Results 61 to 70 of about 36,300 (256)

Biopsychosocial Determinants of Hand Function and Its Trajectories Over Five Years in Patients With Hand Osteoarthritis

Arthritis Care &Research, EarlyView.
Objective This study aimed to investigate hand function trajectories over five years in primary hand osteoarthritis (OA). Additionally, determinants of baseline and longitudinal hand function were assessed. Methods A total of 538 patients with both baseline and five‐year study visits were analyzed.
Annemiek V. E. M. Olde Meule, Coen van der Meulen, Jos Runhaar, Frits R. Rosendaal, Margreet Kloppenburg   +4 more
wiley   +1 more source

Automated Hand Flexor Tendon Thickness Measurement in Systemic Sclerosis

Arthritis Care &Research, Accepted Article.
Objective Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are currently assessed with ultrasound and measured manually, a time‐consuming process prone to inter‐observer variability.
Mark Greveling, Ties van het Erve, Yvette van de Berg, Simon Mastbergen, Julia Spierings   +4 more
wiley   +1 more source

Machine Learning Hazard Estimation with Valid Bootstrap Inference for Generalized Progressive Hybrid Censoring

Mathematics
Reliability studies frequently employ progressive censoring schemes that remove surviving units during testing, yet statistical inference under such designs remains vulnerable to parametric model misspecification.
Sherif I. Ammar, Faizah T. Alamri, Faiza A. Althubyani, Mahmoud H. Abu-Moussa   +3 more
doaj   +1 more source

A Non-Parametric Bootstrap for Spectral Clustering

, 2022
Finite mixture modelling is a popular method in the field of clustering and is beneficial largely due to its soft cluster membership probabilities. A common method for fitting finite mixture models is to employ spectral clustering, which can utilize the expectation-maximization (EM) algorithm.
Welsh, Liam, Shreeves, Phillip
openaire   +2 more sources

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

USEFULNESS OF BOOTSTRAPPING IN PORTFOLIO MANAGEMENT

Croatian Operational Research Review, 2012
This paper contains a comparison of in-sample and out-of-sample performances between the resampled efficiency technique, patented by Richard Michaud and Robert Michaud (1999), and traditional Mean-Variance portfolio selection, presented by Harry ...
Boris Radovanov, Aleksandra Marcikić
doaj  

On the Simulation Study of Jackknife and Bootstrap MSE Estimators of a Domain Mean Predictor for Fay‑Herriot Model

Acta Universitatis Lodziensis. Folia Oeconomica, 2017
We consider the problem of the estimation of the mean squared error (MSE) of some domain mean predictor for Fay‑Herriot model. In the simulation study we analyze properties of eight MSE estimators including estimators based on the jackknife method (Jiang,
Małgorzata Karolina Krzciuk
doaj   +1 more source

MSA: reproducible mutational signature attribution with confidence based on simulations

BMC Bioinformatics, 2021
Background Mutational signatures proved to be a useful tool for identifying patterns of mutations in genomes, often providing valuable insights about mutagenic processes or normal DNA damage.
Sergey Senkin
doaj   +1 more source

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

Advanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer, Christopher Mai, Luca Eisentraut, Andreas Bund, Ricardo Buettner   +4 more
wiley   +1 more source

Modeling third-party liability insurance claims: An exponential mixture distribution and parametric bootstrap-based solution

Desimal
This study aims to model large third-party liability insurance claim data using an exponential mixture distribution with a parametric bootstrap approach.
Ainani Tajriyan Muntaharridwan, Aceng Komarudin Mutaqin   +1 more
doaj   +1 more source