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heguji
- 非参数统计学中非参数回归的简单应用核回归程序，应用范围广泛，不需要知道样本的分布就可以使用该方法。-Non-parametric statistical regression Nonparametric kernel regression of the simple application procedure, a wide range of applications, does not need to know the distribution of the samples you can u
NBGModel
- NBGModel，most reliable background mode MRBM,Nonparametric Background subtraction classes video background of non-parametric modeling of a class that the method is modeling in the present context, one of the best way
Nonparametric-econometrics
- 简洁明了的介绍了非参计量经济学和半参计量经济学的原理和方法，是很好的非参计量经济学入门教程-Concise descr iption of the non-parametric and semi-parametric econometric theory and econometric methods, is a good introductory tutorial nonparametric econometrics
penalized_splines
- 关于惩罚样条的非参数估计方法，利用样条函数估计非参数模型-Non-parametric estimation methods of punishment on the spline, using spline nonparametric estimation model
npbayes
- 剑桥大学无参数贝叶斯课程的代码,主要包括狄利克雷过程，主题模型，无限混合高斯分布等-code of nonparametric bayesian cambridge， include dirichlet process, topic model, infinite mixutre gaussian
Z
- 基于k近邻估计法的非参数概率密度估计论文及源代码的如何实现-K-nearest neighbor nonparametric probability density estimation method based on the estimated
Nonparametric kernel density
- 计算数据的累计概率密度，采用三次样条插值计算分位点的值，区间预测，里面有具体程序及相关文献。(The cumulative probability density of the calculated data is calculated by three spline interpolation)
三步搜索法
- 本实验的目的是学习Parzen窗估计和k最近邻估计方法。在之前的模式识别研究中，我们假设概率密度函数的参数形式已知，即判别函数J(.)的参数是已知的。本节使用非参数化的方法来处理任意形式的概率分布而不必事先考虑概率密度的参数形式。在模式识别中有躲在令人感兴趣的非参数化方法，Parzen窗估计和k最近邻估计就是两种经典的估计法。(The purpose of this experiment is to study the Parzen window estimation and the k nea
lwpfindh
- 局部加权多项式回归的目的是解决全球行为模型的表现不好或不能有效地应用于不必要的努力。LWP是一种非参数回归方法，是通过低阶多项式对数据子集进行逐点拟合局部。(Locally Weighted Polynomial regression is designed to address situations in which models of global behaviour do not perform well or cannot be effectively applied without u