finite-state Markov model
Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers
... HMM state transi- ...Weighted Finite-State Transducers (WF- STs) unfold the complete HSMM structure, where each un- folded path is modeled individually at the expense of ...first state of the ...
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Finite State Markov Chain Approximations to Highly Persistent Processes
... growth model when the full depreciation assumption is ...discrete state space with 2000 grid points for capital and 400 states in the Markov chain constructed by the Rouwenhorst ...discrete ...
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Finite State Markov Chain Approximations to Highly Persistent Processes
... pricing model à la Lucas (1978), and the standard real business cycle (RBC) ...Lucas’ model, the stochastic dividend stream is assumed to follow a Markov ...RBC model, the logarithm of the ...
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Identifying speculative bubbles with an in finite hidden Markov model
... a finite hidden Markov model usually has a small number of regimes, which guarantees that each regime can have a reasonable amount of ...hidden Markov model, however, may assign each ...
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A new method for approximating vector autoregressive processes by finite state Markov chains
... The rest of the paper is organized as follows. Section 2 introduces the continuous- and discrete-valued versions of the multivariate model and the main notation. Section 3 reviews the existing approximation ...
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Genetic Algorithm Based Finite State Markov Channel Modeling
... the Markov chains where the outputs are a deterministic function of the states based on the principle of semi-hidden Markov ...Hidden Markov Model (HMM), a hidden semi-Markov ...
7
Chinese named entity recognition algorithm based on the improved hidden Markov model
... named Markov put forward the Markov Model in 1870, which is used to depict the sequence information of stochastic variable ...and finite state ...every state which is used to ...
5
The SIS epidemic model with Markovian switching
... epidemic model, which is useful in performing computer ...epidemic model and compare these with the corresponding conditions for the deterministic SIS epidemic ...two-state Markov chain and ...
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Computing the Most Probable String with a Probabilistic Finite State Machine
... probabilistic finite automaton or a hidden Markov model arises in a number of natural language processing tasks: it has to be solved in several transducer related tasks like opti- mal decoding in ...
8
On the Derivational Entropy of Left to Right Probabilistic Finite State Automata and Hidden Markov Models
... Probabilistic finite-state automata are a formalism that is widely used in many problems of automatic speech recognition and natural language ...Probabilistic finite-state automata are closely ...
21
A Regime Switching Model for the Term Structure of Credit Risk Spreads
... rating-based model for the term structure of credit risk spreads wherein the credit- worthiness of the issuer is represented as a finite-state continuous time Markov ...A model of the ...
10
Nonlinear Markov games on a finite state space (mean field and binary interactions)
... control model is obtained as a limit of discrete-time models, and we work directly with continuous time ...the model (basically continuous di ff erentiability of coef- ficients instead of Lipschitz ...
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Finite State Transducers Approximating Hidden Markov Models
... We then build the union uS i of all initial subsequences Si and the union uS~n of all extended middle subsequences S,e=, and formulate a preliminary sentence model: uS ° = ~S, uS°~* 14 i[r] ...
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Enhanced state selection Markov model for image splicing detection
... clues, Markov state transition probability feature based on transform domain (discrete cosine transform or discrete wavelet transform) seems to be most promising in the state of the ...of ...
10
Pension plan solvency and extreme market movements: a regime switching approach
... capital model (Models 1 and ...for Markov switching in the ...incorporating Markov switching, consistent with earlier sections of this ...under Model 6 than under Model ...
30
A non parametric hidden Markov model for climate state identification
... Hidden Markov models (HMMs) can allow for varying wet and dry cycles in the climate without the need to simulate supplementary climate ...the state conditional ...about state conditional ...
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Pension plan solvency and extreme market movements : a regime switching approach.
... The paper is related to two streams of the existing literature. The first examines optimal contribution rates and asset allocation decisions for DB pension plans. Josa-Fombellida and Roncón-Zapatero (2011), for example, ...
30
Pension plan solvency and extreme market movements : a regime switching approach
... This model includes a range of active, deferred and pensioner members. The scheme is closed to new entrants but open to new accrual for active members. It incorporates some decrement assumptions between the ...
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Pension plan solvency and extreme market movements: : A regime switching approach
... lognormal model of portfolio returns, we extend our analysis to incorporate extreme events into the ...and Markov regime switching ...preferred Markov models primarily for prag- matic ...that ...
31
Pension plan solvency and extreme market movements : a regime switching approach
... To overcome the weaknesses of the traditional one-state lognormal model of portfolio returns we extend our analysis to incorporate extreme events into the analysis. There are a number of techniques ...
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