Results 21 to 30 of about 24,401 (306)
Adapting to Misspecification in Contextual Bandits
CoRR, 2021 Appeared at NeurIPS ...
Dylan J. Foster +3 more
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An improved multiply robust estimator for the average treatment effect
BMC Medical Research Methodology, 2023 Background In observational studies, double robust or multiply robust (MR) approaches provide more protection from model misspecification than the inverse probability weighting and g-computation for estimating the average treatment effect (ATE). However,
Ce Wang +4 more
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Inference for Iterated GMM Under Misspecification
, 2021 This paper develops inference methods for the iterated overidentified Generalized Method of Moments (GMM) estimator. We provide conditions for the existence of the iterated estimator and an asymptotic distribution theory, which allows for mild ...
Hansen, BE +3 more
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Robust control and model misspecification [PDF]
Journal of Economic Theory, 2006 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lars Peter Hansen +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 +3 more
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Likelihood-based estimation and prediction for a measles outbreak in Samoa
Infectious Disease Modelling, 2023 Prediction of the progression of an infectious disease outbreak is important for planning and coordinating a response. Differential equations are often used to model an epidemic outbreak's behaviour but are challenging to parameterise. Furthermore, these
David Wu +4 more
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Interpretation and Semiparametric Efficiency in Quantile Regression under Misspecification
Econometrics, 2015 Allowing for misspecification in the linear conditional quantile function, this paper provides a new interpretation and the semiparametric efficiency bound for the quantile regression parameter β (
Ying-Ying Lee
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Structured ambiguity and model misspecification
Journal of Economic Theory, 2022 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lars Peter Hansen, Thomas J. Sargent
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An Information Criterion for Auxiliary Variable Selection in Incomplete Data Analysis
Entropy, 2019 Statistical inference is considered for variables of interest, called primary variables, when auxiliary variables are observed along with the primary variables.
Shinpei Imori, Hidetoshi Shimodaira
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Making Decisions under Model Misspecification [PDF]
SSRN Electronic Journal, 2020 Abstract We use decision theory to confront uncertainty that is sufficiently broad to incorporate “models as approximations.” We presume the existence of a featured collection of what we call “structured models” that have explicit substantive motivations.
Cerreia–Vioglio, Simone +3 more
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