[PDF] Top 20 Simulation algorithms for continuous time Markov chain models
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Simulation algorithms for continuous time Markov chain models
... and time. There are some hybrid simulation methods (also referred to as multi-scale approaches; in- terested readers can see [14] for an overview of these methods) specifically designed for multi-scale ... See full document
18
Relevant States and Memory in Markov Chain Bootstrapping and Simulation
... to Markov chains (or processes) with finite states and faces explicitly the problem of maintaining the original data ...bootstrap Markov chains were advanced by Kulperger and Prakasa Rao (1989), Basawa et ... See full document
47
Simulation study of Markov chain models with an application in Cognitive Radio Networks
... discrete-time Markov chain with general-alphabet observable ...detection algorithms derived from the Viterbi and forward-backward algorithms were presented to uncover the state sequence ... See full document
16
Structure-based software reliability prediction*
... discrete time Markov chain (DTMC) or a continuous time Markov chain (CTMC), and illustrate these methods using ex- ... See full document
6
Model checking of continuous time Markov Chains against timed automata specifications
... This paper addressed the quantitative (and qualitative) verification of a finite CTMC C against a linear real-time specification given as a deterministic timed automaton (DTA). We studied DTA with finite and ... See full document
35
Accelerating MCMC algorithms
... Markov chain Monte Carlo (MCMC) algorithms have been used for nearly 60 years and have become a reference method for analyzing Bayesian complex models in the early 1990s (Gelfand & Smith, ... See full document
14
A Stochastic SIVS Epidemic Model Based on Birth and Death Process
... general continuous time birth and death chain model, is formulated based on a deterministic model including ...use continuous time Markov chain to construct the birth and ... See full document
12
Stochastic differential equation for two-phase growth model
... Faddy [4] proposed a simple two-phase population growth model to pure death process in stochastic model. Ross and Pollett [6] developed a two-phase population growth model using control regime, while Zheng [11] built a ... See full document
31
Continuous Time Markov Chain Models of Voltage Gating of Gap Junction Channels
... language in order to form transition matrix (for DTMC) or infinitesimal generator (for CTMC), to estimate steady state probabilities and to calculate conductance at single voltage value. Modeling results were identical ... See full document
10
On Evaluating the Efficacy of Predictive Models for Cognitive Radio Spectrum Availability in Nigeria
... two time based predictive models employed in this work in modeling the activity of the PUs in ...of Markov chain model have been presented in our previous work, we focus on presenting the ... See full document
17
Large scale dynamics and fluctuations in non equilibrium stochastic particle systems
... J (ρ) is a non-linear, concave, increasing function, (5.4) equivalently R(φ), as given in (3.52), is a non-linear convex increasing function of φ. This imposes implicit conditions on the jump rates, which cannot be made ... See full document
141
Bandwidth selection for continuous time Markov processes
... In both the scalar and the multidimensional case, consistency and mixed normality of the drift and variance estimator and, hence, of the full system’s dynamics rely on the proper choice [r] ... See full document
60
The role of cellular immunity in Influenza H1N1 population dynamics
... MCMC simulation moves forward in time through the determination of tran- sition probabilities which, in turn, determine the amount of time that elapses between ...MCMC simulation using the ... See full document
7
Comparing Markov Chain Samplers for Molecular Simulation
... Keywords: Markov chain Monte Carlo; stochastic dynamics integrators; decorrelation time; integrated.. 15.[r] ... See full document
16
Stochastic Analysis of Static and Fatigue Failures with Fluctuating Manpower and Business
... Considering a continuous time Markov chain approach, the backlog level probabilities of the occurred static failures, steady state fatigue failure and various other measures are obtained[r] ... See full document
5
On the containment condition for adaptive Markov Chain Monte Carlo algorithms
... Markov chain Monte Carlo algorithms are widely used for approximately sampling from com- plicated probability ...MCMC algorithms modify their transitions on the fly, in an effort to ... See full document
26
Application of Hidden Markov Models and Hidden Semi Markov Models to Financial Time Series
... competing algorithms, which leads to high numerical stability in the form of robustness against poor initial values (Hathaway ...complex models, as the E-step of the algorithm needs to be derived for each ... See full document
157
An Analysis of Exchange Rate Regime Duration
... compared to those in the 1980s and 1970s. The durability of intermediate regimes was the highest in the 1970s and 1980s (standard errors were also the highest), which has decreased substantially in the 1990s, and the ... See full document
7
Variance Optimization for Continuous Time Markov Decision Processes
... in continuous-time Markov decision process ...traditional Markov decision process, the cost function in the variance criterion will be affected by future ... See full document
15
Markov and Neural Network Models for Prediction of Structural Deterioration of Stormwater Pipe Assets
... the time of inspection (WSAA ...mathematical models using limited samples of CCTV inspected pipes for predicting the current and future condition of stormwater pipe ... See full document
15
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