Results 41 to 50 of about 19,319 (259)

Nonparametric Probability Density Function Estimation Using the Padé Approximation

Algorithms
Estimating the Probability Density Function (PDF) of observed data is crucial as a problem in its own right, and also for diverse engineering applications.
Hamid Reza Aghamiri, S. Abolfazl Hosseini, James R. Green, B. John Oommen   +3 more
doaj   +1 more source

Nonparametric series density estimation and testing [PDF]

Statistical Methods & Applications, 2018
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources

Evaluation of Dried Plasma Spot‐Based Quantification of Glial Fibrillary Acidic Protein as a Disease‐Associated Biomarker in Neuromyelitis Optica Spectrum Disorder

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To evaluate the diagnostic accuracy of glial fibrillary acidic protein (GFAP) measured in dried plasma spots versus conventional plasma‐ and serum‐GFAP testing for assessment of disease severity in aquaporin‐4 immunoglobulin G–positive neuromyelitis optica spectrum disorder (AQP4‐IgG+ NMOSD).
Felix Wohlrab, Evelyn Alvarez, Roua Hamdi, Bingqing Zhang, Hayeun Ji, Niyati Jhaveri, Patrick Schindler, Pedro Sanchez, Pia S. Sperber, Tanja Schmitz‐Hübsch, Frederike C. Oertel, Nisa Vorasoot, Najib Kissani, Falko Böhringer, Jens Kuhle, Anne‐Katrin Pröbstel, Xiao‐Jun Ma, Péter Körtvelyessy, Patrick Waters, Friedemann Paul   +19 more
wiley   +1 more source

On using nonparametric approaches for precipitation estimation

ITM Web of Conferences, 2018
Nonparametric density estimation methods have been used for precipitation estimation for decades. The new approach for estimating the density proposed recently by Geenens and Wang appears to offer advantages over them as far as their behavior in the tail
Grządziel Mariusz
doaj   +1 more source

A Novel Nonparametric Estimation for Conditional Copula Functions Based on Bayes Theorem

IEEE Access, 2019
Conditional copula which measures the conditional dependence among variables, possesses a special position in copula field. In this article, based on Bayes theorem, we derive three kinds of conditional copula functions as the product of the corresponding
Xinyao Li, Weihong Zhang, Liangli He
doaj   +1 more source

Nonparametric density estimation for multivariate bounded data [PDF]

Journal of Statistical Planning and Inference, 2010
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Taoufik Bouezmarni, Jeroen V.K. Rombouts
openaire   +4 more sources

Rheumatoid Arthritis and Coronary Artery Calcium Progression: A Case Cohort Analysis From ELSA‐Brasil

Arthritis Care &Research, EarlyView.
Objective To investigate the association between rheumatoid arthritis (RA) and coronary artery calcium (CAC) prevalence, incidence, and progression over four years in adults without prior cardiovascular disease. Methods A case‐cohort study within the Brazilian Longitudinal Study of Adult Health (ELSA‐Brasil) included 585 participants (86 patients with ...
Patrícia Fonseca Estrada, Marcos Rafael N. Cavalcante, Itamar de Souza Santos, Márcio S. Bittencourt, Vandrize Meneghini, Paulo A. Lotufo, Alessandra C. Goulart, Isabela M. Bensenor   +7 more
wiley   +1 more source

Trivariate Joint Distribution Modelling of Compound Events Using the Nonparametric D-Vine Copula Developed Based on a Bernstein and Beta Kernel Copula Density Framework

Hydrology, 2022
Low-lying coastal communities are often threatened by compound flooding (CF), which can be determined through the joint occurrence of storm surges, rainfall and river discharge, either successively or in close succession.
Shahid Latif, Slobodan P. Simonovic
doaj   +1 more source

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Feature Screening via Mutual Information Learning Based on Nonparametric Density Estimation

Journal of Mathematics, 2022
With the advent of the era of big data, feature selection in high- or ultra-high-dimensional data is increasingly important in statistics and machine learning fields.
Shengbin Zhou, Tao Wang, Yejin Huang
doaj   +1 more source