Nonparametric Estimate of a Parzen-Type Probability Density with an Implicitly Specified Form of the Kernel

Lapko A. V.; Lapko V. A.

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Nonparametric Estimate of a Parzen-Type Probability Density with an Implicitly Specified Form of the Kernel

机译：具有隐式指定形式的核的Parzen型概率密度的非参数估计

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摘要

A nonparametric estimate for the probability density is proposed with better approximation properties than the traditional Rosenblatt-Parzen statistics. The dependences of its properties on the form of the kernel function and on the formulas for the sampling interval for the random quantity are discussed.

机译：对于概率密度的非参数估计，提出了比传统Rosenblatt-Parzen统计更好的逼近特性。讨论了其性质对核函数形式和随机量采样间隔公式的依赖性。

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来源
《Measurement techniques》 |2016年第6期|571-576|共6页
作者
Lapko A. V.; Lapko V. A.;
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作者单位

Russian Acad Sci, Inst Computat Modelling, Siberian Branch, Krasnoyarsk, Russia|Siberian State Aerosp Univ, Krasnoyarsk, Russia;

Russian Acad Sci, Inst Computat Modelling, Siberian Branch, Krasnoyarsk, Russia|Siberian State Aerosp Univ, Krasnoyarsk, Russia;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);
原文格式 PDF
正文语种 eng
中图分类
关键词
probability density; nonparametric Rosenblatt-Parzen estimate; approximation properties; kernel function; Sturges' rule; Heinhold-Gaede formula;

机译：概率密度;非参数Rosenblatt-Parzen估计;逼近性质;核函数;Strurges规则;Heinhold-Gaede公式;
入库时间 2022-08-17 13:11:01

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Nonparametric Estimate of a Parzen-Type Probability Density with an Implicitly Specified Form of the Kernel

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