Results 11 to 20 of about 14,389 (265)
A Kernel Estimator of a Conditional Quantile
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Xiaojing Xiang
exaly +3 more sources
Beta Kernel Estimator for a Cumulative Distribution Function with Bounded Support [PDF]
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
doaj +1 more source
Comparing nonparametric density estimators using different canonical kernel functions [PDF]
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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Kernel Minimum Error Entropy Based Estimator for MIMO Radar in Non-Gaussian Clutter
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
doaj +1 more source
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
openaire +3 more sources
A New Kernel Estimator of Copulas Based on Beta Quantile Transformations
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
doaj +1 more source
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
doaj +1 more source
Robust kernel density estimation [PDF]
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.
JooSeuk Kim, Clayton D. Scott
openaire +3 more sources
Kernel estimation for quantile sensitivities [PDF]
AbstractQuantiles, also known as value‐at‐risks in the financial industry, are important measures of random performances. Quantile sensitivities provide information on how changes in input parameters affect output quantiles. They are very useful in risk management.
Guangwu Liu, L. Jeff Hong
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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
doaj +1 more source

