Robust heavy-tailed versions of generalized linear models with applications in actuarial science

Cites Work

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Bayesian heavy-tailed models and conflict resolution: a review
Full robustness in Bayesian modelling of a scale parameter
Adaptively truncated maximum likelihood regression with asymmetric errors.
Robust regression: Asymptotics, conjectures and Monte Carlo
Theoretical properties of Bayesian Student-\(t\) linear regression
Log-regularly varying scale mixture of normals for robust regression
A new Bayesian approach to robustness against outliers in linear regression
Informed reversible jump algorithms
Bayesian robustness to outliers in linear regression and ratio estimation
Robustness to outliers in location-scale parameter model using log-regularly varying distributions
Bayesian Robustness Modelling of Location and Scale Parameters
Posterior expectations for large observations
Rejection of Outliers
The Wilson-Hilferty transformation is locally saddlepoint
Robust Inference for Generalized Linear Models
Conditionally Unbiased Bounded-Influence Estimation in General Regression Models, with Applications to Generalized Linear Models
The Fitting of Power Series, Meaning Polynomials, Illustrated on Band-Spectroscopic Data
A mixture-based approach to robust analysis of generalised linear models
Nonreversible Jump Algorithms for Bayesian Nested Model Selection
A General Framework for Updating Belief Distributions
Robust Estimation of a Location Parameter
A Useful Convergence Theorem for Probability Distributions
An automatic robust Bayesian approach to principal component regression
An asymptotic Peskun ordering and its application to lifted samplers
Robustness against conflicting prior information in regression

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