Results 1 to 10 of about 10,348 (206)
A bivariate two-state Markov modulated Poisson process for failure modeling [PDF]
Reliability Engineering and System Safety, 2021 Motivated by a real failure dataset in a two-dimensional context, this paper presents an extension of the Markov modulated Poisson process (MMPP) to two dimensions. The one-dimensional MMPP has been proposed for the modeling of dependent and non-exponential inter-failure times (in contexts as queuing, risk or reliability, among others).
Yoel G Yera +2 more
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Statistical analysis on markov-modulated poisson processes [PDF]
Environmetrics, 1995 AbstractA class of doubly stochastic Poisson processes, which is termed a Markov‐modulated Poisson process, is studied. The maximum likelihood method is used to make inferences about the Markov‐modulated Poisson process. Expressions are derived for the likelihood function and for second‐order properties of both counts and intervals.
N I Ramesh
exaly +3 more sources
An Exact Gibbs Sampler for the Markov-Modulated Poisson Process
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2006 SummaryA Markov-modulated Poisson process is a Poisson process whose intensity varies according to a Markov process. We present a novel technique for simulating from the exact distribution of a continuous time Markov chain over an interval given the start and end states and the infinitesimal generator, and we use this to create a Gibbs sampler which ...
Fearnhead, P, Sherlock, C
semanticscholar +4 more sources
Estimating the parameters of a seasonal Markov-modulated Poisson process [PDF]
Statistical Methodology, 2015 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Guillou, Armelle +2 more
semanticscholar +4 more sources
Control problem for the Markov-modulated Poisson process in the diffusion schema
Математичні СтудіїThis paper addresses the optimal control problem for a stochastic evolution system perturbed by a Markov-modulated Poisson process within a diffusion approximation framework. The considered system captures complex dynamics involving continuous evolution
S. A. Semenyuk +3 more
doaj +3 more sources
Fitting procedure for the two-state Batch Markov modulated Poisson process
European Journal of Operational Research, 2019 The Batch Markov Modulated Poisson Process (BMMPP) is a subclass of the versatile Batch Markovian Arrival process (BMAP) which has been proposed for the modeling of dependent events occurring in batches (as group arrivals, failures or risk events).
Yoel G Yera +2 more
exaly +8 more sources
Performance approximations of Markov Modulated Poisson Process arrival queue with Markovian Service using matrix geometric approach [PDF]
Yugoslav Journal of Operations Research, 2023 Queue analysis of correlated work of the arrival and the service process are not available much in literature. This research paper applies matrix geometric approach to study the MMPP/MSP/1 queuing model under the quasi-birth death(QBD) process. Customers
Ramanathan Raghavendran +1 more
doaj +2 more sources
Mathematics, 2022 In this paper, we propose models that significantly expand the scope of practical applications, namely, queueing systems with various nodes for processing heterogeneous data that require arbitrary resource capacities for their service.
Ekaterina Pankratova +2 more
doaj +2 more sources
Markov-Modulated Poisson Process Modeling for Machine-to-Machine Heterogeneous Traffic
Applied SciencesTheoretical mathematics is a key evolution factor of artificial intelligence (AI). Nowadays, representing a smart system as a mathematical model helps to analyze any system under development and supports different case studies found in real life ...
Ahmad Hani El Fawal +2 more
doaj +2 more sources
Bayesian inference for the Markov-modulated Poisson process with an outcome process [PDF]
Journal of the Royal Statistical Society Series C: Applied StatisticsAbstract In medical research, understanding changes in outcome measurements is crucial for inferring shifts in health conditions. However, traditional methods often struggle with large, irregularly longitudinal data and fail to account for the tendency of individuals in poorer health to interact more frequently with the healthcare ...
Yu Luo, Chris Sherlock
openaire +5 more sources