This paper presents the statistical inference on the parameters of the Burr type III distribution, when the data are Type-II hybrid censored. The maximum likelihood estimators are developed for the unknown parameters using the EM algorithm method. We provided the observed Fisher information matrix using the missing information principle which is useful for constructing the asymptotic confidence...

In the first part of the correspondence we derive an upper bound on the undetected error probability of binary ( n , k ) block codes used on channels with memory described by Markov distributions. This bound is a generalization of the bound presented by Kasami et al. for the binary symmetric channel, and is given as an average value of some function of the composition of the state sequence of t...

We extend the “policy rollout” sampling technique for Markov decision processes to Markov games, and provide an approximation result guaranteeing that the resulting sampling-based policy is closer to the Nash equilibrium than the underlying base policy. This improvement is achieved with an amount of sampling that is independent of the state-space size. We base our approximation result on a more...

In this paper, we first present a key approximation result for zero-sum, discounted Markov games, providing bounds on the state-wise loss and the loss in the sup norm resulting from using approximate Q-functions. Then we extend the policy rollout technique for MDPs to Markov games. Using our key approximation result, we prove that, under certain conditions, the rollout technique gives rise to a...

We analyze the moments of the accumulated reward over the interval (0, t) in a continuous-time Markov chain. We develop a numerical procedure to efficiently compute the normalized moments using the uniformization technique. Our algorithm involves auxiliary quantities whose convergence is analyzed, and for which we provide a probabilistic interpretation. Key-words: Markov models, accumulated rew...

due to the effective role of markov models in customer relationship management (crm), there is a lack of comprehensive literature review which contains all related literatures. in this paper the focus is on academic databases to find all the articles that had been published in 2011 and earlier. one hundred articles were identified and reviewed to find direct relevance for applying markov models...

The predominant technique for computing the transient distribution of a Continuous Time Markov Chain (CTMC) exploits uniformization, which is known to be stable and efficient for non-stiff to mildly-stiff CTMCs. On stiff CTMCs however, uniformization suffers from severe performance degradation. In this paper, we report on our observations and analysis of an alternative technique using Krylov su...

High-performance control of semi-Markov jump linear systems requires an accurate model for theunderlying stochastic jump process. In practice, however, a reasonable compromise between the controlquality and computational costs should be made and the tractability of the control design problem hasto be established. This paper considers the problem of finite-horizon optimal quadratic c...

Growing amount of information on biological sequences has made application of statistical approaches necessary for modeling and estimation of their functions. In this paper, sensitivity and specificity of the first and second Markov chains for prediction of genes was evaluated using the complete double stranded  DNA virus. There were two approaches for prediction of each Markov Model parameter,...

  In this paper Semi-Markov models are used to forecast the triple dimensions of next earthquake occurrences. Each earthquake can be investigated in three dimensions including temporal, spatial and magnitude. Semi-Markov models can be used for earthquake forecasting in each arbitrary area and each area can be divided into several zones. In Semi-Markov models each zone can be considered as a sta...