statistics & Probability Letters, Volume 36, Issue 2, 1 December 1997, Pages 115-125
資料類型 article
DOI https://doi.org/10.1016/S0167-7152(97)00054-0
dc.creator (作者) 吳柏林zh_TW
dc.creator (作者) Carbon, Michel ; Tran, Lanh Tat ; Wu, Berlin-
dc.date (日期) 1997en_US
dc.date.accessioned 24-十二月-2008 13:30:42 (UTC+8)-
dc.date.available 24-十二月-2008 13:30:42 (UTC+8)-
dc.date.issued (上傳時間) 24-十二月-2008 13:30:42 (UTC+8)-
dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/18711-
dc.description.abstract (摘要) Kernel-type estimators of the multivariate density of stationary random fields indexed by multidimensional lattice points space are investigated. Sufficient conditions for kernel estimators to converge uniformly are obtained. The estimators can attain the optimal rates L∞ of convergence. The results apply to a large class of spatial processes.-
dc.format application/en_US
dc.language enen_US
dc.language en-USen_US
dc.language.iso en_US-
dc.relation (關聯) Statistics & Probability Letters, Volume 36, Issue 2, 1 December 1997, Pages 115-125en_US
dc.title (題名) Kernel density estimation for random fields (density estimation for random fields)en_US
dc.type (資料類型) articleen
dc.identifier.doi (DOI) 10.1016/S0167-7152(97)00054-0-
dc.doi.uri (DOI) https://doi.org/10.1016/S0167-7152(97)00054-0-