A continuous-time Markov chain approximation to L´ evy
Adaptive continuous time Markov chain approximation model to general jump-diffusions
... (2007), Markov chain Monte Carlo simulations as in Phillips and Yu (2009), Kalogeropoulos et ...the Markov chain approximation we propose in this paper has several ...the ...
22
Adaptive Continuous time Markov Chain Approximation Model to General Jump-Diffusions
... the Markov chain with S min = 60 to S max = ...the Markov chain method produces a very good fit for the call option prices from deep out-of-money to deep in-the-money strikes and relative ...
23
Applying Mean-field Approximation to Continuous Time Markov Chains
... with time, therefore not only the next state probability at a given time t 0 is of interest, but also the dependency of such probability measure on time the formula is ...
47
Applying Mean-Field Approximation to Continuous Time Markov Chains
... is time stamped and the base stations are the sources for fresh ...the time period between 8:00am till midnight, each ...different time points and for different ...
47
Efficient approximation of optimal control for continuous-time Markov games
... the Markov Reward Model Checker (MRMC) [11] implementation, which includes an implementation of the techniques proposed by Buchholz and ...the approximation for each interval may become prohibitive, these ...
45
Geometric fluid approximation for general continuous-time Markov chains
... fluid approximation for any ...a continuous process, which we term the geometric fluid approximation ...an approximation related to the GFA is consistent with the standard fluid ...a ...
26
Simulation algorithms for continuous time Markov chain models
... quickly spread throughout the system. Other interruptions occur when nurseries supply- ing farms have nowhere to send animals as they mature if the farms have not cleared their current animals for some reason. This will ...
18
Optimal Consumption and Insurance: A Continuous-Time Markov Chain Approach
... indicator process indicating sojourn, I j (t) = 1 [Z (t) = j], and the functions µ jk (t), j, k ∈ J and the intensity process µ Z(t−)k (t) are connected by the relation µ Z(t)k (t) = X j:j6=k I j (t) µ jk (t). The reader ...
22
Markov chain approximation in bootstrapping autoregressions
... stationary time series ...the Markov conditional bootstrap (Rajarshi, 1990, Horowitz, 2001), where the conditional density is estimated by kernel methods and bootstrap data are generated by successively ...
8
A Markov Chain Framework for Approximation of Cycle Time in Semiconductor Manufacturing Toolsets.
... processing time. In Equation (11) time to failure for a tool is assumed to be exponentially ...the time to failure of a tool through aggregating all the failure types into one distribution is a crude ...
85
Markov chain Monte Carlo for continuous-time discrete-state systems
... total time spent in each state and the number of transitions between each pair of MJP ...discrete-time Markov chain on this set of times to sample a new tra- ...of time where the MJP ...
155
Continuous Time Markov Chain Models of Voltage Gating of Gap Junction Channels
... a continuous time Markov chain (CTMC) models of voltage gating of gap junction (GJ) channels formed of connexin ...of Markov chain model from description of the system using PLA ...
10
Quasi-exact Approximation of Hidden Markov Chain Filters
... larger time step sizes numerical instabilities potentially arise, which limits the applicability of the filtering ...hidden Markov chain ...hidden Markov chain filter ...discrete ...
17
ctmcd: An R Package for Estimating the Parameters of a Continuous-Time Markov Chain from Discrete-Time Data
... a continuous-time Markov chain from discrete-time data occurs in a wide range of applications and especially plays an important role in gene sequence data analysis and rating based ...
15
Option pricing with transaction costs using a Markov chain approximation
... A fair option price is determined by requiring that an in6nitesimal diversion of funds into the purchase or sale of options has a neutral e7ect on achievable utility. This results in a general option pricing formula, in ...
25
Bandwidth selection for continuous time Markov processes
... This discussion illustrates a fundamental di¢culty with estimating continuous-time models with discretely-sampled data. When the data frequency is not high enough (as may be the case with daily data), and ...
60
Bayesian inference for continuous time Markov chains
... Andrey Markov. This stochastic process is called a Markov process. Markov processes can be classified based on their timing and ...the Markov process are a discrete time Markov ...
228
PARAMETER SYNTHESIS FOR CONTINUOUS-TIME MARKOV CHAINS
... This thesis built on the results of [ 4 ] and [ 13 ] to provide a gentle introduction into ap- proximation for parametric transient analysis. By minimizing (maximizing) the outgoing and incoming mass per iteration, we ...
34
A sparse Markov chain approximation of LQ-type stochastic control problems
... an approximation of certain optimal control problems for reversible diffusions by Markov decision ...reversible Markov jump process ...a Markov decision problem. A sparse approximation ...
27
Variance Optimization for Continuous Time Markov Decision Processes
... The Postal Service Company’s catalogue information system, inventory issues, and supply chain management issues are all early successful applications of the Markov decision process. Later, many real-life ...
15