Results 51 to 60 of about 177 (131)
Statistics in Medicine, Volume 45, Issue 13-14, June 2026.ABSTRACT Although homoscedasticity is often assumed in linear regression, real data may show variance patterns or residual structures that violate this assumption. We propose VarGuid, a variance‐guided framework for two related settings: Covariate‐dependent conditional variance under a global linear mean model, and residual nonlinear mean structure ...
Sibei Liu, Min Lu
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Subgroup Identification via Multiple Change Point Detection: Methods and Applications
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Subgroup identification methods facilitate the discovery of clinically meaningful subpopulations with differing disease progression, improving personalized risk assessment and treatment strategies. ABSTRACT Subgroup identification is a significant research area in statistics and machine learning, aiming to partition a heterogeneous population into more
Yaguang Li +3 more
wiley +1 more source
Covariance Estimation for Wide Data
WIREs Computational Statistics, Volume 18, Issue 2, June 2026.Covariance matrix estimation is fundamental to multivariate analysis, with applications spanning finance, genomics, climate science, and signal processing. This review synthesizes recent advances in high‐dimensional covariance estimation‐thresholding, linear and nonlinear shrinkage, graphical models, and random matrix theory‐under a unifying framework ...
Eran Raviv
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Deep Learning for Satellite‐Based Forest Disturbance Monitoring: Recent Advances and Challenges
WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 2, June 2026.Overview of key research challenges in forest disturbance monitoring, including the detection of disturbances of varying severity, the attribution of disturbance agents, and the development of models capable of generalizing across regions. ABSTRACT Climate change and land use pressures are intensifying forest disturbances in many world regions, as ...
Carolina Natel +3 more
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Journal of Geophysical Research: Solid Earth, Volume 131, Issue 6, June 2026.Abstract The physical mechanisms that govern the multi‐scale source properties of earthquakes, such as fracture energy scaling, where the dynamic energy dissipation of earthquakes scales with fault slip, remain debatable. We introduced the rate‐ and roughness‐dependent friction (RRF) law which accounts for the multi‐scale roughness evolution of the ...
Reiju Norisugi, Hiroyuki Noda
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Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 3, June 2026.Abstract Rainfall nowcasting, the short‐term prediction of precipitation, is a vital component of early warning systems aimed at mitigating the effects of extreme weather events. In this study, we develop a deep learning approach based on convolutional neural networks (CNNs) for rainfall nowcasting and train it exclusively on data from rain gauge ...
Fereshteh Taromideh +4 more
wiley +1 more source
Trait coevolution and causal inference using generalized dynamic phylogenetic models
Methods in Ecology and Evolution, Volume 17, Issue 6, Page 1818-1836, June 2026.Abstract Phylogenetic comparative methods are widely used to study trait coevolution across biological and cultural domains. The most common methods are phylogenetic generalized linear (mixed) models, phylogenetic path analysis, Pagel's ‘discrete’ method and Ornstein–Uhlenbeck models. While some frameworks like generalized linear mixed models are quite
Erik J. Ringen +3 more
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Adaptive Weighted Total Variation Penalty for Precise Change Point Detection
Australian &New Zealand Journal of Statistics, Volume 68, Issue 2, June 2026.ABSTRACT Total variation (TV)‐based methods, such as the fused lasso, are standard for change point detection but are impaired by issues like local monotonicity. To address these limitations, this study comparatively analyses the fused lasso with two alternative methodologies.
Dong‐Young Lee +2 more
wiley +1 more source
Expert Systems, Volume 43, Issue 6, June 2026.ABSTRACT Ultra‐short pulse (USP) laser micromachining is a key technology for sustainable manufacturing, offering high precision and minimal thermal damage across a wide range of materials. To enable its effective deployment in industrial environments, it is essential to develop monitoring systems capable of accurately predicting surface roughness at ...
Miguel Camacho‐Sánchez +6 more
wiley +1 more source
The development of dissolved oxygen forecast model using hybrid machine learning algorithm with hydro-meteorological variables. [PDF]
Environ Sci Pollut Res Int, 2023 Ahmed AAM +4 more
europepmc +1 more source