Global ETD Search
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Showing 1 to 14 of 14 for “"Bayesian Parameter Estimation"”.
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Bayesian Parameter Estimation on Three Models of Influenza
… virology research for years. Estimating parameter values for these models can lead to understanding of biological values. This has been successful in HIV modeling for the estimation of values such as the lifetime of infected CD8 T-Cells. However, estimating these values is notoriously …
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Minimally Corrective, Approximately Recovering Priors to Correct Expert Judgement in Bayesian Parameter Estimation
Bayesian parameter estimation is a popular method to address inverse problems. However, since prior distributions are chosen based on expert judgement, the method can inherently introduce bias into the understanding of the parameters. This can be especially relevant in the case of distributed …
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Physics of ultrasonic wave propagation in bone and heart characterized using Bayesian parameter estimation
… in bone and in heart tissue through the use of Bayesian probability theory. Quantitative ultrasound is a noninvasive modality used for clinical detection, characterization, and evaluation of bone quality and cardiovascular disease. Approaches that extend the state of knowledge of the physics …
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Joint Shear Behavior of Reinforced Concrete Beam-Column Connections Subjected to Seismic Lateral Loading
… key points, qualitative assessment on influence parameters on RC joint shear behavior was performed. Then, RC joint shear strength models were developed using the constructed experimental database in conjunction with a Bayesian parameter estimation method. For diverse types of RC beam-column …
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Parameterizing transport maps for ensemble data assimilation
This thesis discusses methods for Bayesian parameter estimation, particularly in the case of state space models (SSMs). We begin by reviewing established methods for filtering in SSMs, and by examining the graphical model structure of a parameterized SSM. Then we discuss established methods for …
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DETECTION AND INFERENCE IN GRAVITATIONAL WAVE ASTRONOMY
… and neutron star-black hole binaries. We use Bayesian inference to place upper limits on the rate of coalescence of these binaries. We use developments made in the PyCBC search pipeline during Advanced LIGO and Virgo’s second observing run to re-analyze Advanced LIGO’s first observing run and …
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Mathematical Modeling Plasma Transport in Tokamaks
… for anomalous plasma transport in tokamaks. A Bayesian parameter estimation method is used including experimental calibration error/model offsets and error bar rescaling factors to determine the two uncertain constants in the transport model with quantitative confidence level estimates for the …
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A psychophysical investigation of quantum cognition: An interdisciplinary synthesis
… comparison based on Bayes Factors analysis, Bayesian bootstrapping, and Bayesian parameter estimation via Markov chain Monte Carlo simulations). This multimethod approach enabled us to analytically cross-validate our experimental results, thereby increasing the robustness and reliability of …
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Merging neutron star and black hole binaries: Inference of their parameters and simulations of their formation and fate
… observatories' second observing run, using Bayesian parameter estimation on the gravitational-wave data. During this observing run, LIGO-Virgo for the first time reported observations of gravitational waves from a binary neutron star inspiral, GW170817. This same source was also observed …
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Using Bayesian Inference in Design Applications
… The tools and methods previously developed for Bayesian inference are adapted and utilized to solve design problems. Given a desired design output, Bayesian parameter estimation and model comparison are employed to produce designs that meet the prescribed design specifications and requirements. …
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A Comparison of Bayesian Estimation Techniques in a Multidimensional Two-Parameter Partial Credit Item Response Model
<p>Bayesian estimation methods have shown better performance than the traditional Marginal Maximum Likelihood (MML) estimation method for parameter estimation in relatively simple item response models. However, extant literature is lacking on the investigation of Bayesian parameter estimation …
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Distributed Estimation and Performance Limits in Resource-constrained Wireless Sensor Networks
… inference in sensor networks, emphasizing parameter estimation and target tracking with resource-constrainted networks.</p> <p>To reduce the transmissions between sensors and the fusion center thereby saving bandwidth and energy consumption in sensor networks, a novel methodology, where …
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Retrieval of atmospheric properties of extrasolar planets
… in order to cover the large range of allowed parameter space. In order to run such a large number of models, we have developed a parametric pressure-temperature (P-T) profile coupled with line-by-line radiative transfer, hydrostatic equilibrium, and energy balance, along with prescriptions for …
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Investigating the Characteristics of Exoplanetary Atmospheres and Interiors
… exoplanets. Retrieval methods commonly conduct Bayesian parameter estimation and statistical inference using sampling algorithms such as Markov Chain Monte Carlo or Nested Sampling. Recently several attempts have been made to use machine learning algorithms either to complement or replace fully …