Nonparametric estimation of a probability density function and its derivatives. C-approach

被引:0
作者
V. G. Alekseev
机构
[1] Russian Academy of Sciences,Obukhov Institute of Atmospheric Physics
关键词
probability density function; nonparametric (kernel) estimator; uniform consistency of estimate with increasing sample size;
D O I
10.1134/S8756699009010075
中图分类号
学科分类号
摘要
Nonparametric (kernel) estimation of a probability density function f(x) for a sample of finite size is considered using the C-approach. The smoothness parameter β of the estimated probability density is introduced. For the case β > 2, it is shown that the convergence of the density estimate fn(x) to the function f(x) can be improved by using alternating-sign weight functions (higher-order weight functions). Estimation of the derivatives of a function is briefly considered using the same approach.
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页码:43 / 47
页数:4
相关论文
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