Nadaraya–Watson estimator for I.I.D. paths of diffusion processes [PDF]
Scandinavian Journal of Statistics, 2022 AbstractThis paper deals with a nonparametric Nadaraya–Watson (NW) estimator of the drift function computed from independent continuous observations of a diffusion process. Risk bounds on the estimator and its discrete‐time approximation are established.
Marie, Nicolas, Rosier, Amélie
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PAC learning using Nadaraya-Watson estimator based on orthonormal systems [PDF]
, 1997 Regression or function classes of Euclidean type with compact support and certain smoothness properties are shown to be PAC learnable by the Nadaraya-Watson estimator based on complete orthonormal systems. While requiring more smoothness properties than typical PAC formulations, this estimator is computationally efficient, easy to implement, and known ...
Hongzhu Qiao +2 more
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On the adaptive Nadaraya-Watson kernel regression estimators
, 2010 WOS ...
DEMİR, S., TOKTAMİŞ, Ö.
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Spatio-Functional Nadaraya–Watson Estimator of the Expectile Shortfall Regression
AxiomsThe main aim of this paper is to consider a new risk metric that permits taking into account the spatial interactions of data. The considered risk metric explores the spatial tail-expectation of the data.
Mohammed B. Alamari +3 more
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Nadaraya-Watson type estimator of the transition density function for diffusion processes
Annals of the Institute of Statistical Mathematics24 pages, 4 ...
Marie, Nicolas, Sacko, Ousmane
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Local Linear Regression Estimator on the Boundary Correction in Nonparametric Regression Estimation
Journal of Statistical Theory and Applications (JSTA), 2020 The precision and accuracy of any estimation can inform one whether to use or not to use the estimated values. It is the crux of the matter to many if not all statisticians.
Langat Reuben Cheruiyot
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Smoothing parameter selection in Nadaraya-Watson kernel nonparametric regression using nature-inspired algorithm optimization [PDF]
المجلة العراقية للعلوم الاحصائية, 2020 In the context of Nadaraya-Watson kernel nonparametric regression, the curve estimation is fully depending on the smoothing parameter. At this point, the nature-inspired algorithms can be used as an alternative tool to find the optimal selection. In this
Zinah Basheer, Zakariya Algamal
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A Note on the Unconditional Bias of the Nadaraya-Watson Regression Estimator [PDF]
, 2018 In this note we investigate the order of the unconditional bias of the Nadarya-Watson (Nadaraya, 1964; Watson, 1964) estimator for a multivariate regression. Surprisingly, previous attempts in establishing this result are either imprecise and technically
Pelrine, Kellin
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Mathematics, 2023 This paper studies the estimation problem for semi-varying coefficient heteroscedastic instrumental variable models with missing responses. First, we propose the adjusted estimators for unknown parameters and smooth functional coefficients utilizing the ...
Weiwei Zhang, Jingxuan Luo, Shengyun Ma
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Nadaraya-Watson estimator for sensor fusion problems [PDF]
Proceedings of International Conference on Robotics and Automation, 2002 In a system of N sensors, the sensor S/sub j/, j=1,2...,N, outputs Y/sup j/spl isin//[0, 1], according to an unknown probability density p/sub j/(Y/sup j|/X), corresponding to input X/spl isin/[0, 1]. A training n-sample (X/sub 1/,Y/sub 1/), (X/sub 2/,Y/sub 2/), ..., (X/sub n/,Y/sub n/) is given where Y/sub i/=(Y/sub i//sup 1,/Y/sub i//sup 2,/...,Y/sub
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