Several authors have studied the uniform estimate for the tail probabilities of randomly weighted sums sum from i=1 to ∞(1/i) and their maxima.In this paper,we generalize their work to the situation that {X_i,i ≥ 1}is a sequence of upper tail asymptotically independent random variables with common distribution from the class D∩L,and {θ_i,i ≥ 1} is a sequence of nonnegative random variables,independent of {X_i,i ≥ 1} and satisfying some regular conditions.Moreover,no additional assumption is required on the dependence structure of {θ_i,i≥ 1}.
Abstract This paper deals with a discrete-time batch arrival retrial queue with the server subject to starting failures.Diferent from standard batch arrival retrial queues with starting failures,we assume that each customer after service either immediately returns to the orbit for another service with probabilityθor leaves the system forever with probability 1θ(0≤θ<1).On the other hand,if the server is started unsuccessfully by a customer(external or repeated),the server is sent to repair immediately and the customer either joins the orbit with probability q or leaves the system forever with probability 1 q(0≤q<1).Firstly,we introduce an embedded Markov chain and obtain the necessary and sufcient condition for ergodicity of this embedded Markov chain.Secondly,we derive the steady-state joint distribution of the server state and the number of customers in the system/orbit at arbitrary time.We also derive a stochastic decomposition law.In the special case of individual arrivals,we develop recursive formulae for calculating the steady-state distribution of the orbit size.Besides,we investigate the relation between our discrete-time system and its continuous counterpart.Finally,some numerical examples show the influence of the parameters on the mean orbit size.
Consider the optimal dividend problem for an insurance company whose uncontrolled surplus precess evolves as a spectrally negative Lvy process. We assume that dividends are paid to the shareholders according to admissible strategies whose dividend rate is bounded by a constant. The objective is to find a dividend policy so as to maximize the expected discounted value of dividends which are paid to the shareholders until the company is ruined. In this paper, we show that a threshold strategy(also called refraction strategy)forms an optimal strategy under the condition that the Lvy measure has a completely monotone density.
A risk model with Markovian arrivals and tax payments is considered.When the insurer is in a profitable situation,the insurer may pay a certain proportion of the premium income as tax payments.First,the Laplace transform of the time to cross a certain level before ruin is discussed.Second,explicit formulas for a generalized Gerber-Shiu function are established in terms of the'original'Gerber-Shiu function without tax and the Laplace transform of the first passage time before ruin.Finally,the differential equations satisfied by the expected accumulated discounted tax payments until ruin are derived.An explicit expression for the discounted tax payments is also given.
In this paper,we investigate the problem:How big are the increments of G-Brownian motion.We obtain the Csrg and R′ev′esz’s type theorem for the increments of G-Brownian motion.As applications of this result,we get the law of iterated logarithm and the Erds and R′enyi law of large numbers for G-Brownian motion.Furthermore,it turns out that our theorems are natural extensions of the classical results obtained by Csrg and R′ev′esz(1979).
