LAUSR

Dealing with data conflicts in statistical inference of population assessment models that integrate information from multiple diverse data sets

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0 Published in 2017 at "Fisheries Research"

DOI: 10.1016/j.fishres.2016.04.022

Abstract: Abstract Contemporary fisheries stock assessments often use multiple diverse data sets to extract as much information as possible about biological and fishery processes. However, models are, by definition, simplifications of reality and, therefore, misspecified. Model… read more here.

Keywords: data sets; model misspecification; misspecification; multiple diverse ... See more keywords

Quantification of model risk that is caused by model misspecification

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0 Published in 2020 at "Journal of Applied Statistics"

DOI: 10.1080/02664763.2020.1849055

Abstract: In this paper, we suggest a technique to quantify model risk, particularly model misspecification for binary response regression problems found in financial risk management, such as in credit risk ... read more here.

Keywords: quantification model; risk; model misspecification; model ... See more keywords

Model misspecification, Bayesian versus credibility estimation, and Gibbs posteriors

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0 Published in 2020 at "Scandinavian Actuarial Journal"

DOI: 10.1080/03461238.2019.1711154

Abstract: ABSTRACT In the context of predicting future claims, a fully Bayesian analysis – one that specifies a statistical model, prior distribution, and updates using Bayes's formula – is often viewed as the gold-standard, while Bühlmann's… read more here.

Keywords: model misspecification; credibility; misspecification; gibbs ... See more keywords

Measuring Phylogenetic Information of Incomplete Sequence Data.

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0 Published in 2021 at "Systematic biology"

DOI: 10.1093/sysbio/syab073

Abstract: Widely used approaches for extracting phylogenetic information from aligned sets of molecular sequences rely upon probabilistic models of nucleotide substitution or amino-acid replacement. The phylogenetic information that can be extracted depends on the number of… read more here.

Keywords: information; model misspecification; measuring phylogenetic; sequence alignment ... See more keywords

Model misspecification misleads inference of the spatial dynamics of disease outbreaks

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1 Published in 2022 at "Proceedings of the National Academy of Sciences of the United States of America"

DOI: 10.1101/2022.08.24.22278802

Abstract: Epidemiology has been transformed by the advent of Bayesian phylodynamic models that allow researchers to infer the geographic history of pathogen dispersal over a set of discrete geographic areas (Lemey et al., 2009; Edwards et… read more here.

Keywords: spatial dynamics; misspecification misleads; model misspecification; dynamics disease ... See more keywords

Estimation Under Model Misspecification With Fake Features

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1 Published in 2022 at "IEEE Transactions on Signal Processing"

DOI: 10.1109/tsp.2023.3237174

Abstract: 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… read more here.

Keywords: fake features; estimation model; model misspecification; model ... See more keywords

Statistical methods for incomplete data: Some results on model misspecification

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0 Published in 2017 at "Statistical Methods in Medical Research"

DOI: 10.1177/0962280214544251

Abstract: Inverse probability weighted estimating equations and multiple imputation are two of the most studied frameworks for dealing with incomplete data in clinical and epidemiological research. We examine the limiting behaviour of estimators arising from inverse… read more here.

Keywords: probability weighted; inverse probability; probability; model misspecification ... See more keywords

Structural Panel Bayesian VAR Model to Deal with Model Misspecification and Unobserved Heterogeneity Problems

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0 Published in 2019 at "Econometrics"

DOI: 10.3390/econometrics7010008

Abstract: This paper provides an overview of a time-varying Structural Panel Bayesian Vector Autoregression model that deals with model misspecification and unobserved heterogeneity problems in applied macroeconomic analyses when studying time-varying relationships and dynamic interdependencies among… read more here.

Keywords: model misspecification; unobserved heterogeneity; model; structural panel ... See more keywords