Results 151 to 160 of about 1,619 (185)
Recursive estimation of parameters in Markov-modulated Poisson processes
IEEE Transactions on Communications, 1995 A hidden Markov regime is a Markov process that governs the time or space dependent distributions of an observed stochastic process. Recursive algorithms can be used to estimate parameters in mixed distributions governed by a Markov regime. The authors derive a recursive algorithm for estimation of parameters in a Markov-modulated Poisson process also ...
Georg Lindgren
exaly +4 more sources
Fitting procedure for the two-state Batch Markov modulated Poisson process [PDF]
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 +9 more sources
Markov-modulated Poisson processes for multi-location inventory problems
International Journal of Production Economics, 1997 In this paper we consider inventory systems of multi-location. It is common to allow emergency lateral transshipments from local locations to the main depot. Here we propose a new model for the inventory system of consumable items. The inventory system of each location and the main depot is modeled by Markovian queueing networks. The transshipments are
Wai Ki Ching
exaly +5 more sources
Multivariate models for rainfall based on Markov modulated Poisson processes [PDF]
Hydrology Research, 2013 Point process models for rainfall are constructed generally based on Poisson cluster processes. Most commonly used point process models in the literature were constructed either based on Bartlett–Lewis or Neyman–Scott cluster processes. In this paper, we utilize a class of Cox process models, termed the Markov modulated Poisson process (MMPP), to model
N I Ramesh
exaly +3 more sources
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
exaly +8 more sources
Some of the next articles are maybe not open access.
Analysis of multivariate Markov modulated Poisson processes
Operations Research Letters, 1992zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ushio Sumita, Yasushi Masuda
exaly +3 more sources
The Markov-modulated Poisson process (MMPP) cookbook
Performance Evaluation, 1993Summary: Point processes whose arrival rates vary randomly over time arise in many applications of interest, notably in communications modeling. The Markov- modulated Poisson process has been extensively used for modeling these processes, because it qualitatively models the time-varying arrival rate and captures some of the important correlations ...
Wolfgang Fischer 0002 +1 more
exaly +3 more sources
Parameter estimation for Markov modulated poisson processes
Stochastic Models, 1994Summary: A Markov modulated Poisson process (MMPP) is a doubly stochastic Poisson process whose intensity is controlled by a finite state continuous-time Markov chain. MMPPs have during the last decade been used to model traffic flows in communication networks as well as environmental data.
exaly +3 more sources
ACM Transactions on Modeling and Performance Evaluation of Computing Systems, 2017 The Markov Modulated Poisson Process (MMPP) has been extensively studied in random process theory and widely applied in various applications involving Poisson arrivals whose rate varies following a Markov process. Despite the rich literature
Kui Wu, Venkaṭesh Srinivasan
exaly +2 more sources
Approximation of Some Markov-Modulated Poisson Processes
ORSA Journal on Computing, 1991The Markov-modulated Poisson process (MMPP) is a doubly stochastic Poisson process in which the arrival rate varies according to a finite state irreducible Markov process. In many applications of MMPPs, the point process is constructed by superpositions or similar constructions, which lead to modulating Markov processes with a large state space. Since
exaly +3 more sources