Results 31 to 40 of about 415,263 (295)
Research Based on High-Dimensional Fused Lasso Partially Linear Model
Mathematics, 2023 In this paper, a partially linear model based on the fused lasso method is proposed to solve the problem of high correlation between adjacent variables, and then the idea of the two-stage estimation method is used to study the solution of this model ...
Aifen Feng +4 more
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Understanding Kernel Size in Blind Deconvolution
, 2019 Most blind deconvolution methods usually pre-define a large kernel size to guarantee the support domain. Blur kernel estimation error is likely to be introduced, yielding severe artifacts in deblurring results.
Ren, Dongwei, Si-Yao, Li, Yin, Qian
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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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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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The Augmented Complex Kernel LMS
, 2011 Recently, a unified framework for adaptive kernel based signal processing of complex data was presented by the authors, which, besides offering techniques to map the input data to complex Reproducing Kernel Hilbert Spaces, developed a suitable Wirtinger ...
Bouboulis, Pantelis +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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An Improved Model for Kernel Density Estimation Based on Quadtree and Quasi-Interpolation
Mathematics, 2022 There are three main problems for classical kernel density estimation in its application: boundary problem, over-smoothing problem of high (low)-density region and low-efficiency problem of large samples.
Jiecheng Wang, Yantong Liu, Jincai Chang
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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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Blind Deconvolution with Scale Ambiguity
Applied Sciences, 2020 Recent years have witnessed significant advances in single image deblurring due to the increasing popularity of electronic imaging equipment. Most existing blind image deblurring algorithms focus on designing distinctive image priors for blur kernel ...
Wanshu Fan +3 more
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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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