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- W122742822 abstract "In this research, a local kernel regression method was proposed to improve the computational efficiency after analyzing the kernel weights of the nonparametric kernel regression Based on the correlation between the distribution function and the probability density function, together with the nonparametric local kernel regression we developed a new probability density estimation method With the proper setting of the sparse factor, the number of the kernels involved in the kernel smooth was controlled, and the density was estimated with highly fitness and smoothness According to the simulations, we can see that the proposed method shows a very well performance both in the accuracy and the efficiency." @default.
- W122742822 created "2016-06-24" @default.
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- W122742822 date "2010-01-01" @default.
- W122742822 modified "2023-09-24" @default.
- W122742822 title "Probability Density Estimation Based on Nonparametric Local Kernel Regression" @default.
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- W122742822 doi "https://doi.org/10.1007/978-3-642-13278-0_60" @default.
- W122742822 hasPublicationYear "2010" @default.
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