Models of Alternating Renewal Process at Discrete Time

We study a class of models used with success in the modelling of climatological sequences. These models are based on the notion of renewal. At first, we examine the probabilistic aspects of these models to afterwards study the estimation of their parameters and their asymptotical properties, in particular the consistence and the normality. We will discuss for applications, two particular classes of alternating renewal processes at discrete time. The first class is defined by laws of sojourn time that are translated negative binomial laws and the second class, suggested by Green is deduced from alternating renewal process in continuous time with sojourn time laws which are exponential laws with parameters α^0 and α^1 respectively.

Оптимизация на учителския състав в училище

Silvia Baeva - In the Ministry of Education and Science’s system it has been talked about optimization of the school network; this optimization can be carried out in different directions and be supported by laws. An important aspect in the optimization of the school network is to reduce costs and increase overall efficiency in each school. We will formulate this aspect as a problem of the multicriteria decisions making and by appropriate numbers of methods and criteria it can be transformed to the problem of unicriterion optimization. This problem is separated into two stages: 1-th stage – determining the minimum number of classes in a school under certain statutory provisions for the size of each of them; 2-th stage – the appointment of a minimum number of teachers and achievement of maximal effectiveness of teaching and acquiring of knowledge and skills by students according to certain statutory provisions for teachers’ annual norms of subjects and number of hours in a particular subject area and the salaries of teachers. The achievement of maximum overall efficiency is a priority in all schools.

Geometric Stable Laws Through Series Representations

Let (Xi ) be a sequence of i.i.d. random variables, and let N be a geometric random variable independent of (Xi ). Geometric stable distributions are weak limits of (normalized) geometric compounds, SN = X1 + · · · + XN , when the mean of N converges to infinity. By an appropriate representation of the individual summands in SN we obtain series representation of the limiting geometric stable distribution. In addition, we study the asymptotic behavior of the partial sum process SN (t) = ⅀( i=1 ... [N t] ) Xi , and derive series representations of the limiting geometric stable process and the corresponding stochastic integral. We also obtain strong invariance principles for stable and geometric stable laws.

Sums of a Random Number of Random Variables and their Approximations with ν- Accompanying Infinitely Divisible Laws

* Research supported by NATO GRANT CRG 900 798 and by Humboldt Award for U.S. Scientists.

On a Second Order Condition for Max-Semistable Laws

2000 Mathematics Subject Classification: 62G32, 62G20.