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Characterizing A Database of Sequential Behaviors with Latent Dirichlet Hidden Markov Models
LDHMMs sequential data variational inference variational EM behavior modeling sequence classification
2013/6/14
This paper proposes a generative model, the latent Dirichlet hidden Markov models (LDHMM), for characterizing a database of sequential behaviors (sequences). LDHMMs posit that each sequence is generat...
Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data
Hierarchically-coupled hidden Markov models learning kinetic rates single-molecule data
2013/6/14
We address the problem of analyzing sets of noisy time-varying signals that all report on the same process but confound straightforward analyses due to complex inter-signal heterogeneities and measure...
Concepts and a case study for a flexible class of graphical Markov models
Concepts a case study a flexible class graphical Markov models
2013/4/27
With graphical Markov models, one can investigate complex dependences, summarize some results of statistical analyses with graphs and use these graphs to understand implications of well-fitting models...
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
Modeling Waveform Shapes with Random Eects Segmental Hidden Markov Models
Modeling Waveform Shapes Random Eects Segmental Hidden Markov Models
2012/9/19
In this paper we describe a general probabilis-tic framework for modeling waveforms such as heartbeats from ECGdata. The model is based on segmental hidden Markov mod-els(as usedin speechrecognition) ...
Penalized estimation in high-dimensional hidden Markov models with state-specific graphical models
HMM Graphical Lasso Universal Regularization Model Selection MMDL Greedy Backwards Pruning Genome Biology Chromatin Modeling
2012/9/17
We consider penalized estimation in hidden Markov models (HMMs) with multi-variate Normal observations. In the moderate-to-large dimensional setting, estimation for HMMs remains challenging in practic...
Hidden Markov Models for the Activity Profile of Terrorist Groups
hidden Markov model self-exciting, terrorism terroristgroups Colombia Peru,point process changepoint detection
2012/9/19
The main focus of this work is on developing models for the ac-tivity profile of a terrorist group, detecting sudden spurtsand down-falls in this profile, and in general, tracking it over a period of ...
Parameter and Structure Learning in Nested Markov Models
Parameter Structure Learning in Nested Markov Models
2012/9/19
The constraints arising from DAG mod-els with latent variables can be naturally represented by means of acyclic directed mixed graphs (ADMGs). Such graphs contain directed (!) and bidirected ($) arrow...
About the posterior distribution in hidden Markov Models with unknown number of states
Hidden Markov models number of components order selection Bayesian statistics posterior distribution
2012/9/19
In this paper, we investigate the asymptotic behaviour of the posterior distribution in hidden Markov models (HMMs) when using Bayesian methodology. We obtain a general asymptotic result, and give con...
Spatial wavelet Markov models are more efficient than covariance tapering and process convolutions
Matérn covariances Kriging Wavelets Markov random fields Covariance tapering
2011/7/5
The Mat\'ern covariance function is a popular choice for modeling dependence in spatial environmental data.
Marginal log-linear parameters for graphical Markov models
multivariate discrete statistical models parametrization marginal log-linear graphical Markov models
2011/6/20
The parametrization of multivariate discrete statistical models by marginal log-linear
(MLL) parameters provides a great deal of flexibility; in particular, different MLL parametrizations
under line...
Lie Markov Models
phylogenetics Lie algebras Lie groups representation theory symmetry Markov chains
2011/6/21
Recent work has discussed the importance of multiplicative closure for the Markov mod-
els used in phylogenetics. For continuous-time Markov chains, a sufficient condition for
multiplicative closure...
Restricted Collapsed Draw: Accurate Sampling for Hierarchical Chinese Restaurant Process Hidden Markov Models
Restricted Collapsed Draw Accurate Sampling Hierarchical Chinese
2011/7/5
We propose a restricted collapsed draw (RCD) sampler, a general Markov chain Monte Carlo sampler of simultaneous draws from a hierarchical Chinese restaurant process (HCRP) with restriction.
An asymptotic approximation of the marginal likelihood for general Markov models
Statistics Theory (math.ST)
2010/12/17
The standard Bayesian Information Criterion (BIC) is derived under regularity conditions which are not always satisfied by the graphical models with hidden variables.
Hidden Markov models for alcoholism treatment trial data
Hidden Markov models alcoholism clinical trial
2010/10/19
In a clinical trial of a treatment for alcoholism, a common response variable of interest is the number of alcoholic drinks consumed by each subject each day, or an ordinal version of this response, ...