Excursions of a Gaussian process with variable variance above a barrier increasing to infinity

For a family of real-valued Gaussian processes ξ _u (t), t ∈ [0, T], we obtain an exact asymptotics of the probability of crossing a level u as u → ∞ under certain conditions on the variance and correlation. This result is applied to the investigation of excursions of a stationary zero-mean process above a barrier increasing to infinity.     

Penalized maximum likelihood estimation for a function of the intensity of a Poisson point process

Let be an unknown 2 times differentiable function and consider M to be an α- homogeneous Poisson process on Graf(f). The goal is to estimate f having a sample of the inhomogeneous Poisson process N constructed by dislocating each point of M perpendicularly to Graf(f) by a normal random variable with zero mean and constant variance σ². The exact formulas for the mean measure and the intensity function of N are obtained. Then, the function f is estimated directly using a hybrid spline approach to penalized maximum likelihood. Simulation results indicate the procedure to be consistent as and .      

Constrained maximum variance stopping for a finite horizon increasing random walk

We derive the optimal solution for the problem of choosing a non-anticipative decision rule to maximize the stopping variance of a finite horizon, increasing random walk subject to a distributional constraint, as well as an explicit upper limit on the variance of the walk’s stopping state. Problems of this caliber arise as subproblems for risk-constrained versions of standard stopping problems in areas including, for instance, market entry decision-making. A numerical example verifies the main result.     

Approximations for the maximum of a vector-valued stochastic process with drift

Giving a generalization of Berkes and Horváth (2003), we consider the Euclidean norm of vector-valued stochastic processes, which can be approximated with a vector-valued Wiener process having a linear drift. The suprema of the Euclidean norm of the processes are not far away from the norm of the processes at the right most point. We also obtain an approximation for the supremum of the weighted Euclidean norm with a Wiener process.     

Limit theorems for a recursive maximum process with location-dependent periodic intensity-parameter

We investigate the recursive sequence Z _n : =  max {Z _n − 1,λ(Z _n − 1)X _n } where X _n is a sequence of iid random variables with exponential distributions and λ is a periodic positive bounded measurable function. We prove that the Césaro mean of the sequence λ(Z _n ) converges toward the essential minimum of λ. Subsequently we apply this result and obtain a limit theorem for the distributions of the sequence Z _n . The resulting limit is a Gumbel distribution.     

A variance minimization problem for a Markov decision process

In the steady state of a discrete time Markov decision process, we consider the problem to find an optimal randomized policy that minimizes the variance of the reward in a transition among the policies which give the mean not less than a specified value. The problem is solved by introducing a parametric Markov decision process with average cost criterion. It is shown that there exists an optimal policy which is a mixture of at most two pure policies. As an application, the toymaker's problem is discussed.     

Limit theorem for the maximum of gaussian independent random variables in the spaceC

We generalize the well-known asymptotic equality for the maximum of real Gaussian random variables to the case of random variables with values in the spaceC.Translated from Ukrainskii Matematicheskii Zhurnal, Vol. 47, No. 7, pp. 1006–1008, July, 1995.     

Lower bound for the maximum of a stochastic process

The first author's participation in the preparation of this paper was supported by the Russian Foundation for Basic Research (Grant No. 93-01-00240).     

Bounds for the variance of certain stationary point processes

For the variance of stationary renewal and alternating renewal processes N_n(·) the paper establishes upper and lower bounds of the form

$\text{?B}{}_1\text{?varN}{}_8\text{(0,x–Aλx?B}{}_2\text{(0<x<∞)}$

, where λ=EN₈(0,1), with constants A, B₁ and B₂ that depend on the first three moments of the interval distributions for the processes concerned. These results are consistent with the value of the constant A for a general stationary point process suggested by Cox in 1963 [1].     

A second-order approximation for the variance of a renewal reward process

Let {C(t), t ? 0} be a renewal reward process. We obtain the approximation Var C(t) = ct + d + o(1), and explicitly identify c and d.     

The generalized variance of a stationary autoregressive process

For a stationary autoregressive process of order p and disturbance variance σ² it is shown that the determinant of the covariance of T (≥p) consecutive random variables of the process is (σ²)^T Π_i,j=1^p (1 − w_iw_j)⁻¹, where w₁, …, w_p are the roots of the associated polynomial equation.     

Limit theorems for the critical age-dependent branching process with infinite variance

Let Z(t) be the population at time t of a critical age-dependent branching process. Suppose that the offspring distribution has a generating function of the form f(s) = s + (1 ? s)^1+αL(1 ? s) where α ∈ (0, 1) and L(x) varies slowly as x → 0⁺. Then we find, as t → ∞, (P{Z(t)> 0})^αL(P{Z(t)>0})～ μ/αt where μ is the mean lifetime of each particle. Furthermore, if we condition the process on non-extinction at time t, the random variable P{Z(t)>0}Z(t) converges in law to a random variable with Laplace-Stieltjes transform 1 - u(1 + u^α)^?1/α for u ?/ 0. Moment conditions on the lifetime distribution required for the above results are discussed.     

Representation of gaussian processes equivalent to a gaussian martingalet

This paper states that a Gaussian process Y with mean 0 is equivalent to a Gaussian martingale starting from 0 if and only if Y is a semi-martingale with Gaussian martingale part and Gaussian “clrift” of a particular kind. We also obtain a theorem of Girsanov type tor Gaussian martingales and a criterion for the equivalence mentioned above in more convenient terms. Our results extend those of M. Hitsuda [8] concerning equivalence to a Wiener process