Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 12 of 12 for “"Bayesian model comparison"”.
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Investigating the properties of gamma ray bursts and gravitational wave standard sirens as high redshift distance indicators
… commonly faulted for ad hoc assumptions and models with very little discriminating observational evidence, cosmologists are continually trying, and in many cases succeeding, to improve both the data and models. However, the desire to support currently favoured models often dominates research …
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Setting location priors using beamforming improves model comparison in MEG-DCM
Modelling neuronal interactions using a directed network can be used to provide insight into the activity of the brain during experimental tasks. Magnetoencephalography (MEG) allows for the observation of the fast neuronal dynamics necessary to characterize the activity of sources and their …
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Detecting episodes of star formation using Bayesian model selection.
Bayesian model comparison is a data-driven method to establish model complexity. In this dissertation we investigate its use in detecting multiple episodes of star formation from the analysis of the Spectral Energy Distribution (SED) of galaxies. This method is validated by simulating galaxy …
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Bayesian Model Selection in terms of Kullback-Leibler discrepancy
… article we investigate and develop the practical model assessment and selection methods for Bayesian models, when we anticipate that a promising approach should be objective enough to accept, easy enough to understand, general enough to apply, simple enough to compute and coherent enough to …
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Adjoint-accelerated Bayesian inference in thermoacoustics
We demonstrate a new approach to thermoacoustic modelling, in which we use an efficient Bayesian inference framework to assimilate experimental data into thermoacoustic models. The framework provides four main tools: (i) parameter inference, (ii) uncertainty quantification, (iii) model comparison, …
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The Determinants of Successful Goal Pursuit
… the goal pursuit literature. Finally, using Bayesian model comparison we examined the extent to which these constructs predicted goal progress. Results indicate that people were more likely to make progress on the goals that they are committed to, have plans for, or that are more autonomous …
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Cognitive diagnosis modeling and applications to assessing learning
Chapter 1: Cognitive diagnosis models (CDMs) are restricted latent class models designed to assess test takers' mastery on a set of skills or attributes. With a wide range of applications in education and in psychopathology, various CDMs have been proposed and fitted to response data from different …
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A Geospatial Approach to Wildlife and Wilderness Management
… use of Poisson and negative binomial regression models to examine winter habitat use by mountain goats in the Kenai Mountains of South-Central Alaska. Using GPS collared locations data, these models produce parameter estimates similar to discrete choice models, popular in resource selection …
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Application of statistical analysis techniques to solar and stellar phenomena
… theoretical one dimensional hydrostatic loop models with observations of the temperature and/or density structure along these features. The most wellknown method for dealing with comparisons like that is the x2 approach. In this research we consider the restrictions imposed by this approach …
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Deep forward and reverse phenotyping for genetic discovery in pulmonary arterial hypertension.
… into new phenotypic clusters, I deployed a Bayesian model comparison method, BeviMed, for case-control analysis. The BeviMed analysis identified 59 significant gene-tag associations with posterior probability (PP) above 0.75 (when prior set to 0.001), including three associations with a new …
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The Bayesian Global Sky Model (B-GSM)
… cosmology studies, that an accurate foreground model be available for the low frequency sky. In this thesis, we present a new low frequency global model of the diffuse radio sky, the Bayesian Global Sky Model (B-GSM). The novel Bayesian framework of B-GSM aims to address the limitations of …
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Development and interrogation of approaches to modelling xylogenesis with a view towards their suitability for inclusion in Dynamic Global Vegetation Models
… growth processes in Dynamic Global Vegetation Models (DGVMs). Current understanding of environmental controls on plant carbon dynamics is encapsulated in DGVMs. These models are today largely ‘source-driven’, meaning that they assume growth to be the direct outcome of photosynthesis. Contrary …