搜索结果: 1-12 共查到“理论统计学 Markov models”相关记录12条 . 查询时间(0.118 秒)
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...
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...
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.
In this work we introduce a new and richer class of finite
order Markov chain models and address the following model
selection problem: find the Markov model with the minimal set
of parameters (min...
Efficient estimation of copula-based semiparametric Markov models
Copula geometric ergodicity nonlinear Markov models semi-parametric efficiency sieve likelihood ratio statistics sieve MLE tail dependence value-at-risk
2010/3/17
paper considers the efficient estimation of copula-based semi-
parametric strictly stationary Markov models. These models are char-
acterized by nonparametric invariant (one-dimensional marginal) di...
EM versus Markov chain Monte Carlo for estimation of hidden Markov models: a computational perspective
hidden Markov model incomplete data missing data EM trans-dimensional Monte Carlo computational statistics
2009/9/22
Hidden Markov models (HMMs) and related models have become stan-
dard in statistics during the last 15C2 years, with applications in diverse areas
like speech and other statistical signal processing...
Maximum Likelihood Estimator for Hidden Markov Models in continuous time
Maximum Likelihood Estimator continuous time Hidden Markov Models partial observations filtering
2010/4/30
The paper studies large sample asymptotic properties of the
Maximum Likelihood Estimator (MLE) for the parameter of a continuous
time Markov chain, observed in white noise. Using the method of
weak...
We will outline novel approaches to derive model invariants for
hidden Markov and related models. These approaches are based on
a theoretical framework that arises from viewing random processes as
...
Distributions associated with general runs and patterns in hidden Markov models
Competing patterns CpG islands finite Markov chain imbedding generalized later patterns higher-order hidden Markov models
2010/4/29
This paper gives a method for computing distributions associated
with patterns in the state sequence of a hidden Markov model, conditional
on observing all or part of the observation sequence. Proba...
Forgetting of the initial distribution for Hidden Markov Models
Nonlinear filtering Hidden Markov Models asymptotic stability totalvariation norm
2010/4/27
The forgetting of the initial distribution for discrete Hidden Markov Models (HMM)
is addressed: a new set of conditions is proposed, to establish the forgetting property
of the filter, at a polynom...