Results 171 to 180 of about 501,333 (190)

The uniform convergence of the nadaraya‐watson regression function estimate

Canadian Journal of Statistics, 1978
AbstractIf (X1,Y1), …, (Xn,Yn) is a sequence of independent identically distributed Rd × R‐valued random vectors then Nadaraya (1964) and Watson (1964) proposed to estimate the regression function m(x) = ϵ {Y1|X1 = x{ by where K is a known density and {hn} is a sequence of positive numbers satisfying certain properties.
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A NEW MODIFICATION TO THE ADAPTIVE NADARAYA-WATSON KERNEL REGRESSION ESTIMATOR

Advances and Applications in Statistics, 2016
Summary: In this paper, a modification to the adaptive Nadaraya-Watson (NW) kernel regression estimator based on a function of the range of pilot density estimates and the sample size with varying bandwidths is proposed. The performance of proposed estimator in terms of mean squared error (MSE) is compared with NW and modified NW estimators.
Joshi, Venkatesh B., Deshpande, Bhargavi
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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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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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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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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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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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Nadaraya–Watson estimator for I.I.D. paths of diffusion processes

Scandinavian Journal of Statistics, 2023
Nicolas Marie
exaly  

Almost Sure Convergence Properties of Nadaraya-Watson Regression Estimates

2002
For Nadaraya-Watson regression estimates with window kernel self-contained proofs of strong universal consistency for special bandwidths and of the corresponding Cesaro summability for general bandwidths are given.
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Regional forecasting of PM concentrations: A novel model based on the empirical orthogonal function analysis and Nadaraya–Watson kernel regression estimator

Environmental Modelling and Software, 2023
Dejian Zhang
exaly