Continuous Time Markov Chains

نویسنده

  • STEVEN P. LALLEY
چکیده

Discrete-time Markov chains are useful in simulation, since updating algorithms are easier to construct in discrete steps. They can also be useful as crude models of physical, biological, and social processes. However, in the physical and biological worlds time runs continuously, and so discrete-time mathematical models are not always appropriate. This is especially true in population biology – organisms do not reproduce, infect each other, etc., synchronously, as in the Galton-Watson and Reed-Frost models. In such situations continuous-time Markov chains are often more suitable as models.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Stochastic Dynamic Programming with Markov Chains for Optimal Sustainable Control of the Forest Sector with Continuous Cover Forestry

We present a stochastic dynamic programming approach with Markov chains for optimal control of the forest sector. The forest is managed via continuous cover forestry and the complete system is sustainable. Forest industry production, logistic solutions and harvest levels are optimized based on the sequentially revealed states of the markets. Adaptive full system optimization is necessary for co...

متن کامل

Quasistationary Distributions for Continuous-Time Markov Chains

Quasistationary Distributions for Continuous-Time Markov Chains – p.1

متن کامل

Lecture 3: Continuous times Markov Chains. Poisson Process. Birth and Death Process. 1 Continuous Time Markov Chains

In this lecture we will discuss Markov Chains in continuous time. Continuous time Markov Chains are used to represent population growth, epidemics, queueing models, reliability of mechanical systems, etc. In Continuous time Markov Process, the time is perturbed by exponentially distributed holding times in each state while the succession of states visited still follows a discrete time Markov ch...

متن کامل

On $L_1$-weak ergodicity of nonhomogeneous continuous-time Markov‎ ‎processes

‎In the present paper we investigate the $L_1$-weak ergodicity of‎ ‎nonhomogeneous continuous-time Markov processes with general state‎ ‎spaces‎. ‎We provide a necessary and sufficient condition for such‎ ‎processes to satisfy the $L_1$-weak ergodicity‎. ‎Moreover‎, ‎we apply‎ ‎the obtained results to establish $L_1$-weak ergodicity of quadratic‎ ‎stochastic processes‎.

متن کامل

Translation Invariant Exclusion Processes ( Book in Progress ) c © 2003

1 Markov chains and Markov processes 4 1.1 Discrete-time Markov chains . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 1.2 Continuous-time Markov chains . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.3 General definitions for Markov processes . . . . . . . . . . . . . . . . . . . . 10 1.4 Poisson processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 1.5 H...

متن کامل

An Extension of Peskun and Tierney Orderings to Continuous Time Markov Chains

Peskun ordering is a partial ordering defined on the space of transition matrices of discrete time Markov chains. If the Markov chains are reversible with respect to a common stationary distribution π, Peskun ordering implies an ordering on the asymptotic variances of the resulting Markov chain Monte Carlo estimators of integrals with respect to π. Peskun ordering is also relevant in the framew...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2012