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A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
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Partial-likelihood analysis of spatio-temporal point-process data.

Peter J Diggle1, Irene Kaimi, Rosa Abellana

  • 1Department of Medicine, Lancaster University, Lancaster LA1 4YB, UK.

Biometrics
|August 14, 2009
PubMed
Summary
This summary is machine-generated.

This study introduces partial likelihood for spatio-temporal point processes, focusing on continuous spatial models. It demonstrates improved efficiency and easier implementation compared to full likelihood methods.

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Area of Science:

  • Statistics
  • Ecological Modeling
  • Spatio-temporal analysis

Background:

  • Spatio-temporal point-process models are crucial for analyzing event data over space and time.
  • Parameter estimation in these models often relies on full likelihood methods, which can be computationally intensive.
  • A distinction exists between spatially discrete and continuous models, with limited research on the latter.

Purpose of the Study:

  • To investigate the utility of partial likelihood for parameter estimation in spatio-temporal point-process models.
  • To specifically address the under-researched spatially continuous case.
  • To compare the efficiency and implementation ease of partial versus full likelihood methods.

Main Methods:

  • Utilized an inhomogeneous Poisson process and an infectious disease process for tractable maximum-likelihood estimation.
  • Assessed the relative efficiency of partial versus full likelihood estimation.
  • Implemented the partial-likelihood method for a real-world ecological dataset.

Main Results:

  • Partial likelihood offers a more easily implemented alternative to full likelihood for spatio-temporal point processes.
  • The study highlights the distinction and challenges associated with spatially continuous models.
  • Demonstrated the practical application and potential benefits of partial likelihood in ecological studies.

Conclusions:

  • Partial likelihood is a viable and potentially advantageous method for parameter estimation in spatially continuous spatio-temporal point-process models.
  • The findings suggest broader applicability of partial likelihood in ecological and spatial statistics.
  • Further research into spatio-temporal continuous models is warranted.