Results 21 to 30 of about 48,941 (244)
Bandwidth selection for the Wolverton–Wagner estimator
Journal of Statistical Planning and Inference, 2020 26 pages, 5 ...
Fabienne Comte, Nicolas Marie
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Plug-in Bandwidth Selection for Kernel Density Estimation with Discrete Data
Econometrics, 2015 This paper proposes plug-in bandwidth selection for kernel density estimation with discrete data via minimization of mean summed square error. Simulation results show that the plug-in bandwidths perform well, relative to cross-validated bandwidths, in ...
Chi-Yang Chu +2 more
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Bias corrected bootstrap bandwidth selection [PDF]
Journal of Nonparametric Statistics, 1997 Current bandwidth selectors for kernel density estimation that are asymptotically optimal often prove less promising under more moderate sample sizes. The point of this paper is to derive a class of bandwidth selectors that attain optimal root-n convergence while still showing good results under small and moderate sample sizes.
Birgit Grund, Jörg Polzehl
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The Optimal Bandwidth Parameter Selection in GPH Estimation
Journal of Mathematics, 2021 In this paper, the optimal bandwidth parameter is investigated in the GPH algorithm. Firstly, combining with the stylized facts of financial time series, we generate long memory sequences by using the ARFIMA (1, d, 1) process.
Weijie Zhou +3 more
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Bandwidth Selection in Geographically Weighted Regression Models via Information Complexity Criteria
Journal of Mathematics, 2022 The geographically weighted regression (GWR) model is a local spatial regression technique used to determine and map spatial variations in the relationships between variables.
Tuba Koç
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Optimal Bandwidth Selection Methods with Application to Wind Speed Distribution
Mathematics, 2023 Accurate estimation of the unknown probability density functions of critical variables, such as wind speed—which plays a pivotal role in harnessing clean energy—is essential for various scientific and practical applications.
Necla Gündüz, Şule Karakoç
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Nonparametric Inference in Mixture Cure Models
Proceedings, 2018 A completely nonparametric method for the estimation of mixture cure models is proposed. Nonparametric estimators for the cure probability (incidence) and for the survival function of the uncured population (latency) are introduced.
Ana López-Cheda +3 more
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nprobust: Nonparametric Kernel-Based Estimation and Robust Bias-Corrected Inference
Journal of Statistical Software, 2019 Nonparametric kernel density and local polynomial regression estimators are very popular in statistics, economics, and many other disciplines. They are routinely employed in applied work, either as part of the main empirical analysis or as a preliminary ...
Sebastian Calonico +2 more
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Realized density estimation using intraday prices
Croatian Review of Economic, Business and Social Statistics, 2020 Availability of high-frequency data, in line with IT developments, enables the use of Availability of high-frequency data, in line with IT developments, enables the use of more information to estimate not only the variance (volatility), but also higher ...
Arnerić Josip
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Bandwidth Prediction based on Nu-Support Vector Regression and Parallel Hybrid Particle Swarm Optimization [PDF]
International Journal of Computational Intelligence Systems, 2010 This paper addresses the problem of generating multi-step-ahead bandwidth prediction. Variation of bandwidth is modeled as a Nu-Support Vector Regression (Nu-SVR) procedure. A parallel procedure is proposed to hybridize constant and binary Particle Swarm
Liang Hu, Xilong Che, Xiaochun Cheng
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