Results 21 to 30 of about 14,389 (265)
Estimating a Distribution Function at the Boundary
Austrian Journal of Statistics, 2020 Estimation of distribution functions has many real-world applications. We study kernel estimation of a distribution function when the density function has compact support. We show that, for densities taking value zero at the endpoints of the support, the
Shunpu Zhang, Zhong Li, Zhiying Zhang
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Double Kernel Method Using Line Transect Sampling
Austrian Journal of Statistics, 2016 A double kernel method as an alternative to the classical kernel method is proposed to estimate the population abundance by using line transect sampling.
Omar Eidous, M.K. Shakhatreh
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Estimation of average treatment effect based on a multi-index propensity score
BMC Medical Research Methodology, 2022 Background Estimating the average effect of a treatment, exposure, or intervention on health outcomes is a primary aim of many medical studies. However, unbalanced covariates between groups can lead to confounding bias when using observational data to ...
Jiaqin Xu +7 more
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Nonparametric estimate remarks
Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 2006 Kernel smoothers belong to the most popular nonparametric functional estimates. They provide a simple way of finding structure in data. The idea of the kernel smoothing can be applied to a simple fixed design regression model.
Jitka Poměnková
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Journal of Probability and Statistics, 2018 The circular kernel density estimator, with the wrapped Cauchy kernel, is derived from the empirical version of Carathéodory function that is used in the literature on orthogonal polynomials on the unit circle.
Yogendra P. Chaubey
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Double Kernel Estimation of Sensitivities [PDF]
Journal of Applied Probability, 2009 In this paper we address the general issue of estimating the sensitivity of the expectation of a random variable with respect to a parameter characterizing its evolution. In finance, for example, the sensitivities of the price of a contingent claim are called the Greeks. A new way of estimating the Greeks has recently been introduced in Elie, Fermanian
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A Note on Nonparametric Estimation of Conditional Hazard Quantile Function [PDF]
Journal of Risk Analysis and Crisis Response (JRACR), 2017 In this paper, we study an kernel estimator of the conditional hazard quantile function (CHQF) of a scalar response variable Y given a random variable (rv) X taking values in a semi-metric space and using the proposed estimator based of the kernel ...
El Hadj Hamel, Nadia Kadiri, Abbes Rabhi
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A Berry-Esseen Type Bound in Kernel Density Estimation for Negatively Associated Censored Data
Journal of Applied Mathematics, 2013 We discuss the kernel estimation of a density function based on censored data when the survival and the censoring times form the stationary negatively associated (NA) sequences.
Qunying Wu, Pingyan Chen
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Henderson's method approach to Kernel prediction in partially linear mixed models
Cumhuriyet Science Journal, 2020 In this article, we propose Kernel prediction in partially linear mixed models by using Henderson's method approach. We derive the Kernel estimator and the Kernel predictor via the mixed model equations (MMEs) of Henderson's that they give the best ...
Seçil Yalaz, Özge Kuran
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Asymptotic Behaviors of Nearest Neighbor Kernel Density Estimator in Left-truncated Data [PDF]
Journal of Sciences, Islamic Republic of Iran, 2014 Kernel density estimators are the basic tools for density estimation in non-parametric statistics. The k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in which the bandwidth is varied depending on the ...
V. Fakoor
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