Results 11 to 20 of about 335,347 (295)
New Bandwidth Selection for Kernel Quantile Estimators [PDF]
Journal of Probability and Statistics, 2012 We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a ...
Ali Al-Kenani, Keming Yu
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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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Bandwidth selection for nonparametric modal regression [PDF]
Communications in Statistics - Simulation and Computation, 2018 In the context of estimating local modes of a conditional density based on kernel density estimators, we show that existing bandwidth selection methods developed for kernel density estimation are unsuitable for mode estimation. We propose two methods to select bandwidths tailored for mode estimation in the regression setting.
Haiming Zhou, Xianzheng Huang
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Boundary Kernels for Distribution Function Estimation
Revstat Statistical Journal, 2013 Boundary effects for kernel estimators of curves with compact supports are well known in regression and density estimation frameworks. In this paper we address the use of boundary kernels for distribution function estimation.
Carlos Tenreiro
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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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Bandwidth selection in pre-smoothed particle filters [PDF]
Statistics and Computing, 2012 For the purpose of maximum likelihood estimation of static parameters, we apply a kernel smoother to the particles in the standard SIR filter for non-linear state space models with additive Gaussian observation noise. This reduces the Monte Carlo error in the estimates of both the posterior density of the states and the marginal density of the ...
Tore Selland Kleppe, Hans J. Skaug
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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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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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Bootstrap Bandwidth Selection Using anh‐Dependent Pilot Bandwidth [PDF]
Scandinavian Journal of Statistics, 2008 Abstract. The problem of choosing the bandwidthhfor kernel density estimation is considered. All the plug‐in‐type bandwidth selection methods require the use of a pilot bandwidthg. The usual way to make anh‐dependent choice ofgis by obtaining their asymptotic expressions separately and solving the two equations.
Chacón, José E. +2 more
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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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