Browsing by Subject "Markov Chain Monte Carlo"
Now showing items 1-12 of 12
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(2022-04-19)Additive manufacturing (AM) is a disruptive technology leveraging innovations of the past and present to enable the design and fabrication of the new standard for components across industries. However, the successful ...
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(2013-10-07)In this research thesis, we implement Markov Chain Monte Carlo techniques and polynomial-chaos expansion based techniques for states and parameters estimation in hidden Markov models (HMM). Our goal is to estimate the ...
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(2015-08-12)Cellular behavior is controlled through multivariate interactions between various biological molecules such as proteins and DNA. Various methods have previously been proposed to model such interactions. However many of ...
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(Texas A&M University, 2004-11-15)Univariate hierarchical Bayes models are being vigorously researched for use in disease mapping, engineering, geology, and ecology. This dissertation shows how the models can also be used to build modelbased risk maps for ...
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(2009-05-15)A large body of literature studies the issues of the option price and other ex-ante welfare measures under the microeconomic theory to valuate reductions of risks inherent in environment and human health. However, it does ...
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(2009-05-15)Uncertainty quantification involves sampling the reservoir parameters correctly from a posterior probability function that is conditioned to both static and dynamic data. Rigorous sampling methods like Markov Chain Monte ...
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(2018-05-08)In order to protect assets and operations in space, it is critical to collect and maintain accurate information regarding Resident Space Objects (RSOs). This collection of information is typically known as Space Situational ...
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(2023-01-10)Safe and sustainable operations in Geocentric Orbit require the acquisition, tracking, and predictive use of a large amount of data pertaining to the existence, characterization, and orbital state of objects in Earth orbit. ...
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(2019-03-14)Nonlinear filtering is the problem of estimating the state of a stochastic nonlinear dynamical system using noisy observations. It is well known that the posterior state estimates in nonlinear problems may assume non-Gaussian ...
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(2011-02-22)This dissertation research consists of two topics, population stochastics approximation Monte Carlo (Pop-SAMC) for Baysian model selection problems and ChIP-chip data analysis. The following two paragraphs give a brief ...
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(2011-06-27)In this dissertation, we have proposed two new algorithms for statistical inference for models with intractable normalizing constants: the Monte Carlo Metropolis-Hastings algorithm and the Bayesian Stochastic Approximation ...
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(2012-07-16)The engineered barrier system is a basic element in the design of repository to isolate high level radioactive waste (HLW). In this system, the clay barrier plays a prominent role in dispersing the heat generated from the ...