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A note on unconditional properties of a parametrically guided Nadaraya-Watson estimator [PDF]

Statistics and Probability Letters, 1998
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Large bandwidth asymptotics for Nadaraya–Watson auto-regression estimator

Journal of the Korean Statistical Society, 2008
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Kim, Tae Yoon, Moon, Myung Sang, Lee, Sangyeol   +2 more
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On approximations to the bias of the nadaraya-watson regression estimator

Journal of Nonparametric Statistics, 2001
The Nadaraya Watson regression curve estimator is given as a ratio m = f/g. Under very mild assumptions (in particular not including any continuity of the regression function or design density), the uniform asymptotic deviation of the expectation Em from the ratio Er/Eg (a quantity usually appearing in inspections of the asymptotic properties of m) is ...
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Reweighted Nadaraya–Watson estimation of conditional density function in the right-censored model

Statistics & Probability Letters, 2021
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Xiong, Xianzhu, Ou, Meijuan, Chen, Ailian   +2 more
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Reweighted Nadaraya-Watson estimation of jump-diffusion models

Science China Mathematics, 2011
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Hanif, Muhammad, Wang, HanChao, Lin, ZhengYan   +2 more
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Modification of the adaptive Nadaraya-Watson kernel regression estimator [PDF]

Scientific Research and Essays, 2014
Nadaraya-Watson (NW) kernel regression estimator is a widely used and flexible nonparametric estimator of a regression function, which is often obtained by using a fixed bandwidth. Several studies showed that the adaptive kernel estimators with varying bandwidths have better performance results.
Hamed Aljuhani Khulood, Ismail Al turk Lutfiah   +1 more
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A Smoothed-Distribution Form of Nadaraya-Watson Estimation [PDF]

, 2010
Given observation-pairs (xi ,yi ), i = 1,...,n , taken to be independent observations of the random pair (X ,Y), we sometimes want to form a nonparametric estimate of m(x) = E(Y/ X = x). Let YE have the empirical distribution of the yi , and let (XS ,YS ) have the kernel-smoothed distribution of the (xi ,yi ).
Ralph W. Bailey, John T. Addison
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Particle Swarm Optimization-Based Weighted-Nadaraya-Watson Estimator

2018
This paper proposes a Particle Swarm Optimization-based Weighted-Nadaraya-Watson (PSO-WNW) estimator which uses the standard PSO algorithm to choose the optimal weights for WNW estimator. PSO-WNW estimator gives up the weight constraints of the classical WNW estimator, which makes PSO algorithm to find the more appropriate weights.
Jie Jiang, Yu-Lin He, Joshua Zhexue Huang   +2 more
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Statistics of Nadaraya-Watson estimator errors in surrogate-based optimization

Optimization and Engineering, 2006
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Wan, Zailong, Igusa, Takeru
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Reweighted Nadaraya–Watson estimation of stochastic volatility jump-diffusion models

Computers & Mathematics with Applications
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Shaolin Ji, Linlin Zhu
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