Bayesian variable selection for time series regression, with application to waste water monitoring

Roddis, I. (2014). Bayesian variable selection for time series regression, with application to waste water monitoring. https://scholar.acadiau.ca/islandora/object/theses:340

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Details:

Title

Bayesian variable selection for time series regression, with application to waste water monitoring

Author
Roddis, Ian
Call Number

LE3 .A278 2014

Date

2014

Supervisor

Chipman, Hugh

Degree Grantor

Acadia University

Degree Name

Master of Science

Degree Level

Masters

Discipline

Mathematics and Statistics

Affiliation

Mathematics & Statistics

Abstract

Waste water treatment facilities, owned and run by municipalities and industrial entities, rely on biological agents to perform the bulk of the treatment work. The bacterial agents are sensitive to numerous factors in their environment. This thesis evaluates a speci c implementation of a Bayesian structural time series model with covariates to build predictive models for bacterial health. The model uses stochastic search variable selection (SSVS), assuming independent predictors when performing its selection. A modi cation is made to the SSVS process to induce a dependence structure on the covariates' inclusion, and its e ects are evaluated with respect to MCMC convergence and predictive power.

Rights

The author retains copyright in this thesis. Any substantial copying or any other actions that exceed fair dealing or other exceptions in the Copyright Act require the permission of the author.

Permanent Link

https://scholar.acadiau.ca/islandora/object/theses:340

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