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.     

Inference for thinned point processes, with application to Cox processes

Given i.i.d. point processes N₁, N₂,…, let the observations be p-thinnings N′₁, N′₂,…, where p is a function from the underlying space E (a compact metric space) to [0, 1], whose interpretation is that a point of N_i at x is retained with probability p(x) and deleted with probability 1−p(x). Strongly consistent estimators of the thinning function p and the Laplace functional L_N(f) = E[e^−N(f)] of the N_i are constructed; associated “central limit” properties are given. Tests are presented, for the case when the N_i and N′_i are both observable, of the hypothesis that the N′_i are p-thinnings of the N_i. State estimation techniques are developed for the case where the N_i are Cox processes directed by unobservable random measures M_i; these techniques yield minimum mean-squared error estimators, based on observation of only the thinned processes N′_i of the N_i and the directing measures M_i. Limit theorems for empirical Laplace functionals of point processes are given.     

Freezing limits for Calogero–Moser–Sutherland particle models

One-dimensional interacting particle models of Calogero–Moser–Sutherland type with N particles can be regarded as diffusion processes on suitable subsets of ${\mathbb{R}}^N$ like Weyl chambers and alcoves with second-order differential operators as generators of the transition semigroups, where these operators are singular on the boundaries of the state spaces. The most relevant examples are multivariate Bessel processes and Heckman–Opdam processes in a compact and noncompact setting where in all cases, these processes are related to special functions associated with root systems. More precisely, the transition probabilities can be described with the aid of multivariate Bessel functions, Jack and Heckman–Opdam Jacobi polynomials, and Heckman–Opdam hypergeometric functions, respectively. These models, in particular, form dynamic eigenvalue evolutions of the classical random matrix models like β-Hermite, β- Laguerre, and β-Jacobi, that is, MANOVA, ensembles. In particular, Dyson's Brownian motions and multivariate Jacobi processes are included. In all cases, the processes depend on so-called coupling parameters. We review several freezing limit theorems for these diffusions where, for fixed N, one or several of the coupling parameters tend to ∞. In many cases, the limits will be N-dimensional normal distributions and, in the process case, Gauss processes. However, in some cases, normal distributions on half spaces and distributions related to some other ensembles appear as limits. In all cases, the limits are connected with the zeros of the classical one-dimensional orthogonal polynomials of order N.     

Bayesian Nonparametric Estimation for Reinforced Markov Renewal Processes

Starting from the definitions and the properties of reinforced renewal processes and reinforced Markov renewal processes, we characterize, via exchangeability and de Finetti’s representation theorem, a prior that consists of a family of Dirichlet distributions on the space of Markov transition matrices and beta-Stacy processes on distribution functions. Then, we show that this family is conjugate and give some estimate results.

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Random Walks with Stochastically Bounded Increments: Renewal Theory

Summary. This paper develops renewal theory for a rather general class of random walks S_N including linear submartingales with positive drift. The basic assumption on S_N is that their conditional increment distribution functions with respect to some filtration ?_? are bounded from above and below by integrable distribution functions. Under a further mean stability condition these random walks turn out to be natural candidates for satisfying Blackwell-type renewal theorems. In a companion paper [2], certain uniform lower and upper drift bounds for S_N, describing its average growth on finite remote time intervals, have been introduced and shown to be equal in case the afore-mentioned mean stability condition holds true. With the help of these bounds we give lower and upper estimates for H * U(B), where U denotes the renewal measure of S_N, H a suitable delay distribution and B a Borel subset of IR. This is then further utilized in combination with a coupling argument to prove the principal result, namely an extension of Blackwell's renewal theorem to random walks of the previous type whose conditional increment distribution additionally contain a subsequence with a common component in a certain sense. A number of examples are also presented.     

Large deviations ordering of point processes in some queueing networks

Given a stochastic ordering between point processes, say that a p.p. N is smooth if it is less than the Poisson process with the same average intensity for this ordering. In this article we investigate whether initially smooth processes retain their smoothness as they cross a network of FIFO ·/D/1 queues along fixed routes. For the so-called strong variability ordering we show that point processes remain smooth as they proceed through a tandem of quasi-saturated (i.e., loaded to 1) M+·/D/1 queues. We then introduce the Large Deviations ordering, which involves comparison of the rate functions associated with Large Deviations Principles satisfied by the point processes. For this ordering, we show that smoothness is retained when the processes cross a feed-forward network of unsaturated ·/D/1 queues. We also examine the LD characteristics of a deterministic p.p. at the output of an M+·/D/1 queue. This revised version was published online in June 2006 with corrections to the Cover Date.     

The Manifold-Valued Dirichlet Problem for Symmetric Diffusions

Harmonic maps between two Riemannian manifolds M and N are often constructed as energy minimizing maps. This construction is extended for the Dirichlet problem to the case where the Riemannian energy functional on M is replaced by a more general Dirichlet form. We obtain weakly harmonic maps and prove that these maps send the diffusion to N-valued martingales. The basic tools are the reflected Dirichlet space and the stochastic calculus for Dirichlet processes.     

Stochastic comparisons and bounds for aging renewal process shock models and their applications

Sharp comparisons between aging renewal process shock models and the corresponding Esary-Marshall-Proschan (EMP) shock model are considered. The usefulness of such comparisons derive from the simplicity of the latter models. Simple conditions under which such aging renewal process shock models are stochastically ordered relative to a corresponding EMP-model are derived. Applications to renewal functions and single server queues are indicated.     

Properties of Hida processes on . 2. Prediction and interpolation problems for processes on

If E is an ordered set, we study the processes Y_t, t E, for which the vectorial spaces _t generated by all the conditional expectations E(Y_sβ _t) for s ≥ t have finite dimensions d(t) ≤ N. ( _t is some convenient filtration.) We first develop a geometrical approach in the general situation and give a “Goursat's representation” Y_t = Σf_i(t)M_i(t), where the M_i(t) are martingales. We then restrict us to the cases E = or E = ² and give representations of the processes by the mean of stochastic integrals of “Goursat's kernels.” The special case when Y_t is the solution of a differential equation is considered.     

The Equilibrium Behavior of Reversible Coagulation-Fragmentation Processes

The coagulation-fragmentation process models the stochastic evolution of a population of N particles distributed into groups of different sizes that coagulate and fragment at given rates. The process arises in a variety of contexts and has been intensively studied for a long time. As a result, different approximations to the model were suggested. Our paper deals with the exact model which is viewed as a time-homogeneous interacting particle system on the state space _N, the set of all partitions of N. We obtain the stationary distribution (invariant measure) on _N for the whole class of reversible coagulation-fragmentation processes, and derive explicit expressions for important functionals of this measure, in particular, the expected numbers of groups of all sizes at the steady state. We also establish a characterization of the transition rates that guarantee the reversibility of the process. Finally, we make a comparative study of our exact solution and the approximation given by the steady-state solution of the coagulation-fragmentation integral equation, which is known in the literature. We show that in some cases the latter approximation can considerably deviate from the exact solution.     

Symmetries on random arrays and set-indexed processes

A processX on the setÑ of all finite subsetsJ ofN is said to be spreadable, if for all subsequencesp=(p ₁,p ₂,...) ofN, wherepJ={p _j ;jJ}. Spreadable processes are characterized in this paper by a representation formula, similar to those obtained by Aldous and Hoover for exchangeable arrays of r.v.'s. Our representation is equivalent to the statement that a process onÑ is spreadable, iff it can be extended to an exchangeable process indexed by all finite sequences of distinct elements fromN. The latter result may be regarded as a multivariate extension of a theorem by Ryll-Nardzewski, stating that, for infinite sequences of r.v.'s, the notions of exchangeability and spreadability are equivalent.     

A study of renewal processes with infinite means

This study concerns the spent lifetime characteristic of renewal processes with infinite means. Recently, Mitov and Yanev established some important limit theorems on the asymptotic behavior of the spent lifetime which extend earlier classical results of Feller and Erickson. Here, we study the rates of convergence associated with these limit theorems by means of Monte Carlo simulation. We also identify the forms of finite approximations associated with the limits. Our simulation study leads to several questions of theoretical importance, which, if properly addressed, could open the way to applications in a variety of areas. Published in Lietuvos Matematikos Rinkinys, Vol. 46, No. 3, pp. 386–402, July–September, 2006.     

Preservation of reliability classes associated with the mean residual life by a renewal process stopped at a random time

In this paper, we show that some ageing classes of a random time T related to the mean residual life are preserved by the discrete random count variable N(T), where {N(t) : t ?0}is a renewal process independent from T under suitable conditions. In the particular case of the Poisson process, we extend the results to more reliability classes. We also consider real examples of N(T) and apply the results to queuing systems. Copyright © 2011 John Wiley & Sons, Ltd.     

Stochastic Differentiation – A Generalized Approach

The space (D ^*) of Wiener distributions allows a natural Pettis-type stochastic calculus. For a certain class of generalized multiparameter processes X: R ^N (D ^*) we prove several differentiation rules (Itô formulas); these processes can be anticipating. We then apply these rules to some examples of square integrable Wiener functionals and look at the integral versions of the resulting formulas.     

Towards better multi-class parametric-decomposition approximations for open queueing networks

Methods are developed for approximately characterizing the departure process of each customer class from a multi-class single-server queue with unlimited waiting space and the first-in-first-out service discipline. The model is (GT _i /GI _i )/1 with a non-Poisson renewal arrival process and a non-exponential service-time distribution for each class. The methods provide a basis for improving parametric-decomposition approximations for analyzing non-Markov open queueing networks with multiple classes. For example, parametric-decomposition approximations are used in the Queueing Network Analyzer (QNA). The specific approximations here extend ones developed by Bitran and Tirupati [5]. For example, the effect of class-dependent service times is considered here. With all procedures proposed here, the approximate variability parameter of the departure process of each class is a linear function of the variability parameters of the arrival processes of all the classes served at that queue, thus ensuring that the final arrival variability parameters in a general open network can be calculated by solving a system of linear equations.     

Towards a Characterization of Markov Processes Enjoying the Time-Inversion Property

We give a necessary and sufficient condition for a homogeneous Markov process taking values in ℝ ⁿ to enjoy the time-inversion property of degree α. The condition sets the shape for the semigroup densities of the process and allows to further extend the class of known processes satisfying the time-inversion property. As an application we recover the result of Watanabe (Z. Wahrscheinlichkeitstheor. Verwandte Geb. 31:115–124, 1975) for continuous and conservative Markov processes on ℝ₊. As new examples we generalize Dunkl processes and construct a matrix-valued process with jumps related to the Wishart process by a skew-product representation.      

Nonparametric density estimation for nonmixing approximable Stochastic Processes

The author deals with nonparametric density estimation for stochastic processes which satisfy the L _∞-approximability property. He considers a Parzen–Rosenblatt estimator of the density for general stationary L _∞-approximable processes. He states conditions under which it is consistent and investigates its rate of convergence. Finally, he applies his results to general nonmixing linear processes and nonmixing nonlinear autoregressive processes.     

Large deviation principle for enhanced Gaussian processes

We study large deviation principles for Gaussian processes lifted to the free nilpotent group of step N. We apply this to a large class of Gaussian processes lifted to geometric rough paths. A large deviation principle for enhanced (fractional) Brownian motion, in Hölder- or modulus topology, appears as special case.