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Beta Kernel Estimator for a Cumulative Distribution Function with Bounded Support [PDF]
Journal of Sciences, Islamic Republic of Iran, 2023 Kernel estimation of the cumulative distribution function (CDF), when the support of the data is bounded, suffers from bias at the boundaries. To solve this problem, we introduce a new estimator for the CDF with support (0,1) based on the beta kernel ...
Behzad Mansouri +2 more
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Statistics & Risk Modeling, 2012 Abstract Many statistical estimation techniques for high-dimensional or functional data are based on a preliminary dimension reduction step, which consists in projecting the sample X 1,...,X n onto the first D eigenvectors of the Principal Component Analysis ...
Biau, Gérard, Mas, André
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Comparing nonparametric density estimators using different canonical kernel functions [PDF]
المجلة العراقية للعلوم الاحصائية, 2010 In this article we make a comparison between three different nonparametric density estimators .The first estimator is called fixed kernel which uses a fixed bandwidth.
Munaf Yousif, Dhafir H.Rashed
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Using Kernel Estimator and K-Mean Clustering Approach to Hand Gesture Recognition [PDF]
Al-Rafidain Journal of Computer Sciences and Mathematics, 2013 In this paper we used non parametric density estimator (Kernel Estimator) to estimate probability density function for Image data of Hand Gesture and warping Hand Gesture and we see the curve for Kernel Estimator and combine the curve between Kernel ...
Ban Mitras, AAlA Mohammed
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Kernel Minimum Error Entropy Based Estimator for MIMO Radar in Non-Gaussian Clutter
IEEE Access, 2021 In this paper, a kernel minimum error entropy (KMEE) based estimator is proposed for the estimation of multiple targets’ direction of departure (DOD), the direction of arrival (DOA), and the Doppler shift with multiple input multiple output radar ...
Uday Kumar Singh +3 more
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A New Kernel Estimator of Copulas Based on Beta Quantile Transformations
Mathematics, 2021 A copula is a multivariate cumulative distribution function with marginal distributions Uniform(0,1). For this reason, a classical kernel estimator does not work and this estimator needs to be corrected at boundaries, which increases the difficulty of ...
Catalina Bolancé, Carlos Alberto Acuña
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Barekeng, 2022 ISSI reflects the movement of sharia stock prices as a whole. It is necessary to forecast the share price to help investors determine whether the shares should be sold, bought, or retained. This study aims to predict the value of ISSI using nonparametric
Yuniar Farida +2 more
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Nonparametric estimation of the measure of functional dependence
AIMS Mathematics, 2021 In this paper, we propose a beta kernel estimator to measure functional dependence (MFD). The MFD not only can measure the strength of linear or monotonic relationships, but it is also suitable for more complicated functional dependence.
Qingsong Shan, Qianning Liu
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Robust kernel density estimation [PDF]
2008 IEEE International Conference on Acoustics, Speech and Signal Processing, 2008 We propose a method for nonparametric density estimation that exhibits robustness to contamination of the training sample. This method achieves robustness by combining a traditional kernel density estimator (KDE) with ideas from classical $M$-estimation.
Kim, JooSeuk, Scott, Clayton D.
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Barekeng, 2023 Research on innovations in the statistics and statistical computing program systems implemented in the health sector. The development of a mixed estimator model is an innovation of nonparametric regression analysis by combining two approaches in ...
Sifriyani Sifriyani +3 more
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