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Estimating an Activity Driven Hidden Markov Model

Machine Learning 2015-07-28 v1 Data Structures and Algorithms Machine Learning Social and Information Networks Statistics Theory Statistics Theory
Authors: David A. Meyer , Asif Shakeel
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Abstract

We define a Hidden Markov Model (HMM) in which each hidden state has time-dependent activity levels\textit{activity levels} that drive transitions and emissions, and show how to estimate its parameters. Our construction is motivated by the problem of inferring human mobility on sub-daily time scales from, for example, mobile phone records.

Keywords

hidden markov models point process modeling traffic safety analysis

Cite

@article{arxiv.1507.07495,
  title  = {Estimating an Activity Driven Hidden Markov Model},
  author = {David A. Meyer and Asif Shakeel},
  journal= {arXiv preprint arXiv:1507.07495},
  year   = {2015}
}

Comments

13 pages, 2 figures

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