The correlation of the backward and forward recurrence times in a renewal process

The joint complementary distribution function is used to obtain the covariance function of the backward and forward recurrence times in an ordinary renewal process for both the time dependent and the steady state cases. Hence, a closed form expression for the steady state correlation of the backward and forward recurrence times is obtained and special cases are investigated     

The moments of forward recurrence time

The moments of the forward recurrence time of an ordinary renewal process are derived in terms of the renewal function and the moments of the common lifetime distribution. The covariance between the forward recurrence time and the number of renewals is also obtained. Asymptotic formulae as the process is allowed to run on for a fixed long time are given.     

The asymptotic ruin problem when the healthy and sick periods form an alternating renewal process

Let {T₁, Y₁}^∞_i=1 be a sequence of positive independent random variables. Let, also, Z₁ = βY′₁ ? πT_i, i = 1, 2, …, where Y′₁ = Max(0, Y_i ? w), w ? 0, and where β < 0 and π is such that E(Z₁) < 0. We consider the random walk of partial sums S_n = ?ⁿ_i=1Z_i in the presence of an absorbing region (u, ∞), u ? 0, and S₀ ≡ 0. Of interest is $\text{ψ(u) = Pr(}\text{S}\text{?}\text{≤ u)}$ where S? = Sup(0, S₁, S₂, …, S_n, …).     

The superposition of the backward and forward processes of a renewal process

A fixed sampling point O is chosen independently of a renewal process

on the whole real line. The distances Y₁, Y₂, … from O to the renewal points of

, when they are measured either forwards or backwards in time, define a point process

. The process

is a folding over of the past of

onto its future. It is the superposition of two equilibrium renewal processes which are known to be independent only when

is a Poisson process. The joint distribution of Y₁, Y₂, …, Y_k is found. The marginal distribution of 2Y_k is shown to be the same as that of the distance from O to the k^th following point of

. The intervals of

are shown to have a stationarity property, and it is proved that if any pair of adjacent intervals of

are independent, then

is a Poisson process.     

Delayed renewal process with uncertain interarrival times

Delayed renewal process is a special type of renewal process in which the first interarrival time is quite different from the others. This paper first proposes an uncertain delayed renewal process whose interarrival times are regarded as uncertain variables. Then it gives an uncertainty distribution of delayed renewal process and an elementary delayed renewal theorem.     

Distribution of order statistics of waiting times in an ordinary renewal process and the covariance of the renewal increments

The joint distribution of inter–renewal times and the number of renewals is used to derive joint and marginal distributions of order statistics of waiting times of an ordinary renewal process. Also, expressions are obtained for the covariance function of the number of renewals and of the renewal increments in an ordinary renewal counting process in terms of the renewal function     

Characterizations of the Poisson process as a renewal process via two conditional moments

Given two independent positive random variables, under some minor conditions, it is known that fromE(X^rX+Y)=a(X+Y)^r andE(X^sX+Y)=b(X+Y)^s, for certain pairs ofr ands, wherea andb are two constants, we can characterizeX andY to have gamma distributions. Inspired by this, in this article we will characterize the Poisson process among the class of renewal processes via two conditional moments. More precisely, let {A(t), t0} be a renewal process, with {S _k, k1} the sequence of arrival times, andF the common distribution function of the inter-arrival times. We prove that for some fixedn andk, kn, ifE(S _k ^r A(t)=n)=at^r andE(S _k ^s A(t)=n)=bt^s, for certain pairs ofr ands, wherea andb are independent oft, then {A(t), t0} has to be a Poisson process. We also give some corresponding results about characterizingFto be geometric whenF is discrete.Support for this research was provided in part by the National Science Council of the Republic of China, Grant No. NSC 81-0208-M110-06.     

Backward and forward recurrence times,and their interrelationships in Bellman-Harris branching processes

Random variables are constructed for a Bellman-Harris branching process which are the extensions of backward and forward recurrence times from an ordinary renewal process. The sum of the two extended random variables is also constructed, and then the distribution functions for all three random variables are developed. The asymptotic limits for all three time-dependent distributions are also obtained.     

An asymptotic of high order moments of renewal

Institute of Mathematics and Informatics, Akademijos 4, 2600 Vilnius, Lithuania. Published in Lietuvos Matematikos, Rinkinys, Vol. 35, No. 3, pp. 251–258, July–September, 1995.     

A generalization of the inspection paradox in an ordinary renewal process

The inspection paradox in an ordinary renewal process is investigated in the very general case of the time dependent problem and arbitrary distribution of inter–renewal times with finite mean and a probability density function     

Exponential estimates of the rate of convergence for the higher renewal moments

Novosibirsk. Translated from Sibirskii Matematicheskii Zhurnal, Vol. 32, No. 4, pp. 143–152, July–August, 1991.     

Adjustment of the moments of the project completion times when activity times are exponentially distributed

The problem of determining the moment of the project completion time (MPCT) with stochastic activity durations is addressed. In the direct approach the MPCT is obtained after analyzing all possible network paths which is NP-hard problem. A recursive method for determining MPCT by proceeding iteratively over the nodes is the computationally least demanding and therefore the most efficient approach. Unfortunately, the moment methods which are available in literature ignore some aspects. In this paper, an adjustment of the moment completion time is discussed. Two illustrative examples are presented.     

A semimarkov model of a renewal process with an unreliable switch

We consider the superposition of two renewal processes and construct a semimarkov process with a discrete/continuous phase space that describes the functioning of the superposition Translated fromDinamicheskie Sistemy, Vol. 11, 1992.     

The moments of the extended compound point process with applications

The Concept of Compound point(or counting)process is generalized to account for situations in which the compound events are described by a stochastic process rather than a random variable. Quasi–closed form expressions for the mean and the variance of this extended compounded point process are obtained in terms of the first two moments of the underlying point process and of the process describing the compound events. An expression for the higher moments is also obtained. The results are applied to obtain the mean and variance of the number of busy channels in a pp^x/G/∞ queue. (PP=point process) which generalises results of the M(t)^x/G/∞ and GI^x/G/∞ queue. Other applications include the derivation of the first two moments of the total backlog and of the revenues from telephone traffic in a PP/G/∞ queue. Finally, a special empirical model is considered     

Construction of a recurrence relation for modified moments

In this paper we are constructing a recurrence relation of the form

$\text{∑}\text{i=0}\text{r}\text{ω}{}_{\mathrm{i}}\text{(k)m}{}_{\mathrm{k+i}}{}^{\mathrm{\{\lambda \}}}\text{[f] = ω(k)}$

for integrals (called modified moments)

$\text{m}{}_{\mathrm{k}}{}^{\mathrm{\{\lambda \}}}\text{[f]df=}\text{∫}\text{?1}\text{1}\text{f(x)C}{}_{\mathrm{k}}{}^{\mathrm{(\lambda )}}\text{(x)dx (k = 0,1,…)}$

in which C_k^(λ) is the k-th Gegenbauer polynomial of order $\text{λ(λ > ?}\text{1}\text{2}\text{)}$, and f is a function satisfying the differential equation

$\text{∑}\text{i=0}\text{n}\text{P}{}_{\mathrm{i}}\text{(x)f}{}^{\mathrm{(i)}}\text{(x) = p(x) (?1?x?1)}$

of order n, where p₀, p₁, …, p_n ? 0 are polynomials, and m_k^〈λ〉[p] is known for every k. We give three methods of construction of such a recurrence relation. The first of them (called Method I) is optimum in a certain sense.     

Asymptotic expansions for the variance of stopping times in nonlinear renewal theory

We treat the problem of finding asymptotic expansions for the variance of stopping times for Wiener processes with positive drift (continuous time case) as well as sums of i.i.d. random variables with positive mean (discrete time case). Carrying over the setting of nonlinear renewal theory to Wiener processes, we obtain an asymptotic expansion up to vanishing terms in the continuous time case. Applying the same methods to sums of i.i.d. random variables, we also provide an expansion in the discrete time case up to terms of order o(b^1/2) where the leading term is of order O(b), as b → ∞. The possibly unbounded term is the covariance of nonlinear excess and stopping time.     

Invariance principles for renewal processes when only moments of low order exist

Starting from recent strong and weak approximations to the partial sums of i.i.d. random vectors (cf. U. Einmahl, Ann. Probab., 15 1419–1440), some corresponding invariance principles are developed for associated renewal processes and random sums. Optimality of the approximation is proved in the case when only two moments exist. Among other applications, a Darling-Erdös type extreme value theorem for renewal processes will be derived.     

On the moments of some first passage times and the associated processes

First passage problems for exponenetial class of random processes are discussed