Results 41 to 50 of about 1,669,248 (311)
Nonparametric Copula Density Estimation Methodologies
MathematicsThis paper proposes several methodologies whose objective consists of securing copula density estimates. More specifically, this aim will be achieved by differentiating bivariate least-squares polynomials fitted to Deheuvels’ empirical copulas, by making
Serge B. Provost, Yishan Zang
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Nonparametric estimation in random sum models
Statistica, 2013 Let X1,X2,…,XN be independent, identically distributed, non-negative, integervalued random variables and let N be a non-negative, integer-valued random variable independent of X1,X2,…,XN .
Hassan S. Bakouch, Thomas A. Severini
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Nonparametric Range-Based Double Smoothing Spot Volatility Estimation for Diffusion Models
Complexity, 2020 We consider nonparametric spot volatility estimation for diffusion models with discrete high frequency observations. Our estimator is carried out in two steps.
Jingwei Cai
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Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective This study aimed to investigate the immunological response to influenza vaccination, the incidence and severity of influenza infection, and the side effects of the vaccination in patients with ischemic stroke. Methods This prospective observational study was conducted between 2023 and 2024 at Ramathibodi Hospital.
Achiraya Pakngao +5 more
wiley +1 more source
Natural Frequencies of Levodopa‐Induced Dyskinesia in Parkinson's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objectives Abnormal involuntary movements, known as dyskinesias, are common complications of levodopa treatment in patients with Parkinson's disease and can significantly impair quality of life. The underlying pathophysiology remains unclear, and current therapeutic options are limited.
Ioannis U. Isaias +3 more
wiley +1 more source
Model Selection for High Dimensional Nonparametric Additive Models via Ridge Estimation
Mathematics, 2022 In ultrahigh dimensional data analysis, to keep computational performance well and good statistical properties still working, nonparametric additive models face increasing challenges.
Haofeng Wang +3 more
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Nonparametric Estimation of Value-at-Risk [PDF]
SSRN Electronic Journal, 2012 A method to estimate an extreme quantile that requires no distributional assumptions is presented. The approach is based on transformed kernel estimation of the cumulative distribution function (cdf). The proposed method consists of a double transformation kernel estimation.
Ramon Alemany +2 more
openaire +4 more sources
Stage‐Dependent β‐Synuclein Links MRI and Cognitive Decline in Alzheimer's Disease
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Synaptic degeneration drives cognitive decline in Alzheimer's disease (AD), but synaptic biomarkers are scarce. Brain‐enriched β‐synuclein emerged as a synaptic damage marker. We investigated its diagnostic, prognostic, and structural correlates across the AD continuum.
Ulaş Ay +15 more
wiley +1 more source
ANALISIS MODEL REGRESI NONPARAMETRIK SIRKULAR-LINEAR BERGANDA
E-Jurnal Matematika, 2016 Circular data are data which the value in form of vector is circular data. Statistic analysis that is used in analyzing circular data is circular statistics analysis.
KOMANG CANDRA IVAN +2 more
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Nonparametric and semiparametric methods for economic research [PDF]
, 1992 Developments in the vast and growing literatures on nonparametric and semiparametric statistical estimation are reviewed. The emphasis is on useful methodology rather than statistical properties for their own sake. Some empirical applications to economic
Robinson, Peter M., Delgado, Miguel A.
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