Results 41 to 50 of about 2,848,958 (338)
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
openaire +5 more sources
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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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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Kernel density classification and boosting: an L2 sub analysis [PDF]
, 2005 Kernel density estimation is a commonly used approach to classification. However, most of the theoretical results for kernel methods apply to estimation per se and not necessarily to classification.
B.W. Silverman +25 more
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A tutorial on kernel density estimation and recent advances [PDF]
, 2017 This tutorial provides a gentle introduction to kernel density estimation (KDE) and recent advances regarding confidence bands and geometric/topological features.
Yen-Chi Chen
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Convergence Analysis of MAP Based Blur Kernel Estimation [PDF]
IEEE International Conference on Computer Vision, 2016 One popular approach for blind deconvolution is to formulate a maximum a posteriori (MAP) problem with sparsity priors on the gradients of the latent image, and then alternatingly estimate the blur kernel and the latent image.
Sunghyun Cho, Seungyong Lee
semanticscholar +1 more source
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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, 2015 We propose a generalized partially linear functional single index risk score model for repeatedly measured outcomes where the index itself is a function of time.
Jiang, Fei, Ma, Yanyuan, Wang, Yuanjia
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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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