Results 71 to 80 of about 16,361 (164)
Minimum Penalized ϕ-Divergence Estimation under Model Misspecification
Entropy, 2018 This paper focuses on the consequences of assuming a wrong model for multinomial data when using minimum penalized ϕ -divergence, also known as minimum penalized disparity estimators, to estimate the model parameters.
M. Virtudes Alba-Fernández +2 more
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Complexity and Misspecification
We propose a tractable model of repeated decision problems that combines concern about model misspecification, as in robust control, with a complexity cost, such as Shannon entropy, that makes pessimistic beliefs trade off statistical plausibility against simplicity. In a static setting, stronger complexity aversion selects more concentrated worst-case
Fudenberg, Drew, Mudekereza, Florian
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Robust Portfolio Optimization with Environmental, Social, and Corporate Governance Preference
RisksThis study addresses the crucial but under-explored topic of ambiguity aversion, i.e., model misspecification, in the area of environmental, social, and corporate governance (ESG) within portfolio decisions.
Marcos Escobar-Anel, Yiyao Jiao
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Uncertainty quantification for misspecified machine learned interatomic potentials
npj Computational MaterialsThe use of high-dimensional regression techniques from machine learning has significantly improved the quantitative accuracy of interatomic potentials. Atomic simulations can now plausibly target quantitative predictions in a variety of settings, which ...
Danny Perez +3 more
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Newsvendor under Ambiguity and Misspecification
Manufacturing & Service Operations ManagementWe consider a newsvendor problem with unknown demand distribution, where we distinguish ambiguity under which the newsvendor does not differentiate demand distributions of common characteristics (e.g., mean and variance) and misspecification under which such characteristics might be misspecified (due to, e.g., estimation error and/or distribution shift)
Feng Liu +3 more
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Acta Universitatis Lodziensis. Folia Oeconomica, 2014 The aim of this paper is to evaluate the spatial and hierarchical models for data generating processes with spatial heterogeneity and spatial dependence at the higher level.
Edyta Łaszkiewicz
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BMC Medical Research MethodologyBackground In multi-site studies in clinical practice, the treatment effects may exhibit potential heterogeneity across different sites. Additionally, propensity score methods used to adjust for confounding may suffer from model misspecification, which ...
Chen Huang +3 more
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Nature Communications, 2018 Standard approaches for heritability and set testing in statistical genetics rely on parametric models that might not hold in reality and give inflated p-values.
Regev Schweiger +9 more
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Investigating item complexity as a source of cross-national DIF in TIMSS math and science
Large-scale Assessments in EducationBackground Large scale international assessments depend on invariance of measurement across countries. An important consideration when observing cross-national differential item functioning (DIF) is whether the DIF actually reflects a source of bias, or ...
Qi Huang, Daniel M. Bolt, Weicong Lyu
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DSGE Estimation Using Generalized Empirical Likelihood and Generalized Minimum Contrast
EntropyWe investigate the performance of estimators of the generalized empirical likelihood and minimum contrast families in the estimation of dynamic stochastic general equilibrium models, with particular attention to the robustness properties under ...
Gilberto Boaretto +1 more
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