Browsing by Author "Liang, Faming"
Now showing items 1-20 of 39
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Ren, Yuan (2010-01-14)This dissertation presents an algorithm to solve optimization problems with "black-box" objective functions, i.e., functions that can only be evaluated by running a computer program. Such optimization problems often arise ...
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Park, Jincheol (2012-10-19)The Gaussian geostatistical model has been widely used in Bayesian modeling of spatial data. A core difficulty for this model is at inverting the n x n covariance matrix, where n is a sample size. The computational complexity ...
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Liang, Faming; Xiong, Momiao; Wang, Kai (PloS One, 2013)
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Gold, David L. (2009-05-15)Life sciences research is advancing in breadth and scope, affecting many areas of life including medical care and government policy. The field of Bioinformatics, in particular, is growing very rapidly with the help of ...
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Wu, Mingqi; Liang, Faming; Tian, Yanan (BMC Bioinformatics, 2009)
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Mondal, Anirban (2012-10-19)We considered a Bayesian approach to nonlinear inverse problems in which the unknown quantity is a high dimension spatial field. The Bayesian approach contains a natural mechanism for regularization in the form of prior ...
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Zhang, Ning; Li, Xiaoyan; Tao, Kai; Jiang, Liyu; Ma, Tingting; Yan, Shi; Yuan, Cunzhong; Moran, Meena S; Liang, Faming; Haffty, Bruce G; Yang, Qifeng (BMC Medical Genetics, 2011)
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Kim, Jinsu (2014-11-19)Markov chain Monte Carlo (MCMC) methods have proven to be a very powerful tool for analyzing data of complex structures. However, their compute-intensive nature, which typically require a large number of iterations and a ...
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Lin, Fang-Yu (2014-10-15)Modeling and mining with massive volumes of data have become popular in recent decades. However, it is difficult to analyze on a single commodity computer because the size of data is too large. Parallel computing is widely ...
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Maadooliat, Mehdi (2012-10-19)Storage and analysis of high-dimensional datasets are always challenging. Dimension reduction techniques are commonly used to reduce the complexity of the data and obtain the informative aspects of datasets. Principal ...
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De, Debkumar (2014-05-08)Estimating model parameters in dynamic model continues to be challenge. In my dissertation, we have introduced a Stochastic Approximation based parameter estimation approach under Ensemble Kalman Filter set-up. Asymptotic ...
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Lee, Sang Han (2009-05-15)The objective of this dissertation is to develop a suitable statistical methodology for functional data analysis. Modern advanced technology allows researchers to collect samples as functional which means the ideal unit ...
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Yang, Jui-Chung (2014-08-05)The reaction coefficients of expected inflations and output gaps in the forecast-based monetary policy reaction function may be merely weakly identified when the smoothing coefficient is close to unity, i.e., the nominal ...
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Zhang, Xuesong (2009-05-15)This study focuses on developing and evaluating efficient and effective parameter calibration and uncertainty methods for hydrologic modeling. Five single objective optimization algorithms and six multi-objective optimization ...
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Yu, Kai; Wacholder, Sholom; Wheeler, William; Wang, Zhaoming; Caporaso, Neil; Landi, Maria Teresa; Liang, Faming; Schork, Nicholas J. (PLoS Genetics, 2012)
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Wang, Qi (2012-10-19)In this dissertation, the classical problems of testing goodness-of-fit of uniformity and parametric families are reconsidered. A new omnibus test for these problems is proposed and investigated. The new test statistics ...
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Lee, Ho-Jin (Texas A&M University, 2005-11-01)Functional data refer to data which consist of observed functions or curves evaluated at a finite subset of some interval. In this dissertation, we discuss statistical analysis, especially classification and regression ...
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Pourhabib, Arash (2014-07-08)Big Data refers to the complexity, high-dimensionality, and high volume of information which are common features in many contemporary engineering applications. In the context of Big Data, however, specific treatments are ...
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Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems Liang, Faming (Annals of Statistics, 2009)
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Li, Yue (2012-02-14)This dissertation investigates three topics concerning high clouds: 1) convectively coupled equatorial wave (CCEW) signals derived from cloud top temperature (CTT) and cirrus optical thickness retrieved from satellite ...