The Applications of Thinning Process in Two Kinds of Multiple-Type Risk Model with Dependent Claims Number Process;

In this paper,we discussed a risk process for Two-Type-Risk Problem,where the arrival of term policies follows Two-Type poisson processes and the arrival of the claims follows a p-thinning processes and q-thinning processes.

In this paper we consider a continuous time doubletype-insurance risk model with thinning process,where the premium income process and the arrival of the claims are different, one of the premium income process is a linear function of time t,another follows a Poisson process;one of the arrival of the claims is compound Poisson process,another is a thinning process.

Aiming at the problem of data sparsity for collaborative filtering,a novel rough set-based collaborative filtering algorithm is proposed.

With the in-depth study, however, appearing sparse data imaging, which traditional methods can not used to reconstruct a clear image.

This paper focuses on the sparse data interpolation which is based on Kriging method,and an improved method named Regression Kriging method is derivated.

The key problem in N-gram method is the problem of sparse data which still can not be solved effectively now.

Based on N-gram models, this paper proposes a three-step method of "word-similar word-part of speech" by incorporating the similar words and solves the problem of sparse data to a large extent.

We consider a risk model with dependent two classes,where the claim number process of the first class is Erlang(2) process,and the second is its p-thinning process.