Results 101 to 110 of about 113,075 (317)
A spiking neural network implementation of Gaussian belief propagation
Bayesian inference offers a principled account of information processing in natural agents. However, it remains an open question how neural mechanisms perform their abstract operations.
Sepideh Adamiat +2 more
doaj +1 more source
Mapping wind erosion hazard with regression-based machine learning algorithms
Land susceptibility to wind erosion hazard in Isfahan province, Iran, was mapped by testing 16 advanced regression-based machine learning methods: Robust linear regression (RLR), Cforest, Non-convex penalized quantile regression (NCPQR), Neural network ...
Hamid Gholami +3 more
doaj +1 more source
Comparative Effectiveness and Safety of Inebilizumab Versus Rituximab in AQP4‐IgG‐Positive NMOSD
ABSTRACT Objective Rituximab (anti‐CD20, RTX) and inebilizumab (anti‐CD19, INE) represent B‐cell‐depleting therapies used for aquaporin‐4 antibody‐positive (AQP4‐IgG+) neuromyelitis optica spectrum disorder (NMOSD); however, direct comparative evidence remains limited.
Jie Lin +11 more
wiley +1 more source
Heteroskedasticity-robust inference in linear regression models
This paper considers inference in heteroskedastic linear regression models with many control variables. The slope coefficients on these variables are nuisance parameters. Our setting allows their number to grow with the sample size, possibly at the same rate, in which case they are not consistently estimable.
openaire +2 more sources
ABSTRACT Objective Digital technologies hold promise for transforming healthcare by enhancing personalized treatments and offer valuable opportunities to improve patient care. Here, we evaluated several novel, self‐administered, home‐based, digital endpoints for their association with corresponding conventional standard clinical measures (primary) in ...
Arne Mueller +14 more
wiley +1 more source
Inference for high-dimensional sparse econometric models [PDF]
This article is about estimation and inference methods for high dimensional sparse (HDS) regression models in econometrics. High dimensional sparse models arise in situations where many regressors (or series terms) are available and the regression ...
Christian Hansen +2 more
core
A Two‐Stage Questionnaire and Actigraphy Screening for iRBD in a Multicenter Retrospective Cohort
ABSTRACT Objective Isolated rapid‐eye‐movement sleep behavior disorder is a prodromal marker of synucleinopathies. However, most cases remain undiagnosed due to the insufficient predictive value of questionnaires and limited access to confirmatory video‐polysomnography. We assessed a two‐stage screening strategy combining a brief questionnaire on rapid‐
Caleb A. Massimi +17 more
wiley +1 more source
Prominent Movement Disorders in RNU2‐2‐Related Spliceosomopathy
ABSTRACT Pediatric movement disorders often overlap with neurodevelopmental diseases, suggesting shared molecular mechanisms. Variants in small nuclear RNA (snRNA) genes encoding spliceosome components have recently been associated with neurodevelopmental disorders, termed “RNUopathies.” We analyzed genome sequencing data from 14 patients with ...
Magdalena Krygier +6 more
wiley +1 more source
Multivariate Student -t Regression Models: Pitfalls and Inference [PDF]
We consider likelihood-based inference from multivariate regression models with independent Student-t errors. Some very intruiging pitfalls of both Bayesian and classical methods on the basis of point observations are uncovered. Bayesian inference may be
Steel, M.F.J., Fernández, C.
core +1 more source
The limiting power of autocorrelation tests in regression models with linear restrictions [PDF]
It is well known that the Durbin-Watson and several other tests for first-order autocorrelation have limiting power of either zero or one in a linear regression model without an intercept, and tend to a constant lying strictly between these values when ...
Wan, Alan, Zou, Guohua, Banerjee, Anurag
core

