標(biāo)題: Titlebook: Nonparametric Kernel Density Estimation and Its Computational Aspects; Artur Gramacki Book 2018 Springer International Publishing AG 2018 [打印本頁(yè)] 作者: infection 時(shí)間: 2025-3-21 19:27
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects影響因子(影響力)
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects影響因子(影響力)學(xué)科排名
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects網(wǎng)絡(luò)公開(kāi)度
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects被引頻次
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects被引頻次學(xué)科排名
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects年度引用
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects年度引用學(xué)科排名
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects讀者反饋
書(shū)目名稱(chēng)Nonparametric Kernel Density Estimation and Its Computational Aspects讀者反饋學(xué)科排名
作者: 紅潤(rùn) 時(shí)間: 2025-3-21 22:19 作者: 散布 時(shí)間: 2025-3-22 02:52 作者: 天然熱噴泉 時(shí)間: 2025-3-22 08:09 作者: 感情脆弱 時(shí)間: 2025-3-22 08:47
Artur GramackiContains both background information and much more sophisticated material on kernel density estimation (KDE), its computational aspects, and its applications.Describes in detail computational-like pro作者: exacerbate 時(shí)間: 2025-3-22 16:43 作者: Inelasticity 時(shí)間: 2025-3-22 20:27
Nonparametric Kernel Density Estimation and Its Computational Aspects作者: PALMY 時(shí)間: 2025-3-23 00:55 作者: 填滿(mǎn) 時(shí)間: 2025-3-23 01:25 作者: regale 時(shí)間: 2025-3-23 07:39
FFT-Based Algorithms for Kernel Density Estimation and Bandwidth Selection, discuss the use of this method for plug-in and . bandwidth selectors. The final part is devoted to an overview of extended computer simulations confirming high performance and accuracy levels of the FFT-based method for KDE and bandwidth selection.作者: LAITY 時(shí)間: 2025-3-23 13:33
Introduction, capture only the important patterns, while filtering noise and ignoring the data structures that are deemed not relevant. The functions commonly referred to as filters can serve as examples of typical smoothers. In our treatment of the topic, we focus on one of the most well-known nonparametric smo作者: 無(wú)底 時(shí)間: 2025-3-23 15:12
Nonparametric Density Estimation,. technique is briefly presented together with a description of its main drawbacks. To avoid the highlighted problems, at least to some extent, one might use a smart histogram modification known in the literature as an . (ASH). A simple example presented in this chapter shows its advantages over the作者: paradigm 時(shí)間: 2025-3-23 19:45
Kernel Density Estimation,r .. First, the most popular kernel types are presented together with a number of basic definitions both for uni- and multivariate cases and then a review of performance criteria is provided, starting with the univariate case and then extended to the general multivariate case. The subsequent part of作者: Lineage 時(shí)間: 2025-3-24 01:17
Bandwidth Selectors for Kernel Density Estimation, and moves on to an overview of the three major types of selectors (that is: . (ROT), . (CV) and . (PI) selectors). The next part of the chapter is devoted to describing these selectors in more detail, both for the uni- and multivariate cases. Finally, a few numerical examples are given. The chapter作者: 誤傳 時(shí)間: 2025-3-24 03:22 作者: 浮雕寶石 時(shí)間: 2025-3-24 10:30
,FPGA-Based Implementation of?a?Bandwidth Selection Algorithm,ithm. In contrast to the results presented in Chapter 5, this chapter describes a hardware-based method, which relies on utilizing the so-called . (FPGA). FPGA devices are not often used for purposes of implementing purely numerical algorithms. The proposed implementation can be seen as a preliminar作者: Yourself 時(shí)間: 2025-3-24 12:53 作者: narcotic 時(shí)間: 2025-3-24 17:31
Bandwidth Selectors for Kernel Density Estimation,voted to describing these selectors in more detail, both for the uni- and multivariate cases. Finally, a few numerical examples are given. The chapter is rounded off with a short section on the computational issues related to bandwidth selectors.作者: Chronic 時(shí)間: 2025-3-24 21:27
2197-6503 its applications.Describes in detail computational-like pro.This book describes computational problems related to kernel density estimation?(KDE) – one of the most important and widely used data smoothing techniques. A?very detailed description of novel FFT-based algorithms for both KDE computation作者: GORGE 時(shí)間: 2025-3-25 01:07
Kernel Density Estimation, the chapter is devoted to an introduction of two important KDE extensions, namely . KDE and KDE with .. The notion of . (KDDE) is also presented. The final part of the chapter describes how KDE can be used for nonparametric estimation of . (CDF). The chapter ends with some notes on computational aspects related to KDE.作者: 水槽 時(shí)間: 2025-3-25 03:37
,FPGA-Based Implementation of?a?Bandwidth Selection Algorithm,cepts then being described in more detail. The final part of this chapter describes the results confirming the practical usability of FPGA chips for fast implementations of complex numerical algorithms作者: entitle 時(shí)間: 2025-3-25 09:16 作者: 行為 時(shí)間: 2025-3-25 13:35
Introduction,smoothing, histograms, orthogonal series, splines, frequency polygons, wavelets or the penalized likelihood. Our method of choice is kernel density estimation, given that it can be easily interpreted and is very often used in practical applications.作者: PIZZA 時(shí)間: 2025-3-25 19:23 作者: resuscitation 時(shí)間: 2025-3-25 20:50
Book 2018niques. A?very detailed description of novel FFT-based algorithms for both KDE computations?and bandwidth selection are presented..The theory of KDE appears to have matured and is now well developed and understood.?However, there is not much progress observed in terms of performance improvements.?Th作者: embolus 時(shí)間: 2025-3-26 00:32
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