Results 11 to 20 of about 77,552 (290)
Identifying the sources of model misspecification [PDF]
Journal of Monetary Economics, 2020 The first and third authors acknowledge financial support from the National Science Foundation through grants 102159 and 1022125, respectively.
Atsushi Inoue +2 more
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Estimation Under Model Misspecification With Fake Features
IEEE Transactions on Signal Processing, 2023 We consider estimation under model misspecification where there is a model mismatch between the underlying system, which generates the data, and the model used during estimation. We propose a model misspecification framework which enables a joint treatment of the model misspecification types of having fake features as well as incorrect covariance ...
Martin Hellkvist +2 more
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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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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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Statistical Modelling, 2008 A common problem in statistical modelling is to distinguish between finite mixture distribution and a homogeneous non-mixture distribution. Finite mixture models are widely used in practice and often mixtures of normal densities are indistinguishable from homogenous non-normal densities.
Tarpey, Thaddeus +2 more
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Model Misspecification as the Causes of Flypaper Effect
Proceedings, 2023 The aim of this paper is to investigate the relationship between the Fly-paper effect (FPE) and possible errors in the specification of econometric models used in the empirical analysis of FPE.
Siniša Mali
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Measuring Model Misspecification: Application to Propensity Score Methods with Complex Survey Data. [PDF]
Comput Stat Data Anal, 2018 Lenis D, Ackerman B, Stuart EA.
europepmc +2 more sources
Mathematics, 2021 In optimal experimental design theory it is usually assumed that the response variable follows a normal distribution with constant variance. However, some works assume other probability distributions based on additional information or practitioner’s ...
Sergio Pozuelo-Campos +2 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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Minimizing sensitivity to model misspecification [PDF]
Quantitative Economics, 2018 We propose a framework for estimation and inference when the model may be misspecified. We rely on a local asymptotic approach where the degree of misspecification is indexed by the sample size. We construct estimators whose mean squared error is minimax in a neighborhood of the reference model, based on one‐step adjustments.
Weidner, Martin, Bonhomme, Stéphane
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