Results 111 to 120 of about 29,799 (296)
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
doaj +1 more source
Vine copula knockoffs for variable selection in gene expression studies
Canadian Journal of Statistics, EarlyView.Abstract Identifying clinical and genetic markers is essential for stratifying cancer patients by survival outcomes and guiding personalized treatment strategies. However, gene expression studies often involve high‐dimensional predictors with mixed data types and complex dependence, which complicates reliable variable selection.
José Ulises Márquez Urbina +3 more
wiley +1 more source
On the Model-Misspecification in Reinforcement Learning [PDF]
The success of reinforcement learning (RL) crucially depends on effective function approximation when dealing with complex ground-truth models. Existing sample-efficient RL algorithms primarily employ three approaches to function approximation: policy ...
Yang, Lin, Li, Yunfan
core +1 more source
Sparse maximum likelihood estimation of regression models
Canadian Journal of Statistics, EarlyView.Abstract For regression model selection and estimation, we study a small set of candidate models of maximum likelihood from which all information criteria such as the Akaike information criterion (AIC) and the Bayesian information criterion (BIC) choose their models.
Min Tsao
wiley +1 more source
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
doaj +1 more source
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
openaire +2 more sources
Market selection and learning under model misspecification
, 2023 This paper studies market selection in an Arrow-Debreu economy with complete markets where agents learn over misspecified models. Under model misspecification, standard Bayesian learning loses its formal justification and biased learning processes may ...
Bottazzi, Giulio +2 more
core
Mitigating measurement error in misspecified small area models
Canadian Journal of Statistics, EarlyView.Abstract In the framework of Small area estimation, we consider an area‐level model where a subset of covariates is measured with error. The extent of the error is assumed to be constant throughout the areas, and it is expressed by a scalar parameter γ$$ \gamma $$, which multiplies the deterministic covariance matrix of the estimator of the true ...
Diego Battagliese +3 more
wiley +1 more source
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
doaj +1 more source
Canadian Journal of Statistics, EarlyView.Abstract Irregular observation times are common in longitudinal observational studies and can affect causal inferences. We use data from electronic health records of Kaiser Permanente Washington patients in the United States who initiated an antidepressant medication between 2008 and 2018, with a confirming diagnosis of depression. We are interested in
Janie Coulombe +2 more
wiley +1 more source