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核密度估计的英文

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"核密度估计"怎么读用"核密度估计"造句

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  • kernal density

例句与用法

  • Moderate deviations for the kernel density estimators
    核密度估计的中偏差
  • Methods non - parameter kernel density estimation method was adopted
    方法采用非参数核密度估计推断方法。
  • Compared with traditional pca - based methods which assumes that the data are independent and follow normal distribution , this kernel - density based method does n ' t require any assumption on data distribution
    而传统的基于主元分析的系统性能监控方法都是假定测量数据相互独立且服从正态分布的,采用核密度估计方法无需对数据的分布作任何假定。
  • In last chapter , a new conception and model for var , based on prediction are brought forward . finally , a kind of new kernel density estimating function , adapting to financial time series is employed to extend time series kernel density estimating model
    文中最后一部分,从风险价值预测的角度出发,建立了基于var预测的概念和模型,提出了一种适合估计金融时间序列分布的核密度函数,并采用加权法推广了时间序列核密度估计模型
  • Considering the fact that continuous process and batch process are the two important production modes in process industry , and each of them has its respective characteristic , our works are divided into two parts , those are , monitoring of continuous processes and of batch processes . the main contribution of this thesis is as follows , 1 multivariate kernel - density estimation method is used to calculate the distribution of data and assess the impact of parametric uncertainty on the monitoring performance
    由于连续生产方式和间歇生产方式是流程工业中两种重要的生产方式,它们具有各自不同的特点,因此,本文的工作分两大部分,即连续工业过程的监控和间歇工业过程的监控,具体包括: ( 1 )采用多变量核密度估计方法,研究了参数不确定条件下,过程数据的分布及其对系统监控性能的影响。
  • It also puts forward logical explanations to a few facts that are still unable to be explained , up to now , by the classical consumption models . however , for the scholars in china , the cognition of the buffer - stock theory still remains at a superficial level of only providing simple theoretical introduction to it . a finer depiction and empirical application of it will not only facilitate studies on the related theories in china but also do great benefit to the development of the buffer - stock theory itself because china is admittedly one of the
    本论文的主要发现及创新包括:在理解和刻画我国居民的预防性储蓄行为时,缓冲储备模型要优于以储蓄水平量作为被解释变量的模型;核密度估计方法对不确定性的描述更准确;从储蓄率变化率的角度进行的格兰杰因果关系检验证实了我国的居民存款储蓄对经济增长有推动作用;养老金的变化对我国居民储蓄行为具有显著影响,而我国现有的医疗保障体系没有发挥其应该能够发挥出的作用。
用"核密度估计"造句  

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百科解释

核密度估计(kernel density estimation)是在概率论中用来估计未知的密度函数,属于非参数检验方法之一,由Rosenblatt (1955)和Emanuel Parzen(1962)提出,又名Parzen窗(Parzen window)。Ruppert和Cline基于数据集密度函数聚类算法提出修订的核密度估计方法。
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