Random Variables and Stochastic Processes
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چکیده
منابع مشابه
Numerical solution and simulation of random differential equations with Wiener and compound Poisson Processes
Ordinary differential equations(ODEs) with stochastic processes in their vector field, have lots of applications in science and engineering. The main purpose of this article is to investigate the numerical methods for ODEs with Wiener and Compound Poisson processes in more than one dimension. Ordinary differential equations with Ito diffusion which is a solution of an Ito stochastic differentia...
متن کاملSecond Moment of Queue Size with Stationary Arrival Processes and Arbitrary Queue Discipline
In this paper we consider a queuing system in which the service times of customers are independent and identically distributed random variables, the arrival process is stationary and has the property of orderliness, and the queue discipline is arbitrary. For this queuing system we obtain the steady state second moment of the queue size in terms of the stationary waiting time distribution of a s...
متن کاملDiscrete Time Markov Chain (DTMC)
A. A stochastic process is a collection of random variables {X t , t ∈ T }. B. A sample path or realization of a stochastic process is the collection of values assumed by the random variables in one realization of the random process, e.g. C. The state space is the collection of all possible values the random variables can take on, i.e. it is the sample space of the random variables. For example...
متن کاملFUZZY INFORMATION AND STOCHASTICS
In applications there occur different forms of uncertainty. The twomost important types are randomness (stochastic variability) and imprecision(fuzziness). In modelling, the dominating concept to describe uncertainty isusing stochastic models which are based on probability. However, fuzzinessis not stochastic in nature and therefore it is not considered in probabilisticmodels.Since many years t...
متن کاملOn the Compound Poisson Distribution
exist. We shall prove that under certain conditions we obtain (1) as a limit distribution of double sequences of independent and infinitesimal random variables and apply this theorem to stochastic processes with independent increments. Theorem 1 Let ξn1, ξn2, . . . , ξnkn (n = 1, 2, . . .) be a double sequence of random variables. Suppose that the random variables in each row are independent, t...
متن کاملResults on Sym \ 1 Etric Stable Distributions and Processes
This work investigates properties of symmetric stable distributions and stochastic processes. A necessary and sufficient condition is presented for a regression involving symmetric stable random variables to be linear. We introduce the notion of n-fold dependence for symmetric stable random variables and under this condition characterize all monomials in such random variables for which moments ...
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تاریخ انتشار 2001