Results 81 to 90 of about 460,060 (291)

Exploring helical dynamos with machine learning

, 2019
We use ensemble machine learning algorithms to study the evolution of magnetic fields in magnetohydrodynamic (MHD) turbulence that is helically forced.
Nauman, Farrukh, Nättilä, Joonas
core   +1 more source

Fluid Biomarkers of Disease Burden and Cognitive Dysfunction in Progressive Supranuclear Palsy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Identifying objective biomarkers for progressive supranuclear palsy (PSP) is crucial to improving diagnosis and establishing clinical trial and treatment endpoints. This study evaluated fluid biomarkers in PSP versus controls and their associations with regional 18F‐PI‐2620 tau‐PET, clinical, and cognitive outcomes.
Roxane Dilcher, Charles B. Malpas, Stuart J. McDonald, William T. O’Brien, Craig Despott, Kelly L. Bertram, Matthew P. Pase, Lukas Frontzkowski, Meng Law, Terence J. O’Brien, Lucy Vivash   +10 more
wiley   +1 more source

Bayesian regression modeling and inference of energy efficiency data: the effect of collinearity and sensitivity analysis

Frontiers in Energy Research
The majority of research predicted heating demand using linear regression models, but they did not give current building features enough context. Model problems such as Multicollinearity need to be checked and appropriate features must be chosen based on
Laila A. Al-Essa, Endris Assen Ebrahim, Yusuf Ali Mergiaw   +2 more
doaj   +1 more source

An Rkhs Approach for Pivotal Inference in Functional Linear Regression

Statistica Sinica
We develop methodology for testing hypotheses regarding the slope function in functional linear regression for time series via a reproducing kernel Hilbert space approach. In contrast to most of the literature, which considers tests for the exact nullity of the slope function, we are interested in the null hypothesis that the slope function vanishes ...
Dette, Holger, Tang, Jiajun
openaire   +2 more sources

Vestibular Patient Journey: Insights From Vestibular Disorders Association (VeDA) Registry

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Vestibular symptoms impose a high burden of disability. Understanding real‐world diagnostic and treatment pathways can identify care gaps and guide interventions. We aimed to characterize symptom profiles, diagnostic trends, provider involvement, and treatment patterns in vestibular disorders.
Ali Rafati, Sami I. Nassar, Shaun A. Nguyen, Patricia L. Gerend, Michael C. Schubert, Michael T. Teixido, Frederick A. Godley, Joel A. Goebel, Cynthia A. Ryan, Habib G. Rizk, Amir Kheradmand   +10 more
wiley   +1 more source

Baseline Regional Cholinergic Denervation Predicts Cognitive Trajectories in Moderate Parkinson Disease

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Cognitive decline is a disabling and variable feature of Parkinson disease (PD). While cholinergic system degeneration is linked to cognitive impairments in PD, most prior research reported cross‐sectional associations. We aimed to fill this gap by investigating whether baseline regional cerebral vesicular acetylcholine transporter ...
Taylor Brown, Giulia Carli, Prabesh Kanel, Stiven Roytman, Jaimie Barr, Nicolaas I. Bohnen, Roger L. Albin   +6 more
wiley   +1 more source

Bayesian variable selection in linear quantile mixed models for longitudinal data with application to macular degeneration.

PLoS ONE, 2020
This paper presents a Bayesian analysis of linear mixed models for quantile regression based on a Cholesky decomposition for the covariance matrix of random effects.
Yonggang Ji, Haifang Shi
doaj   +1 more source

On Inference of the Linear Regression Model with Groupwise Heteroscedasticity

Pakistan Journal of Statistics and Operation Research, 2017
The performance of heteroscedasticity consistent covariance matrix estimators (HCCMEs), namely, HC0, HC1, HC2, HC3 and HC4 have been evaluated by numerous researchers for the heteroscedastic linear regression models. This study focuses on examining the performance of these covariance estimators in case of groupwise heteroscedasticity.
Abdul Majid, Muhammad Aslam, Muhammad Amanullah, Saima Altaf   +3 more
openaire   +2 more sources

Epilepsy‐Associated Variants of a Single SCN1A Codon Exhibit Divergent Functional Properties

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Pathogenic variants in SCN1A, which encodes the voltage‐gated sodium channel NaV1.1, are associated with multiple epilepsy syndromes exhibiting a range of clinical severity. SCN1A variants are reported in different syndromes, including Dravet syndrome, which is associated with loss‐of‐function, whereas neonatal/infantile‐onset ...
Lanie N. Liebovitz, Christopher H. Thompson, Linda C. Laux, Alfred L. George Jr.   +3 more
wiley   +1 more source

A robust permutation test for subvector inference in linear regressions

Quantitative Economics
We develop a new permutation test for inference on a subvector of coefficients in linear models. The test is exact when the regressors and the error terms are independent. Then we show that the test is asymptotically of correct level, consistent, and has power against local alternatives when the independence condition is relaxed, under two main ...
D'Haultfœuille, Xavier, Tuvaandorj, Purevdorj   +1 more
openaire   +3 more sources