Results 121 to 130 of about 83,537 (273)

Imputación de datos en diseños switchback usando un modelo mixto con errores correlacionados Data Imputation in Switchback Designs Using a Mixed Model with Correlated Errors

Revista Colombiana de Estadística, 2006
Se trata el problema de imputar mediciones individuales en datos provenientes de diseños switchback con errores correlacionados, teniendo en cuenta la propuesta de Barroso et al.
LUIS FERNANDO GRAJALES, LUIS ALBERTO LÓPEZ   +1 more
doaj  

Imputation of genetic composition for missing pedigree data in Serrasalmidae using morphometric data

Scientia Agricola
This study aimed to impute the genetic makeup of individual fishes of Serrasalmidae family on the basis of body weight and morphometric measurements. Eighty-three juveniles, belonging to the genetic groups Pacu, Pirapitinga, Tambaqui, Tambacu, Tambatinga,
Adriano Carvalho Costa, Marcio Balestre, Hortência Aparecida Botelho, Rilke Tadeu Fonseca de Freitas, Richardson Cesar da Silva Gomes, Sérgio Augusto de Sousa Campos, Fábio Porto Foresti, Diogo Teruo Hashimoto, Diego Galetti Martins, Fernanda Dotti do Prado, Maria Andreia Corrêa Mendonça   +10 more
doaj   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Bootstrap Approximation to Prediction MSE for State-Space Models with Estimated Parameters

, 2004
We propose a simple but general bootstrap method for estimating the Prediction Mean Square Error (PMSE) of the state vector predictors when the unknown model parameters are estimated from the observed series.
Pfeffermann, Danny, Tiller, Richard
core  

Interpretable Machine Learning for Bandgap Prediction and Descriptor‐Guided Design Rules of Phosphates

Advanced Intelligent Discovery, EarlyView.
An explainable CatBoost model was trained to predict the bandgaps of 474 phosphate crystals based on composition and density descriptors. SHAP analysis identified two key variables—d‐electron‐count dispersion and atomic‐density dispersion—as the primary drivers of the model's predictions.
Wenhu Wang, Abudukadi Tudi, Ran An, Zhihua Yang   +3 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

On Theil's Errors [PDF]

We take a fresh look at Theil's BLUS residuals and ask why they have gone out of fashion.All our simulation experiments indicate that tests based on BLUS residuals have higher power than those based on the more popular recursive residuals, even in those ...
Magnus, J.R., Sinha, A.K.
core   +1 more source

Digital Surface‐Enhanced Raman Scattering With Event Counting and Spectrum Learning for Label‐Free Protein Quantification

Advanced Intelligent Systems, EarlyView.
A statistical and machine learning‐assisted surface‐enhanced Raman scattering (SERS) framework is developed for label‐free quantification of low‐abundance analytes, including proteins. Combining digital SERS event counting with binomial regression and an artificial neural network (ANN) trained on full spectra, the approach achieves picomolar detection ...
Eni Kume, James Rice
wiley   +1 more source

Profiling Co‐Occurrent Morphological Phenotypes and Their Degree of Expression Severity in Vacuolated Cells by Holo‐Tomographic Flow Cytometry and Fractal Analysis

Advanced Intelligent Systems, EarlyView.
HTFC gets 3D refractive index tomograms of flowing cells. Label‐free monocytes are engineered to express patterns of cytoplasmic vacuoles. From the tomogram, an efficient dimensionality reduction is operated. Interpretable features are extracted to classify the expression severity of phenotypes coexisting in each cell, visually represented by a seven ...
Marika Valentino, Giusy Giugliano, Daniele Pirone, Fabrizio Licitra, Fulvia Vitale, Pasquale Memmolo, Lisa Miccio, Massimo D’Agostino, Pietro Ferraro, Vittorio Bianco   +9 more
wiley   +1 more source

Expected Improvement in Efficient Global Optimization Through Bootstrapped Kriging - Replaces CentER DP 2010-62 [PDF]

This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output ...
Beers, W.C.M. van, Kleijnen, Jack P.C., Nieuwenhuyse, I. van   +2 more
core   +1 more source