## 5 Citations

Multiple Chains Hidden Markov Models for Bivariate Dynamical Systems

- Mathematics
- 2020

We present a new modelling framework for the bi-variate hidden Markov model. The proposed specification is composed by five latent Markovian chains which drive the evolution of the parameters of a…

Hidden Markov Models for Longitudinal Rating Data with Dynamic Response Styles

- Economics
- 2021

This work deals with the analysis of longitudinal ordinal responses. The novelty of the proposed approach is in modeling simultaneously the temporal dynamics of a latent trait of interest, measured…

Hidden Markov Model for Exchange Rate with EWMA Control Chart

- Economics
- 2020

Exponentially Weighted Moving Average (EWMA) control chart will be used to determine the state of HMM and the existence of uncontrolled data implies the probability of increasing of the exchange rate in 2019.

A Hidden Markov Model for Forecasting Rainfall Data Availability at the Weather Station in West Sumatra

- Environmental Science
- 2020

Indonesia is a maritime continent in Southeast Asian, laying between Indian Ocean and Pacific Ocean. This position intensely affects the level of rainfall in Indonesia, especially West Sumatra. The…

Can hidden Markov models be used for inference about operational risk

- Computer Science
- 2018

This thesis aims to investigate the possibility if hidden Markov models (HMM) can be used for inference about operational risk given financial time series data of Auditchanges and Audit prices. The…

## References

SHOWING 1-10 OF 25 REFERENCES

Discrete chain graph models

- Mathematics
- 2009

The statistical literature discusses different types of Markov properties for chain graphs that lead to four possible classes of chain graph Markov models. The different models are rather well…

Chain graph models of multivariate regression type for categorical data

- Mathematics, Computer Science
- 2011

A parametrization based on a sequence of generalized linear models with a multivariate logistic link function that captures all independence constraints in any chain graph model of this kind.

Testing lumpability for marginal discrete hidden Markov models

- Mathematics
- 2011

When some states of a Markov chain are aggregated (or lumped) and the new process, with lumped states, inherits the Markov property, the original chain is said to be lumpable. We discuss the notion…

Inference in hidden Markov models

- Computer Science, MathematicsSpringer series in statistics
- 2005

This book is a comprehensive treatment of inference for hidden Markov models, including both algorithms and statistical theory, and builds on recent developments to present a self-contained view.

A coupled hidden Markov model for disease interactions

- MathematicsJournal of the Royal Statistical Society. Series C, Applied statistics
- 2013

To investigate interactions between parasite species in a host, a population of field voles was studied longitudinally, finding evidence for interactions between several pairs of parasites and of an acquired immune response for two of the parasites.

Hidden Markov Models for Time Series: An Introduction Using R

- Computer Science
- 2009

The model Likelihood evaluation Parameter estimation by maximum likelihood Model checking Inferring the underlying state Models for a heterogeneous group of subjects Other modifications or extensions Application to caterpillar feeding behavior appear at the end of most chapters.

Marginal models for categorical data

- Mathematics
- 2002

Statistical models defined by imposing restrictions on marginal distributions of contingency tables have received considerable attention recently. This paper introduces a general definition of…

Coupled hidden Markov models for complex action recognition

- Computer ScienceProceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition
- 1997

We present algorithms for coupling and training hidden Markov models (HMMs) to model interacting processes, and demonstrate their superiority to conventional HMMs in a vision task classifying…

Selecting hidden Markov model state number with cross-validated likelihood

- Computer ScienceComput. Stat.
- 2008

Two approaches are proposed to compute cross-validated likelihood for a hidden Markov model using a deterministic half-sampling procedure and an adaptation of the EM algorithm, to take into account randomly missing values induced byCross-validation.