Results 101 to 110 of about 6,446,441 (278)
Uncertainty under a multivariate nested-error regression model with logarithmic transformation [PDF]
, 2006 Assuming a multivariate linear regression model with one random factor, we consider the parameters defined as exponentials of mixed effects, i.e., linear combinations of fixed and random effects.
Molina, Isabel
core +1 more source
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 +1 more
wiley +1 more source
BEST LINEAR UNBIASED SCALAR (BLUS) RESIDUAL PADA REGRESI LINIER BERGANDA [PDF]
, 2001 THIS PAPER CONTAINS ABOUT HOW TO USED OF BEST LINEAR UNBIASED SCALED (BLUS) METHOD, WHICH MAKES UNCORRELATED TO MULTIPLE LINEAR ...
RENNY ANGGRAENI, 089511307
core +3 more sources
Quantitative Methods in Economics, 2009 In the paper the results of small area estimation using empiricalbest linear unbiased predictor (EBLUP) for the data coming from PolishHousehold Budget Survey are presented.
Alina Jędrzejczak, Jan Kubacki
doaj
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 +3 more
wiley +1 more source
Discrete-Time Linear Filtering in Arbitrary Noise
, 2008 The Kalman filter is a recursive Best Linear Unbiased Estimator (BLUE) for a linear dynamic system with uncorrelated white process and measurement noises.
Rong Li University +2 more
core
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 +4 more
wiley +1 more source
Bootstrap for estimating the mean squared error of the spatial EBLUP [PDF]
This work assumes that the small area quantities of interest follow a Fay-Herriot model with spatially correlated random area effects. Under this model, parametric and nonparametric bootstrap procedures are proposed for estimating the mean squared error ...
Isabel Molina +2 more
core
Accelerating Materials Discovery: A Review of Machine Learning in X‐Ray Absorption Spectroscopy
Advanced Intelligent Systems, EarlyView.This review systematically details how machine learning transforms X‐ray absorption spectroscopy (XAS) analysis. It covers advanced deep learning architectures for structure‐spectra mapping and inverse tasks, while discussing key challenges like the simulation‐to‐reality gap.
Melaku Lake Tegegne +5 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.An integrated OT‐2/plate reader platform automates LCST cloud point measurement of NIPAM‐co‐DMAEMA copolymers across high‐dimensional formulation spaces. Machine learning trained on the resulting high‐throughput datasets achieves R2 up to 0.96 and enables inverse design of polymer formulations to target transition temperatures with <1% error.
Lachlan Alexander +2 more
wiley +1 more source