Results 81 to 90 of about 7,836,569 (290)
Analytic and bootstrap approximations of prediction errors under a multivariate fay-herriot model [PDF]
, 2005 A Multivariate Fay-Herriot model is used to aid the prediction of small area parameters of dependent variables with sample data aggregated to area level.
Morales, Domingo +4 more
core +1 more source
Induced Ranked Set Sampling when Units are Inducted from Several Populations
Statistica, 2018 The method of ranked set sampling when units are to be inducted from several bivariate populations is introduced in this work. The best linear unbiased estimation of a common parameter of two bivariate Pareto distributions is discussed based on the n ...
P. Yageen Thomas, Anne Philip
doaj +1 more source
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
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
"Mixed Effects Prediction under Benchmarking and Applications to Small Area Estimation" [PDF]
The empirical best linear unbiased predictor (EBLUP) in the linear mixed model (LMM) is useful for the small area estimation in the sense of increasing the precision of estimation of small area means.
Tatsuya Kubokawa
core
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
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
Prediction of a Small Area Mean for an Infinite Population when the Variance Components Are Random [PDF]
In this paper, we propose a new model with random variance components for estimating small area characteristics. Under the proposed model, we derive the empirical best linear unbiased estimator, an approximation to terms of order and an estimator whose ...
Stefan, Marius
core
American Journal of Agricultural Economics, EarlyView.Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman +1 more
wiley +1 more source
Improving access to new technologies: An experiment with Kenyan input sellers
American Journal of Agricultural Economics, EarlyView.Abstract Agrodealers play a critical role in rural economies, selling essential inputs for agricultural production, stocking new products, and providing farmers with technical advice. However, uncertainty can discourage them from stocking newer, less familiar products, limiting the availability of innovative technologies and leading to market failures ...
Sarah W. Kariuki +6 more
wiley +1 more source