Standard tri-point transition function

It is usually difficult to express a family of tri-point transition function (TTF) by a transition matrix as Markov processes with one parameter. In this paper, we define three kinds of connection matrixes on the states of standard tri-point transition function (STTF) and study their essential character, give a constructive method on the constant-value standard tri-point transition function and a general expression of the state-symmetric standard tri-point transition function by a sequence of the transition matrixes of special and simple Markov processes with one parameter.     

Markov积分算子半群的限制及关于增加积分算子半群的生成

证明了转移函数是l∞的一个子空C^1上的正的压缩C0半群，其极小生成元恰好是Markov积分算子半群的生成元在C^1中的部分；Markov积分算子半群的生成元稠定的充分必要条件是q-矩阵Q一致有界；同时转移函数是Feller—Reuter—Riley的充要条件是Markov积分算子半群的生成元在Cn中的部分产生一个强连续半群．最后，在序Banach空间给出了增加的压缩积分算子半群的生成定理．     

Applications of Feller–Reuter–Riley Transition Functions

A Feller–Reuter–Riley function is a Markov transition function whose corresponding semigroup maps the set of the real-valued continuous functions vanishing at infinity into itself. The aim of this paper is to investigate applications of such functions in the dual problem, Markov branching processes, and the Williams-matrix. The remarkable property of a Feller–Reuter–Riley function is that it is a Feller minimal transition function with a stable q-matrix. By using this property we are able to prove that, in the theory of branching processes, the branching property is equivalent to the requirement that the corresponding transition function satisfies the Kolmogorov forward equations associated with a stable q-matrix. It follows that the probabilistic definition and the analytic definition for Markov branching processes are actually equivalent. Also, by using this property, together with the Resolvent Decomposition Theorem, a simple analytical proof of the Williams' existence theorem with respect to the Williams-matrix is obtained. The close link between the dual problem and the Feller–Reuter–Riley transition functions is revealed. It enables us to prove that a dual transition function must satisfy the Kolmogorov forward equations. A necessary and sufficient condition for a dual transition function satisfying the Kolmogorov backward equations is also provided.     

Estimate Optimization for Characteristics of Dynamical Systems

The purpose of this article is to obtain the most accurate estimate for the transition process of a system. The estimate is calculated by using the Lyapunov function. Finding the most accurate estimates for transition processes is formulated as a problem of constructing the most optimal Lyapunov function. At the beginning, the optimization problems were related to finding a maximal region of asymptotic stability. Later, the methods used for optimizing the Lyapunov function were used to calculate the overcontrol measure, an integral quality criterion, and the duration of the transition process.     

MIL-STD-1916中连续抽样方案的流向图方法

本文把转移概率流向图和转移概率母函数的方法引入到对MIL-STD-1916中连续抽样方案的讨论中,给出了抽样方案的平均检出质量函数AOQ,抽查特性函数L(p)和平均检查比率函数AFI全部3项指标的理论推导,为进一步探讨带有停止检查的MIL-STD-1916中连续抽样方案及相应的动态检出质量提供了理论基础。     

Decompositions of theM/M/1 transition function

Two decompositions are established for the probability transition function of the queue length process in the M/M/1 queue by a simple probabilistic argument. The transition function is expressed in terms of a zero-avoiding probability and a transition probability to zero in two different ways. As a consequence, the M/M/1 transition function can be represented as a positive linear combination of convolutions of the busy-period density. These relations provide insight into the transient behavior and facilitate establishing related results, such as inequalities and asymptotic behavior.     

更新过程及流向图在链型抽样方案中的应用

本文首次将更新过程 ,多元转移概率流向图及多元转移概率母函数引入到链型抽样方案chsp- 1中 ,推导出链型抽样方案 chsp- 1的抽样特性函数 L(P) ,为探讨各类链型抽样方案的统计特性提供新途径     

Siegmund Duality for Continuous Time Markov Chains on Z_+~d

For the continuous time Markov chain with transition function P(t) on Z_+~d, we give the necessary and sufficient conditions for the existence of its Siegmund dual with transition function P(t).If Q, the q-matrix of P(t), is uniformly bounded, we show that the Siegmund dual relation can be expressed directly in terms of q-matrices, and a sufficient condition under which the Q-function is the Siegmund dual of some Q-function is also given.     

Derivation of transitional asymptotic expansions from integral representations

A method for deriving transitional asymptotic expansions from integral representations is described and applied to Anger function and modified Hankel function. The method consists in deriving asymptotic expansions of the function considered as well as its first derivativeat the transition point using conventional methods such as Laplace’s method or the method of steepest descents. Since both the functions considered satisfy a second order linear differential equation, it is possible to obtain asymptotic expansions of higher order derivatives of the functions from the first two expansions. Thus asymptotic expressions for all the derivatives at the transition point are known and a Taylor expansion of the function in the neighbourhood of the transition point can be written. The method is also applicable to the generalized exponential integral, Weber’s parabolic cylinder function and Poiseuille function.     

扰动色谱方程黎曼解的极限-delta激波的行成和转换

本文主要讨论扰动色谱方程delta激波解的行成和转换,并讨论上述方程的黎曼问题.当扰动参数趋于零时,通过研究黎曼解的极限,我们可以观察到如下两个重要现象:激波和接触间断重合行成delta激波,一类激波(一个变量含有delta函数).     

A generalized penalty function in Sparre Andersen risk models with surplus-dependent premium

In a general Sparre Andersen risk model with surplus-dependent premium income, the generalization of Gerber-Shiu function proposed by Cheung et al. (2010a) is studied. A general expression for such Gerber-Shiu function is derived, and it is shown that its determination reduces to the evaluation of a transition function which is independent of the penalty function. Properties of and explicit expressions for such a transition function are derived when the surplus process is subject to (i) constant premium; (ii) a threshold dividend strategy; or (iii) credit interest. Extension of the approach is discussed for an absolute ruin model with debit interest.     

The Strong Mixing Data-Based Semiparametric Smooth Transition Regression Model

In this paper, we generalize the semiparametric smooth transition regression model proposed by Wang (2012a), to adapt for the strictly stationary strong mixing data and strong mixing data with deterministic trends. The unknown bounded smooth function embedded in the smooth transition function is estimated by series estimator, the consistency and asymptotic normality properties of estimators are proved employing nonlinear least square regression theory and series estimator approach. Variance matrix estimation and hypothesis testing problems are also discussed based on estimated standard errors. The new model is then used to study the annually inflation rates of China.     

The ergodic theorems for Markov chains with an arbitrary phase space

The ergodic theorems are formulated both is the case of the uniform ergodicity and in the absence of this latter under more general conditions than before. The conditions laid down on the transition function in the case of nonuniform ergodicity are less restrictive than these by Athreya-Ney and Nummelin. In contrast to these latter the restrictions are set not on the initial transition function, but on that of the imbedded Markov chain which is constructed by the instants of the recurrence to some fixed set. The proof is based on the spectral theory of Banach algebras.     

Analyzing continuous state space failure time processes: Two further results*

In a recent paper, Petersen (1988) considered a continuous state space failure time process. The central result provided in that paper was that the destination‐specific rate of transition of the process can be specified in two steps. First, one specifies the overall rate at which a change occurs. Then, one specifies the probability density function of the destination state, given that a transition occurred. This two‐step property was used in deriving the likelihood of the data and was exploited for purposes of estimation. The overall rate of transition can be estimated from the data on durations between changes in the dependent variable. The density for the new value of the dependent variable, given a change, can be estimated from the data on the values of the dependent variable after the change.

This paper extends these results in two ways. First, it is shown that one can derive the likelihood of the process directly from the destination‐specific rate of transition, without going through its decomposition into the overall rate times the density of the destination state, given a transition. Once the likelihood is derived, estimation is comparatively straightforward. Second, it is shown how one can derive, at each point in time, a more standard regression function for the continuous dependent variable, where its value is expressed in terms of its conditional mean plus an error term.     

On solutions of Kolmogorovʼs equations for nonhomogeneous jump Markov processes

This paper studies three ways to construct a nonhomogeneous jump Markov process: (i) via a compensator of the random measure of a multivariate point process, (ii) as a minimal solution of the backward Kolmogorov equation, and (iii) as a minimal solution of the forward Kolmogorov equation. The main conclusion of this paper is that, for a given measurable transition intensity, commonly called a Q-function, all these constructions define the same transition function. If this transition function is regular, that is, the probability of accumulation of jumps is zero, then this transition function is the unique solution of the backward and forward Kolmogorov equations. For continuous Q-functions, Kolmogorov equations were studied in Feller?s seminal paper. In particular, this paper extends Feller?s results for continuous Q-functions to measurable Q-functions and provides additional results.     

Siegmund Duality for Continuous Time Markov Chains on ℤ<Stack><Subscript>+</Subscript><Superscript>d</Superscript></Stack>

For the continuous time Markov chain with transition function P(t) on Z₊^d, we give the necessary and sufficient conditions for the existence of its Siegmund dual with transition function P(t). If Q, the q-matrix of P(t), is uniformly bounded, we show that the Siegmund dual relation can be expressed directly in terms of q-matrices, and a sufficient condition under which the Q-function is the Siegmund dual of some Q-function is also given.     

On the adaptive control of a class of partially observed Markov decision processes

This paper is concerned with the adaptive control problem, over the infinite horizon, for partially observable Markov decision processes whose transition functions are parameterized by an unknown vector. We treat finite models and impose relatively mild assumptions on the transition function. Provided that a sequence of parameter estimates converging in probability to the true parameter value is available, we show that the certainty equivalence adaptive policy is optimal in the long-run average sense.     

Estimation of 1-dimensional nonlinear stochastic differential equations based on higher-order partial differential equation numerical scheme and its application

A method based on higher-order partial differential equation (PDE) numerical scheme are proposed to obtain the transition cumulative distribution function (CDF) of the diffusion process (numerical differentiation of the transition CDF follows the transition probability density function (PDF)), where a transformation is applied to the Kolmogorov PDEs first, then a new type of PDEs with step function initial conditions and 0, 1 boundary conditions can be obtained. The new PDEs are solved by a fourth-order compact difference scheme and a compact difference scheme with extrapolation algorithm. After extrapolation, the compact difference scheme is extended to a scheme with sixth-order accuracy in space, where the convergence is proved. The results of the numerical tests show that the CDF approach based on the compact difference scheme to be more accurate than the other estimation methods considered; however, the CDF approach is not time-consuming. Moreover, the CDF approach is used to fit monthly data of the Federal funds rate between 1983 and 2000 by CKLS model.     

Analytically measurable selection of epsilon optimal transition kernals

The problem of existence of ah ε-optimal transition kernel for a canonical continuous time stochastic process with a general cost variable is considered. An analytically measurable, ε-optimal kernel exists if the state space is a compact Banach space, the cost variable is lower-semi-analytic, and the graph of the admissibility function is an analytic set. The result is applied to a problem in which the controller is to optimally select transition probabilities for a non-Markovian step process based on statistical estimates of holding time distributions.     

多机制半参数平滑转换回归模型——兼论我国宏观经济运行周期

本文结合多机制平滑转换回归模型和半参数平滑转换回归模型,提出多机制半参数平滑转换回归模型。对模型转换函数中的未知光滑有界函数采用级数估计,并给出了结合Back-fitting算法和非线性最小二乘法估计模型参数的具体执行步骤,随机模拟结果说明了本文模型和估计算法的可行性和灵活性。应用本文模型和估计算法对我国宏观经济运行周期的实证研究表明,我国经济增长的非线性结构可以分为四个显著不同的增长机制:扩张阶段、衰退阶段、收缩阶段、恢复阶段,并且宏观经济政策的作用有三到四个季度的迟滞效应。