Results 41 to 50 of about 18,342 (121)

On the Foundational Arguments of Sufficient Dimension Reduction

open access: yesWIREs Computational Statistics, Volume 18, Issue 2, June 2026.
Contemporary Sufficient Dimension Reduction, a versatile method for extracting material information from data, can serve as a preprocessor for classical modeling and inference, or as a standalone theory that leads directly to statistical inference. ABSTRACT Sufficient dimension reduction (SDR) refers to supervised methods of dimension reduction that ...
R. Dennis Cook
wiley   +1 more source

Machine Learning‐Based Air Temperature Prediction for Homa Bay County in Kenya: Implications for Weather‐Sensitive Sector Resilience

open access: yesMeteorological Applications, Volume 33, Issue 3, May/June 2026.
Machine learning models, particularly random forest, demonstrate strong potential for localized temperature prediction in climatically complex regions, achieving high accuracy (R2 ≈ 0.91). Relative humidity (r = −0.92) and solar irradiance (r = 0.79) emerge as predictors, offering valuable insights for climate‐informed agricultural and water resource ...
Hellen Omiti   +4 more
wiley   +1 more source

A Machine Learning Parameterization for the Internal Gravity Wave Spectrum

open access: yesJournal of Geophysical Research: Oceans, Volume 131, Issue 5, May 2026.
Abstract We introduce a stochastic model designed to parametrize the spectral properties of internal waves, using two functions that represent the semidiurnal spectral tidal cusps and the energy continuum between the inertial and the buoyancy frequencies.
Yutao Zheng   +3 more
wiley   +1 more source

Machine Learning and Artificial Intelligence Techniques for Intelligent Control and Forecasting in Energy Storage‐Based Power Systems

open access: yesEnergy Science &Engineering, Volume 14, Issue 4, Page 2318-2344, April 2026.
A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan   +4 more
wiley   +1 more source

Powering RCTs for Marginal Effects With GLMs Using Prognostic Score Adjustment

open access: yesStatistics in Medicine, Volume 45, Issue 8-9, April 2026.
ABSTRACT In randomized clinical trials (RCTs), the accurate estimation of marginal treatment effects is crucial for determining the efficacy of interventions. Enhancing the statistical power of these analyses is a key objective for statisticians. The increasing availability of historical data from registries, prior trials, and health records presents ...
Emilie Højbjerre‐Frandsen   +2 more
wiley   +1 more source

A Data‐Driven Multidimensional Profiling Framework for Residential Electricity Users With Application to Load Forecasting

open access: yesEnergy Internet, Volume 3, Issue 1, Page 23-38, April 2026.
ABSTRACT With the advancement of smart grid and Internet of Things, alongside broad adoption of distributed energy resources, precise profiling of residential users has become vital to grid operational efficiency and load forecasting accuracy. However, existing profiling approaches mainly rely on single‐source load data and fail to capture the dynamic ...
Danlin Li   +6 more
wiley   +1 more source

Mammal Responses to Habitat Degradation Induced by Cashew Expansion in West Africa

open access: yesAnimal Conservation, Volume 29, Issue 2, Page 169-182, April 2026.
Relationships between (a) estimated mammal species richness, (b) overall mammal species photographic rate, (c) carnivore photographic rate, (d) insectivore photographic rate, (e) omnivore photographic rate and (f) herbivore photographic rate and the local habitat characteristics as denoted by the scores of the first component of the Principal Component
Daniel Na Mone   +6 more
wiley   +1 more source

Statistical Testing of Optimality Conditions in Multiresponse Simulation-based Optimization (Revision of 2005-81) [PDF]

open access: yes
This paper studies simulation-based optimization with multiple outputs. It assumes that the simulation model has one random objective function and must satisfy given constraints on the other random outputs.
Bettonvil, B.W.M.   +2 more
core   +1 more source

A Sharper Computational Tool for L2E Regression. [PDF]

open access: yesTechnometrics, 2023
Liu X, Chi EC, Lange K.
europepmc   +1 more source

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