distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Abstract This paper develops Bayesian analysis for Constant Stress Accelerated Life Test (CSALT) under Type-II censoring scheme. Failure times are assumed to distribute as the three-parameter Generalized Logistic ...

This paper investigates the packet loss effects on the VoIP Jitter, and presents a methodology for simulating packet loss on VoIP Jitter traces with self-similar characteristics. Because of its simplicity and effectiveness, the two state Markov model or Gilbert model is used to generate packet loss patterns. We proposed a new model for self-similar VoIP traffic, this model are based on voice tr...

A controlled Markov process in a Hilbert space and an ergodic cost functional are given for a control problem that is solved where the process is a solution of a parameter-dependent semilinear stochastic differential equation and the control can occur only on the boundary or at discrete points in the domain. The linear term of the semilinear differential equation is the infinitesimal generator ...

The limit frequencies of the positions in the game of Monopoly are calculated on the basis of Markov chains. In order to make the process Markovian some minor modifications in the rules are necessary. A parameter is introduced so that by varying this parameter we can determine how distorted our mode is compared with the actual game. The convergence properties of Markov chains are so nice that i...

In this paper, the problem of identifying a hidden Markov model (HMM) with general state space, e.g. a partially observed diffusion process, is considered. A particle implementation of the recursive maximum likelihood estimator for a parameter in the transition kernel of the Markov chain is presented. The key assumption is that the derivative of the transition kernel w.r.t. the parameter has a ...

A natural definition of the Markov property for multi-parameter random processes (random fields) is the following. Let {Xt, tEIR N} be a multiparameter process. For any set D in N. N, let a D denote the a-field generated by {Xt, tED}. The field {Xt, tEN. u} is said to be Markov (or Markov of degree 1 [6], or sharp Markov) if, for any bounded open set D with smooth boundary, oD and ape are condi...

This paper empirically compares the Markov-switching and stochastic volatility diffusion models of the short rate. The evidence supports the Markov-switching diffusion model. Estimates of the elasticity of volatility parameter for single regime models unanimously indicate an explosive volatility process, while the Markov-switching models estimates are reasonable. We find that either Markov-swit...

The weakness of hidden Markov models (HMMs) is that they have difficulty in modeling and capturing the local dynamics of feature sequences due to the piecewise stationarity assumption and the conditional independence assumption on feature sequences. Traditionally, in speech recognition systems, this limitation has been circumvented by appending dynamic (delta and delta-delta) components to the ...

the notion of infinite order markov process is introduced and the markov property of the flow of information is established.