# Markov/semi-Markov model

### Apnea bradycardia detection based on new coupled hidden semi Markov model

**semi**

**Markov**

**Model**(HSMM) [12,13], in which the system can rest in a state for several time instants (resting time) ...hidden

**Markov**

**model**(CHMM) [14, ...

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### Lower limb locomotion activity recognition of healthy individuals using semi-Markov model and single wearable inertial sensor

**model**that can recognize lower limb locomotion activities using one single IMU ...form

**semi**-

**Markov**structure, it allows the hidden states X and U keep the same for a while, which is consistent ...

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### A shared frailty semi-parametric markov renewal model for travel and activity time-use pattern analysis

**semi**-

**Markov**

**model**to estimate the influence of covariates on travel and activity duration ...hazard

**model**to capture endogenously the influence of entrance/exit activity type ...

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### Semi Markov model for market microstructure

**model**for describing the fluctuations of a tick-by-tick single asset ...Our

**model**is based on

**Markov**renewal ...suitable

**Markov**chain, we can reproduce the strong mean-reversion of price ...

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### Applications of hidden hybrid Markov/semi-Markov models: from stopover duration to breeding success dynamics

**Markov**models is the inflexible description of the time spent in a given state, as sojourn time (state occupancy) distributions are implicitly ...a

**semi**-Markovian framework may be considered where ...

11

### Markov and semi-Markov switching linear mixed models used to identify forest tree growth components.

**semi**-

**Markov**chain (GHSMC) parameters ...estimated

**semi**-

**Markov**switching linear mixed

**model**(SMS-LMM) parameters (state occupancy distributions and marginal observation ...

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### Markov and semi-Markov switching linear mixed models for identifying forest tree growth components.

**Markov**models such as for instance hidden

**Markov**tree models; see Durand et ...for

**semi**-

**Markov**switching generalized linear mixed models to take into account non-normally distributed ...

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### Estimating Markov and semi-Markov switching linear mixed models with individual-wise random effects

**semi**-

**Markov**chain pa- rameters and the linear mixed

**model**parameters are obtained by maximizing the Monte Carlo approximation of the complete-data ...

9

### Estimating hidden semi-Markov chains from discrete sequences.

**semi**-

**Markov**chain is represented in Figure 10: only the transitions whose probability is greater than ...underlying

**semi**-

**Markov**chain is composed of two transient states followed by a ...

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### Modèles de semi-Markov cachés pour la segmentation de trajectoires oculométriques en phases de lecture

**model**with minimal BIC (referred to as M1) was then used to assess the significance of random subject effects, by comparing BIC with that of a

**model**without random ...the

**model**obtained by ...

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### On-line apnea-bradycardia detection using hidden semi-Markov models.

**semi**-

**Markov**models Miguel Altuve, Student Member, IEEE, Guy Carrault, Alain Beuch´ee, Patrick Pladys and Alfredo ...hidden

**semi**-

**Markov**

**model**is proposed to represent and ...

5

### A Markov model of land use dynamics

**semi**-

**Markov**

**model**where the sojourn time on the state F will better match the data set and so will not be ...inferred

**model**is dubious as the present data set is relatively limited in time ...

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### Assessment of Resilience in Desalination Infrastructure Using Semi-Markov Models

**model**that incorporates dynamically changing demand and future growth scenarios will contribute to the understanding of how efficiency and end-user programs may affect the system ...

14

### Solving Hidden-Semi-Markov-Mode Markov Decision Problems

**Semi**-

**Markov**-Mode

**Markov**Decision Pro- cesses (HS3MDPs), a new generalization of Hidden-Mode

**Markov**Decision Pro- cesses (HM-MDPs) to handle in a more natural and efficient way ...

15

### Choice between semi-parametric estimators of Markov and non-Markov multi-state models from coarsened observations: Choice between semi-parametric estimators of Markov and non-Markov multi-state models

**model**but a lower risk as compared to choosing the wrong

**model**; in the latter case the additional risk is of order 10 −2 ...right

**model**but to choose the best ...homogeneous

**Markov**...

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### Bayesian Nonparametric Hidden Semi-Markov Models

**semi**-

**Markov**modeling, which has a history of success in the parametric (and usually non-Bayesian) ...combine

**semi**-Markovian ideas with the HDP-HMM to construct a general class of ...

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### Approximate solution methods for partially observable Markov and semi-Markov decision processes

**Model**Approximations Our lower cost approximation approach for average cost POMDPs in fact grows out from the same approach for discounted POMDPs. There, several ...

169

### Hidden hybrid Markov/semi-Markov chains.

**semi**-Markovian states for the modeling of short or medium size homogeneous zones as shown in Section ...with

**semi**-Markovian states may be included in hidden hybrid

**Markov**/

**semi**-

**Markov**...

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### The Class of Semi-Markov Accumulation Processes

5

### Markov concurrent processes

**model**a probabilistic process allowing concurrency of local ...the

**Markov**property, that extends the

**Markov**property in the case of usual, sequential processes, and the local independence ...our ...

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