1) density weighted kernel estimator
密度加权核估计
2) weighted kernel density estimation
加权核密度估计
1.
This paper introduced the weighted kernel density estimation for flood frequency analysis and calculation.
本文引进加权核密度估计方法,研究洪水频率的分析计算;运用统计试验方法,同目前广泛认同的参数估计方法中线性矩法相比,结果表明:线性矩法及加权核密度估计法推求出的设计值的无偏性相当,但加权核密度估计方法的有效性较线性矩法好。
3) weighted kernel estimators
加权核估计
1.
Under Pairwise NQD Sequences error,we discuss the consistency of weighted kernel estimators of nonparametric regression functions of which Priestly,M.
[1]提出的一类给参数回归函数加权核估计的相合性。
4) weighted kernel estimator
加权核估计
1.
This paper discusses that when the weighted kernel estimator for nonparametric regression function from complete or censored data under independent or mixing associated error sequences,r-order mean consistency rates are obtained separately.
分别在完全样本和删失样本下,当误差为独立或混合序列时,获得了非参数回归函数加权核估计的r阶矩收敛速度。
2.
The consistency of the weighted kernel estimators of nonparametric regression function of sequences with censored data is discussed.
在ρ~相依下讨论截尾数据非参数回归函数加权核估计的强相合性,对强相合性给出一些较弱的充分条件。
3.
With independent samples,researches aim at the strong consistency of the weighted kernel estimators of nonparametric regression functions.
在独立样本下研究非参数回归函数加权核估计的强相合性 ,得到了一些较弱的充分条件。
5) Kernel density estimation
核密度估计
1.
A multimodal background model based on binning kernel density estimation;
基于分箱核密度估计的非参数多模态背景模型
2.
Small target tracking in forward looking infrared imagery based on kernel density estimation
基于核密度估计的前视红外小目标跟踪
3.
A bandwidth selection with recursive method for kernel density estimation and its application
核密度估计中递归方法选择窗宽及其应用
6) kernel density estimator
核密度估计
1.
This paper analyses the disadvantages of the existing intrusion detection technology and discusses the advantages of intrusion detection based on outlier mining,a new intrusion detection method based on kernel density estimator called IDKD is proposed.
通过分析现有入侵检测技术的不足,探讨基于孤立点挖掘的入侵检测技术的优势,提出一种基于核密度估计的入侵检测方法。
2.
Then two outlier measures and algorithms based on kernel density estimator are proposed which can identify outliers in a s.
对分布演化数据流上连续异常检测问题,进行形式化地阐述,提出了两个基于核密度估计的异常检测定义和算法,并通过大量真实数据集的实验,表明该算法具有良好的高效性和可扩展性,完全适应数据流应用的需求。
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