A note on smoothed estimating functions

The kernel estimate of regression function in likelihood based models has been studied in Staniswalis (1989,J. Amer. Statist. Assoc.,84, 276–283). The notion of optimal estimation for the nonparametric kernel estimation of semimartingale intensity (t) is proposed. The goal is to arrive at a nonparametric estimate of ₀=(t ₀) for a fixed pointt ₀ [0, 1]. We consider the estimator that is a solution of the smoothed optimal estimating equation is the optimal estimating function as in Thavaneswaran and Thompson (1986,J. Appl. Probab.,23, 409–417).     

Differential equations driven by rough paths with jumps

We develop the rough path counterpart of Itô stochastic integration and differential equations driven by general semimartingales. This significantly enlarges the classes of (Itô/forward) stochastic differential equations treatable with pathwise methods. A number of applications are discussed.     

Existence and uniqueness of an optimum in the infinite-horizon portfolio-cum-saving model with semimartingale investments

The model considered here is essentially that formulated in the author's previous paper Conditions for Optimality in the Infinite-Horizon Portfolio-cum-Saving Problem with Semimartingale Investments, Stochastics and Stochastics Reports 29 (1990), 133-171. In this model, the vector process representing returns to investments is a general semimartingale. Processes defining portfolio plans arc here required only to be predictable and non-negative. Existence of an optimal portfolio-cum-saving plan is proved under slight conditions of integrability imposed on the welfare functional; the proofs rely on properties of weak precompactness of portfolio and utility sequences in suitable L _p spaces together with dominated and monotone convergence arguments. Conditions are also obtained for the uniqueness of the portfolio plan generating a given returns process (i.e. for the uniqueness of the integrands generating a given sum of semimartingale integrals) and for the uniqueness of an optimal plan; here use is made of random measures associated with the jumps of a semimartingale     

On a Class of Generalized Integrands

Abstract

In the framework of the theory of stochastic integration with respect to a family of semimartingales depending on a continuous parameter, introduced by De Donno and Pratelli as a mathematical background to the theory of bond markets, we analyze a special class of integrands that preserve some nice properties of the finite-dimensional stochastic integral. In particular, we focus our attention on the class of processes considered by Mikulevicius and Rozovskii for the case of a locally square integrable cylindrical martingale and which includes an appropriate set of measure-valued processes.     

A large closed queueing network with autonomous service and bottleneck

This paper studies the queue-length process in a closed Jackson-type queueing network with the large number N of homogeneous customers by methods of the theory of martingales and by the up- and down-crossing method. The network considered here consists of a central node (hub), being an infinite-server queueing system with exponentially distributed service times, and k single-server satellite stations (nodes) with generally distributed service times with rates depending on the value N. The service mechanism of these k satellite stations is autonomous, i.e., every satellite server j serves the customers only at random instants that form a strictly stationary and ergodic sequence of random variables. Assuming that the first k-1 satellite stations operate in light usage regime the paper considers the cases where the kth satellite station is a bottleneck node. The approach of the paper is based both on development of the method from the paper by Kogan and Liptser [16], where a Markovian version of this model has been studied, and on development of the up- and down-crossing method. This revised version was published online in June 2006 with corrections to the Cover Date.     

Stochastic partial differential equations with unbounded coefficients and applications i

The present paper is the first instalment of a three-part study of stochastic partial differentia! equations (SPDEs) having unbounded coefficients. In this paper we prove existence and uniqueness theorems for a large class of parabolic SPDEs (having unbounded data), including a class of systems of SPDEs     

Hilbert-值半鞅序列的弱收敛

本文在条件UT下研究了Hilbert-值半鞅序列到连续Hilbert-值半鞅的收敛性,并在弱收敛的条件下研究了形如X^n=∫oa^n(X^n.,s)dY^ns ∫ob^n(X^n.,s)dA^ns,X^no=O,任意n≥1随机微分方程的稳定性,其中Y^n和A^n分别为Hilbert-值半鞅和分量为增过程的Hilbert-值有限变差过程。