dc.contributor.advisor Ali, Ayesha dc.contributor.advisor Umphrey, Gary dc.contributor.author Callaghan, Liam dc.date.accessioned 2013-01-08T16:49:47Z dc.date.available 2013-01-08T16:49:47Z dc.date.copyright 2012-12 dc.date.created 2012-12-04 dc.date.issued 2013-01-08 dc.identifier.uri http://hdl.handle.net/10214/5252 dc.description.abstract There may be several mechanisms that drive observed interactions between plants and pollinators in an ecosystem, many of which may involve trait matching or trait complementarity. Hence a model of insect species activity on plant species should be represented as a mixture of these linkage rules. Unfortunately, ecologists do not always know how many, or even which, traits are the main contributors to the observed interactions. This thesis proposes the Latent Dirichlet Allocation (LDA) model from artificial intelligence for modelling the observed interactions in an ecosystem as a finite mixture of (latent) interaction groups in which plant and pollinator pairs that share common linkage rules are placed in the same interaction group. Several model selection criteria are explored for estimating how many interaction groups best describe the observed interactions. This thesis also introduces a new model selection score called penalized perplexity". The performance of the model selection criteria, and of LDA in general, are evaluated through a comprehensive simulation study that consider networks of various size along with varying levels of nesting and numbers of interaction groups. Results of the simulation study suggest that LDA works well on networks with mild-to-no nesting, but loses accuracy with increased nestedness. Further, the penalized perplexity tended to outperform the other model selection criteria in identifying the correct number of interaction groups used to simulate the data. Finally, LDA was demonstrated on a real network, the results of which provided insights into the functional roles of pollinator species in the study region. en_US dc.language.iso en en_US dc.subject pollination network en_US dc.subject latent Dirichlet allocation en_US dc.subject linkage rules en_US dc.subject perplexity en_US dc.subject model selection en_US dc.subject BIC en_US dc.subject AIC en_US dc.subject DIC en_US dc.title An evaluation of latent Dirichlet allocation in the context of plant-pollinator networks en_US dc.type Thesis en_US dc.degree.programme Mathematics and Statistics en_US dc.degree.name Master of Science en_US dc.degree.department Department of Mathematics and Statistics en_US dc.rights.license All items in the Atrium are protected by copyright with all rights reserved unless otherwise indicated.