Results 11 to 20 of about 2,848,958 (338)
Multivariate kernel density estimation with a parametric support [PDF]
Opuscula Mathematica, 2009 We consider kernel density estimation in the multivariate case, focusing on the use of some elements of parametric estimation. We present a two-step method, based on a modification of the EM algorithm and the generalized kernel density estimator, and ...
Jolanta Jarnicka
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Curve fitting of the corporate recovery rates: the comparison of Beta distribution estimation and kernel density estimation. [PDF]
PLoS ONE, 2013 Recovery rate is essential to the estimation of the portfolio's loss and economic capital. Neglecting the randomness of the distribution of recovery rate may underestimate the risk.
Rongda Chen, Ze Wang
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Pixel-Level Kernel Estimation for Blind Super-Resolution
IEEE Access, 2021 Throughout the past several years, deep learning-based models have achieved success in super-resolution (SR). The majority of these works assume that low-resolution (LR) images are ‘uniformly’ degraded from their corresponding high ...
Jaihyun Lew, Euiyeon Kim, Jae-Pil Heo
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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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Phase-Only Image Based Kernel Estimation for Single Image Blind Deblurring [PDF]
Computer Vision and Pattern Recognition, 2018 The image motion blurring process is generally modelled as the convolution of a blur kernel with a latent image. Therefore, the estimation of the blur kernel is essentially important for blind image deblurring.
Liyuan Pan +3 more
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Predictive accuracy of option pricing models considering high-frequency data
Ekonomski Vjesnik, 2021 Purpose: Recently, considerable attention has been given to forecasting, not only the mean and the variance, but also the entire probability density function (pdf) of the underlying asset.
Josip Arnerić, Maria Čuljak
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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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Matematika, 2018 Abstrak. Pada penelitian yang dilakukan oleh Setiawan dkk, menyatakan bahwa metode loss distribution approach dengan pendekatan kernel density estimation mampu menghasilkan nilai economic capital yang lebih efisien sebesar 1,6% - 3,2% dibandingkan dengan
Erwan Setiawan, Ramdhan F Suwarman
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A Deconvolutional Deblurring Algorithm Based on Short- and Long-Exposure Images
Sensors, 2022 An iterative image restoration algorithm, directed at the image deblurring problem and based on the concept of long- and short-exposure deblurring, was proposed under the image deconvolution framework by investigating the imaging principle and existing ...
Yang Bai, Zheng Tan, Qunbo Lv, Min Huang
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Improved parameter estimation of Time Dependent Kernel Density by using Artificial Neural Networks
Journal of Finance and Data Science, 2018 Time Dependent Kernel Density Estimation (TDKDE) used in modelling time-varying phenomenon requires two input parameters known as bandwidth and discount to perform.
Xing Wang +2 more
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