Dependent Risk Models with Bivariate Phase-type Distributions
نویسندگان
چکیده
In this paper we consider an extension of the Sparre Andersen insurance risk model by relaxing one of its independence assumptions. The newly proposed dependence structure is introduced through the premise that the joint distribution of the interclaim time and the subsequent claim size is bivariate phase-type (see, e.g. Assaf et al. (1984) and Kulkarni (1989)). Relying on the existing connection between risk processes and fluid flows (see, e.g. Badescu et al. (2005), Badescu, Drekic and Landriault (2007), Ramaswami (2006), and Ahn, Badescu and Ramaswami (2007)), we construct an analytically tractable fluid flow that leads to the analysis of various ruin-related quantities in the aforementioned risk model. Using matrix-analytic methods, we obtain an explicit expression for the Gerber–Shiu discounted penalty function (see Gerber and Shiu (1998)) when the penalty function depends on the deficit at ruin only. Finally, we investigate how some ruin-related quantities involving the surplus immediately prior to ruin can also be analyzed via our fluid flow methodology.
منابع مشابه
Asymmetric Univariate and Bivariate Laplace and Generalized Laplace Distributions
Alternative specifications of univariate asymmetric Laplace models are described and investigated. A more general mixture model is then introduced. Bivariate extensions of these models are discussed in some detail, with particular emphasis on associated parameter estimation strategies. Multivariate versions of the models are briefly introduced.
متن کاملA Note on the Bivariate Maximum Entropy Modeling
Let X=(X1 ,X2 ) be a continuous random vector. Under the assumption that the marginal distributions of X1 and X2 are given, we develop models for vector X when there is partial information about the dependence structure between X1 and X2. The models which are obtained based on well-known Principle of Maximum Entropy are called the maximum entropy (ME) mo...
متن کاملOn the construction of bivariate exponential distributions with an arbitrary correlation coefficient
In this paper we use a concept of multivariate phase–type distributions to define a class of bivariate exponential distributions. This class has the following three appealing properties. Firstly, we may construct a pair of exponentially distributed random variables with any feasible correlation coefficient (also negative). Secondly, the class satisfies that any linear combination (projection) o...
متن کاملEM algorithm for bivariate phase distributions
In this paper, we descibe the general construction of multivariate phase-type distributions of discret or continuous type and study their commun distributions and densities on lower dimensional subspaces. Finally, we adopt the known EM algorithm for approximating bivariate phase distributions to a set of two-dimensional observations.
متن کاملBivariate Semi-Logistic Distribution and Processes
Bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions are introduced. Some properties of these distributions are studied. First order autoregressive processes with bivariate semi-logistic and Marshall-Olkin bivariate semi-logistic distributions as marginals are introduced and studied.
متن کامل