Add to ORKGThe problems of robustness in Bayesian forecasting are considered under distortions of the hypothetical probability densities. The expressions for the guaranteed upper risk functional are obtained and the robust prediction statistics under certain types of distortions are constructed
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...
A common concern with Bayesian analysis is uncertainty in specification of the prior distribution. T...
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...
The problems of robustness in Bayesian forecasting are considered under distortions of the hypothet...
The paper is devoted the problem of robust forecasting for the beta-mixed hierarchical models of gro...
This paper presents a new asymptotic approach to study the robustness of Bayesian inference to chang...
In order to deal with mild deviations from the assumed parametric model, we propose a procedure for ...
Two concepts of optimality corresponding to Bayesian robust analysis are considered: conditional Γ-m...
Robustness has always been an important element of the foundation of Statistics. However, it has onl...
This paper derives a formula for the optimal forecast of a discounted sum of future values of a rand...
The concentration function, extending the classical notion of Lorenz curve, is well suited for compa...
In Chapter 2, the robustness of Bayes analysis with reference to conjugate prior classes is discusse...
The first part of the thesis concerns itself with Bayesian nonparametrics. We consider the problem o...
Bayesian predictive methods have a number of advantages over traditional statistical methods. For o...
This paper considers a new class \Gamma specified under uncertainty on the relative weights of some ...
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...
A common concern with Bayesian analysis is uncertainty in specification of the prior distribution. T...
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...
The problems of robustness in Bayesian forecasting are considered under distortions of the hypothet...
The paper is devoted the problem of robust forecasting for the beta-mixed hierarchical models of gro...
This paper presents a new asymptotic approach to study the robustness of Bayesian inference to chang...
In order to deal with mild deviations from the assumed parametric model, we propose a procedure for ...
Two concepts of optimality corresponding to Bayesian robust analysis are considered: conditional Γ-m...
Robustness has always been an important element of the foundation of Statistics. However, it has onl...
This paper derives a formula for the optimal forecast of a discounted sum of future values of a rand...
The concentration function, extending the classical notion of Lorenz curve, is well suited for compa...
In Chapter 2, the robustness of Bayes analysis with reference to conjugate prior classes is discusse...
The first part of the thesis concerns itself with Bayesian nonparametrics. We consider the problem o...
Bayesian predictive methods have a number of advantages over traditional statistical methods. For o...
This paper considers a new class \Gamma specified under uncertainty on the relative weights of some ...
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...
A common concern with Bayesian analysis is uncertainty in specification of the prior distribution. T...
The extrapolation of extremes to values beyond the span of stationary univariate historical data is ...