Browsing by Author "Bhattacharya, Anirban"
Now showing items 1-20 of 38
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Chuu, Eric Jason (2022-06-23)We consider the estimation of the marginal likelihood in Bayesian statistics, a essential and important task known to be computationally expensive when the dimension of the parameter space is large. We propose a general ...
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Larsen, Allyson Elaine (2020-05-21)Markov chain Monte Carlo (MCMC) sampling methods often do not scale well to large datasets, so there has been an increased interest in approximate Markov chain Monte Carlo (aMCMC) sampling methods. We propose two different ...
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Ghosh, Riddhi Pratim (2019-07-25)Estimation of correlation matrices is a challenging problem due to the notorious positive-definiteness constraint and high-dimensionality. Reparameterising Cholesky factors of correlation matrices in terms of angles or ...
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Roy Chowdhury, Ananya (2023-03-30)In a regression setup, one of the most encountered problem is the presence of error in the predictor(s) - also known as measurement error models. A popular way of dealing with measurement error models is a semiparametric ...
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Ray, Pallavi (2021-06-29)This dissertation focuses on Bayesian semiparametric regression techniques under constrained setting, and its methodological, computational and applied aspects. We study several non-traditional statistical problems that ...
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Bayesian Semiparametric Density Deconvolution and Regression in the Presence of Measurement Errors Sarkar, Abhra (2014-06-24)Although the literature on measurement error problems is quite extensive, solutions to even the most fundamental measurement error problems like density deconvolution and regression with errors-in-covariates are available ...
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Chakraborty, Antik (2018-08-06)Sparsity is a standard structural assumption that is made while modeling high-dimensional statistical parameters. This assumption essentially entails a lower dimensional embedding of the high-dimensional parameter thus ...
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Nikooienejad, Amir (2017-12-01)The advent of new genomic technologies has resulted in production of massive data sets. The outcomes in such experiments are often binary vectors or survival times, and the covariates are gene expressions obtained from ...
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Acharyya, Satwik (2020-07-02)My dissertation focuses on developing Bayesian methodology for complex data structures with an emphasis on building novel algorithms to reduce the computational complexity. One viewpoint of this dissertation is to develop ...
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A Case Study for Developing Specification Limits for Hot-Mix Asphalt and the Impact on Pay Factors Al-Khayat, Haydar Tahseen Ali (2018-07-06)Specification limits utilized in percent within limits (PWL) specifications are developed by highway agencies, and used to determine the percent of hot-mix asphalt “Lot” within specified limits, and used later to make ...
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Kidd, Brian J. (2022-07-21)Directed graphs have widespread applicability, so there is continued need for both computational and theoretical improvements. We extend the standard methodology in three different ways, which constitute the main chapters ...
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Pramanik, Sandipan (2022-06-03)We propose efficient priors for two different statistical problems: (1) designing Bayesian hypothesis tests with reduced costs for detecting the presence or absence of hypothesized effects, and (2) efficient modeling of ...
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Kundu, Anupam (2022-06-14)Estimation of the mean vector and covariance matrix is of central importance in the analysis of multivariate data. In the framework of generalized linear models, usually the variances are certain functions of the means ...
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Ghosh, Indrajit (2022-06-15)This dissertation focuses on solving some of the most interesting theoretical and methodological questions arising out of various different disciplines with a Bayesian perspective. With the advent of large scale dataset ...
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Cohn, Jonathan Hall (2022-07-12)In this dissertation, I investigate the formation and evolution of galaxies by studying two extreme populations — young, highly star forming galaxies (SFGs) at z > 2, and old, quiescent galaxies in the local Universe that ...
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Preciado Arreola, Jose Luis (2016-05-02)This dissertation provides frameworks to select production function estimators in both the state-contingent and the general monotonic and concave cases. It first presents a Birth-Death Markov Chain Monte Carlo (BDMCMC) ...
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Duncan, Parker Alley (2018-05-07)We investigate some of the geometric properties of rooted uniform infinite planar triangulations or UIPT. We wish to establish certain isoperimetric properties of the UIPT - for example, to obtain some bounds on the boundary ...
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El Helou, Rayan Sami (2023-07-05)Modern power systems are witnessing a proliferation of Distributed Energy Resources (DERs) such as renewables, energy storage systems, electric vehicles, demand response entities and more, on both supply and demand sides. ...
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El Helou, Rayan Sami (2023-07-05)Modern power systems are witnessing a proliferation of Distributed Energy Resources (DERs) such as renewables, energy storage systems, electric vehicles, demand response entities and more, on both supply and demand sides. ...
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Yuan, Dongbang (2022-07-25)We consider the problem of extracting joint and individual signals from multi-view data, that is, data collected from different sources on matched samples. We present two main contributions in this dissertation. The first ...