"Z i i r i ch ' " Vers icherungs-Gese l l schafL Zt'irich In practical applications of Credibility Theory the structure parameters usually have to be estimated from the data. This leads to an estimator of the a posteriori mean which is often biased and where the credibility factor depends on the data. A more coherent approach to the problem would be to also treat the unknown parameters as random variables and to simultaneously estimate the a posteriori mean and the structure parameters. Different statistical models are proposed which allow for such a solution. These models all lead to an estimation of the posterior mean which is a weighted average of the prior mean and of the observed mean, the weight
Credibility theory is an experience rating technique in insurance used to combine an estimate of the...
The work deals with estimation of unknown risk parameters of a driver. Risk parameter indicates how ...
This paper introduces nonparametric Bayesian credibility without imposing stringent parametric assum...
In practical applications of Credibility Theory the structure parameters usually have to be estimate...
Credibility theory in insurance is essentially a form of experience-rating that attempts to use the ...
summary:This paper presents and analyzes the estimators of the structural parameters, in the Bühlman...
This thesis is about insurance models and aspects of uncertainty pertaining to such models. The mode...
In this article we give the mathematical theory of some credibility models. The first section descri...
One of the most important techniques used in general insurance pricing is the credibility ratemaking...
In this paper it is shown that the estimate and prediction problems considered in credibility theory...
There are various formulations for the randomly varying behavior of regression coefficients, which c...
In the minds of most statisticians there are (at least) two mutually exclusive approaches to data an...
Credibility theory is widely used in insurance. It is included in the examination of the Society of ...
We propose a Bayesian analysis to develop credibility estimates of the well known Biihlmann-Straub m...
Some of the structure parameters in Jewell’s hierarchical credi-bility model are commonly estimated ...
Credibility theory is an experience rating technique in insurance used to combine an estimate of the...
The work deals with estimation of unknown risk parameters of a driver. Risk parameter indicates how ...
This paper introduces nonparametric Bayesian credibility without imposing stringent parametric assum...
In practical applications of Credibility Theory the structure parameters usually have to be estimate...
Credibility theory in insurance is essentially a form of experience-rating that attempts to use the ...
summary:This paper presents and analyzes the estimators of the structural parameters, in the Bühlman...
This thesis is about insurance models and aspects of uncertainty pertaining to such models. The mode...
In this article we give the mathematical theory of some credibility models. The first section descri...
One of the most important techniques used in general insurance pricing is the credibility ratemaking...
In this paper it is shown that the estimate and prediction problems considered in credibility theory...
There are various formulations for the randomly varying behavior of regression coefficients, which c...
In the minds of most statisticians there are (at least) two mutually exclusive approaches to data an...
Credibility theory is widely used in insurance. It is included in the examination of the Society of ...
We propose a Bayesian analysis to develop credibility estimates of the well known Biihlmann-Straub m...
Some of the structure parameters in Jewell’s hierarchical credi-bility model are commonly estimated ...
Credibility theory is an experience rating technique in insurance used to combine an estimate of the...
The work deals with estimation of unknown risk parameters of a driver. Risk parameter indicates how ...
This paper introduces nonparametric Bayesian credibility without imposing stringent parametric assum...