Results 31 to 40 of about 15,975 (254)

Informational herding with model misspecification [PDF]

Journal of Economic Theory, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A View on Model Misspecification in Uncertainty Quantification

, 2023
An initial version of the current work has been accepted to be presented at BNAIC/BeNeLearn 2022, to which it was submitted on August 27 ...
Yuko Kato, David M. J. Tax, Marco Loog
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Robust Online Control with Model Misspecification

CoRR, 2021
We study online control of an unknown nonlinear dynamical system that is approximated by a time-invariant linear system with model misspecification. Our study focuses on robustness, a measure of how much deviation from the assumed linear approximation can be tolerated by a controller while maintaining finite $\ell_2$-gain.
Xinyi Chen 0001, Udaya Ghai, Elad Hazan, Alexandre Megretski   +3 more
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Consequences of Model Misspecification for Maximum Likelihood Estimation with Missing Data

Econometrics, 2019
Researchers are often faced with the challenge of developing statistical models with incomplete data. Exacerbating this situation is the possibility that either the researcher’s complete-data model or the model of the missing-data mechanism is ...
Richard M. Golden, Steven S. Henley, Halbert White, T. Michael Kashner   +3 more
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Accuracy of attribute estimation in the crossed random effects linear logistic test model: impact of Q-matrix misspecification

Frontiers in Education
A simulation study is designed to explore the accuracy of attribute parameter estimation in the crossed random effects linear logistic test model (CRELLTM) with the impact of Q-matrix misspecification on attribute parameter estimation using the SAS ...
Yi-Hsin Chen, Isaac Y. Li, Chunhua Cao, Yan Wang   +3 more
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Allele frequency misspecification: effect on power and Type I error of model-dependent linkage analysis of quantitative traits under random ascertainment

BMC Genetics, 2006
Background Studies of model-based linkage analysis show that trait or marker model misspecification leads to decreasing power or increasing Type I error rate.
Wilson Alexander F, Atwood Larry D, Sorant Alexa JM, Mandal Diptasri M, Bailey-Wilson Joan E   +4 more
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Power Analysis for Parameter Estimation in Structural Equation Modeling: A Discussion and Tutorial

Advances in Methods and Practices in Psychological Science, 2021
Despite the widespread and rising popularity of structural equation modeling (SEM) in psychology, there is still much confusion surrounding how to choose an appropriate sample size for SEM.
Y. Andre Wang, Mijke Rhemtulla
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On the Performance of the RESET Test Under Temporal Aggregation and Autoregressive Dynamics: Evidence from Simulation and Exchange Rate Data

Mathematics
Ramsey’s RESET test is widely used as an omnibus diagnostic for model misspecification, yet its reliability may be affected by temporal aggregation, autoregressive persistence, and the statistical properties of financial time series.
Christos Christodoulou-Volos, Elena Polydorou   +1 more
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Decision trees compensate for model misspecification

CoRR, 2023
The best-performing models in ML are not interpretable. If we can explain why they outperform, we may be able to replicate these mechanisms and obtain both interpretability and performance. One example are decision trees and their descendent gradient boosting machines (GBMs).
Hugh Panton, Gavin Leech, Laurence Aitchison   +2 more
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Human‐Guided Bayesian Optimization Enables High‐Throughput Laser Annealing of Mesoporous SiOx Anodes for Lithium‐Ion Batteries

Advanced Science, EarlyView.
An empirical‐aided active learning framework is developed to optimize high‐throughput laser‐induced photothermal annealing of silicon suboxide anodes. By integrating probabilistic machine learning with empirical domain knowledge, this approach achieves optimal electrochemical performance using limited experiments.
Chaeyoung Park, Yeongje Lee, Sunho Jeong, Eungkyu Lee   +3 more
wiley   +1 more source