Results 31 to 40 of about 411,514 (294)
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
, 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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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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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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The McCance Brain Care Score and Mortality: Evidence From a Large‐Scale Population‐Based Cohort
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives This study aimed to examine the relationship between the McCance Brain Care Score (BCS) and mortality in the general population. Methods We conducted a prospective, population‐based cohort study using data from the UK Biobank. Participants with complete data enabling calculation of BCS and full mortality information were included ...
Zhiqiang Xu, Xiaoxiao Wang, Nan Li
wiley +1 more source
Estimation of Dynamic Networks for High-Dimensional Nonstationary Time Series
Entropy, 2019 This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes.
Mengyu Xu, Xiaohui Chen, Wei Biao Wu
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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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Large-Margin Determinantal Point Processes [PDF]
, 2014 Determinantal point processes (DPPs) offer a powerful approach to modeling diversity in many applications where the goal is to select a diverse subset.
Chao, Wei-lun +3 more
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Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim +3 more
wiley +1 more source
IET Wireless Sensor SystemsThis paper introduces a kernel‐based approach to enhance the security of distributed estimation in the presence of adversary links. Adversary links often degrade distributed recovery algorithm performance in distributed estimation.
Zahra Khoshkalam +2 more
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