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On Scan Statistics Through the Finite Markov Chain Imbedding Approach
This chapter provides a short review of the finite Markov chain imbedding approach for studying the distributions of discrete scan statistics,...
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On Scan Statistics Through the Finite Markov Chain Imbedding Approach
This chapter provides a short review of the finite Markov chain imbedding approach for studying the distributions of discrete scan statistics,...
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Discrete-Time Markov Chain
Markov chains serve as one of the most important methods in the application of probability theory to real-world models involving uncertainty. Markov...
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Continuous-Time Markov Chain Modeling
As we mentioned earlier, the Russian mathematician Andrei Andreyevich Markov (1856–1922) introduced sequences of values of a random variable in which...
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Finite mixture of hidden Markov models for tensor-variate time series data
The need to model data with higher dimensions, such as a tensor-variate framework where each observation is considered a three-dimensional object,...
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The Latent Markov Chain Model
The latent Markov chain model is discussed, and the relationship between the model and the latent class model is considered. An ML estimation...
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Robust parametric inference for finite Markov chains
We consider the problem of statistical inference in a parametric finite Markov chain model and develop a robust estimator of the parameters defining...
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Approximating income inequality dynamics given incomplete information: an upturned Markov chain model
This article aims to understand mobility within income distribution in cases where there is incomplete information about how individuals transit...
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Hidden Markov Model
A problem that researchers often face when constructing the models is that the observations obtained are incomplete, either by physical...
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Pairwise Markov Models and Hybrid Segmentation Approach
The article studies segmentation problem (also known as classification problem) with pairwise Markov models (PMMs). A PMM is a process where the...
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Approximations for Discrete Scan Statistics on i.i.d and Markov-Dependent Bernoulli Trials
In this short note, we examine some approximations for the distribution of the discrete scan statistic defined on i.i.d. and Markov-dependent...
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Inhomogeneous hidden semi-Markov models for incompletely observed point processes
A general class of inhomogeneous hidden semi-Markov models (IHSMMs) is proposed for modelling partially observed processes that do not necessarily...
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Hidden Markov Models
This chapter introduces hidden Markov models (HMMs), which can be viewed as an extension of mixture models, in which a unit of observation (e.g., a...
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Direct statistical inference for finite Markov jump processes via the matrix exponential
Given noisy, partial observations of a time-homogeneous, finite-statespace Markov chain, conceptually simple, direct statistical inference is...
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On the estimation of partially observed continuous-time Markov chains
Motivated by the increasing use of discrete-state Markov processes across applied disciplines, a Metropolis–Hastings sampling algorithm is proposed...
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Fitting sparse Markov models through a collapsed Gibbs sampler
Sparse Markov models (SMMs) provide a parsimonious representation for higher-order Markov models. We present a computationally efficient method for...
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A Semi-Markov Model with Geometric Renewal Processes
We consider a repairable system modeled by a semi-Markov process (SMP), where we include a geometric renewal process for system degradation upon...
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Bayesian Analysis of Proportions via a Hidden Markov Model
Time series of proportions arise in many contexts. In this paper, we consider a hidden Markov model (HMM) to describe temporal dependence in such...
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Stick-Breaking processes, Clum**, and Markov Chain Occupation Laws
We connect the empirical or ‘occupation’ laws of certain discrete space time-inhomogeneous Markov chains, related to simulated annealing, to a novel...
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Laws of Large Numbers for Non-Homogeneous Markov Systems with Arbitrary Transition Probability Matrices
In the present we establish a law of large numbers for non-homogeneous Markov systems (NHMS), for which the inherent non-homogeneous Markov chain has...