Results 21 to 30 of about 81,542 (267)
A new family of kernels from the beta polynomial kernels with applications in density estimation
IJAIN (International Journal of Advances in Intelligent Informatics), 2020 One of the fundamental data analytics tools in statistical estimation is the non-parametric kernel method that involves probability estimates production.
Israel Uzuazor Siloko +2 more
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Super Resolution with Kernel Estimation and Dual Attention Mechanism
Information, 2020 Convolutional Neural Networks (CNN) have led to promising performance in super-resolution (SR). Most SR methods are trained and evaluated on predefined blur kernel datasets (e.g., bicubic).
Huan Liang +4 more
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Kernel regression utilizing heterogeneous datasets
Statistical Theory and Related Fields, 2023 Data analysis in modern scientific research and practice has shifted from analysing a single dataset to coupling several datasets. We propose and study a kernel regression method that can handle the challenge of heterogeneous populations.
Chi-Shian Dai, Jun Shao
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Mars Image Super-Resolution Based on Generative Adversarial Network
IEEE Access, 2021 High-resolution (HR) Mars images have great significance for studying the land-form features of Mars and analyzing the climate on Mars. Nowadays, the mainstream image super-resolution methods are based on deep learning or CNNs, which are better than ...
Cong Wang +4 more
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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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A Doubly Smoothed PD Estimator in Credit Risk
Proceedings, 2020 In this work a doubly smoothed probability of default (PD) estimator is proposed based on a smoothed version of the survival Beran’s estimator. The asymptotic properties of both the smoothed survival and PD estimators are proved and their behaviour is ...
Rebeca Peláez Suárez +2 more
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Rating Crop Insurance Policies with Efficient Nonparametric Estimators That Admit Mixed Data Types
Journal of Agricultural and Resource Economics, 2006 The identification of improved methods for characterizing crop yield densities has experienced a recent surge in activity due in part to the central role played by crop insurance in the Agricultural Risk Protection Act of 2000 (estimates of yield ...
Jeffrey S. Racine, Alan P. Ker
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Nonparametric Estimation of Extreme Quantiles with an Application to Longevity Risk
Risks, 2021 A new method to estimate longevity risk based on the kernel estimation of the extreme quantiles of truncated age-at-death distributions is proposed. Its theoretical properties are presented and a simulation study is reported.
Catalina Bolancé, Montserrat Guillen
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Interval Estimation of Value-at-Risk Based on Nonparametric Models
Econometrics, 2018 Value-at-Risk (VaR) has become the most important benchmark for measuring risk in portfolios of different types of financial instruments. However, as reported by many authors, estimating VaR is subject to a high level of uncertainty.
Hussein Khraibani +2 more
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BACKGROUND ESTIMATION IN KERNEL SPACE [PDF]
International Journal of Pattern Recognition and Artificial Intelligence, 2011 One problem in background estimation is the inherent change in the background such as waving tree branches, water surfaces, camera shakes, and the existence of moving objects in every image. In this paper, a new method for background estimation is proposed based on function approximation in kernel domain.
Hamidreza Baradaran Kashani +2 more
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