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semi-Markov Process (semi-markov + process)

Distribution by Scientific Domains

Mathematics and Statistics	50%

Selected Abstracts

Performance of Markov models for frame-level errors in IEEE 802.11 wireless LANs

INTERNATIONAL JOURNAL OF COMMUNICATION SYSTEMS, Issue 6 2009
Gennaro Boggia
Abstract Interference among different wireless hosts is becoming a serious issue due to the growing number of wireless LANs based on the popular IEEE 802.11 standard. Thus, an accurate modeling of error paths at the data link layer is indispensable for evaluating system performance and for tuning and optimizing protocols at higher layers. Error paths are usually described looking at sequences of consecutive correct or erroneous frames and at the distributions of their sizes. In recent years, a number of Markov-based stochastic models have been proposed in order to statistically characterize these distributions. Nevertheless, when applied to analyze the data traces we collected, they exhibit several flaws. In this paper, to overcome these model limitations, we propose a new algorithm based on a semi-Markov process, where each state characterizes a different error pattern. The model has been validated by using measures from a real environment. Moreover, we have compared our method with other promising models already available in the literature. Numerical results show that our proposal performs better than the other models in capturing the long-term temporal correlation of real measured traces. At the same time, it is able to estimate first-order statistics with the same accuracy of the other models, but with a minor computational complexity. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Pension Valuation Under Uncertainties: Implementation of a Stochastic and Dynamic Monitoring System

JOURNAL OF RISK AND INSURANCE, Issue 2 2002
Shih-Chieh Chang
Financial soundness and funding stability are two critical issues in pension fund management. First, we construct a generalized stochastic model to monitor the solvency risk and cash flow dynamics of the defined benefit pension plan. A semi-Markov process proposed by Dominicis et al. (1991) and Janssen and Manca (1997) is employed in structuring the transition pattern of the plan's population, and the economic-based factors are generated through plausible stochastic processes. Modifications according to classification and movements of the plan member and the plan's turnover pattern are also employed to improve its practical usefulness. Then the actuarial valuations, cash flow analyses, and workforce projection are performed and investigated. Second, we explicitly formulate the plan dynamics and implement the proposed mechanism into a risk management framework for pension management. By employing the stochastic and dynamic approach, the cost factors can be monitored throughout the valuation process. Third, we outline the procedure of implementing the proposed methodology into a monitoring system. Finally, the Taiwan Public Employees Retirement System is simplified to illustrate techniques in achieving risk management goals. [source]

A semi-Markov model of disease recurrence in insured dogs

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 5 2007
Xikui Wang
Abstract We use a semi-Markov model to analyse the stochastic dynamics of disease occurrence of dogs insured in Canada from 1990 to 1999, and the probability pattern of death from illness. After statistically justifying the use of a stochastic model, we demonstrate that a stationary first-order semi-Markov process is appropriate for analysing the available data set. The probability transition function is estimated and its stationarity is tested statistically. Homogeneity of the semi-Markov model with respect to important covariates (such as geographic location, insurance plan, breed and age) is also statistically examined. We conclude with discussions and implications of our results in veterinary contents. Copyright © 2007 John Wiley & Sons, Ltd. [source]

A Queueing Model for Chronic Recurrent Conditions under Panel Observation

BIOMETRICS, Issue 1 2005
Catherine M. Crespi
Summary In many chronic conditions, subjects alternate between an active and an inactive state, and sojourns into the active state may involve multiple lesions, infections, or other recurrences with different times of onset and resolution. We present a biologically interpretable model of such chronic recurrent conditions based on a queueing process. The model has a birth,death process describing recurrences and a semi-Markov process describing the alternation between active and inactive states, and can be fit to panel data that provide only a binary assessment of the active or inactive state at a series of discrete time points using a hidden Markov approach. We accommodate individual heterogeneity and covariates using a random effects model, and simulate the posterior distribution of unknowns using a Markov chain Monte Carlo algorithm. Application to a clinical trial of genital herpes shows how the method can characterize the biology of the disease and estimate treatment efficacy. [source]