Browsing by Duke Department "Statistical Science"

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  • Ji, Chunlin (2009)
    <p>The modelling and analysis of complex stochastic systems with increasingly large data sets, state-spaces and parameters provides major stimulus to research in Bayesian nonparametric methods and Bayesian computation. ...
  • Bonassi, Fernando Vieira (2013)
    <p>This thesis focuses on the development of ABC methods for statistical modeling in complex dynamic systems. Motivated by real applications in biology, I propose computational strategies for Bayesian inference in contexts ...
  • Scott, James Gordon (2009)
    <p>This thesis is about Bayesian approaches for handling multiplicity. It considers three main kinds of multiple-testing scenarios: tests of exchangeable experimental units, tests for variable inclusion in linear regresson ...
  • Niemi, Jarad (2009)
    <p>Dynamic models, also termed state space models, comprise an extremely rich model class for time series analysis. This dissertation focuses on building state space models for a variety of contexts and computationally ...
  • Nakajima, J; West, M (2013-04-01)
    We discuss a general approach to dynamic sparsity modeling in multivariate time series analysis. Time-varying parameters are linked to latent processes that are thresholded to induce zero values adaptively, providing natural ...
  • Leininger, Thomas Jeffrey (2014)
    <p>We explore the posterior inference available for Bayesian spatial point process models. In the literature, discussion of such models is usually focused on model fitting and rejecting complete spatial randomness, with ...
  • Dalzell, Nicole M. (2017)
    <p>File linking allows analysts to combine information from two or more sources of information, creating linked data bases. From linking school records to track student progress across years, to official statistics and ...
  • Shapiro, Heather (2015-05-08)
    The Billboard Hot 100 has been the main record chart for popular music in the American music industry since its first official release in 1958. Today, this rank- ing is based upon the frequency of which a song is played ...
  • Chen, Yuhan (2016)
    <p>Testing for differences within data sets is an important issue across various applications. Our work is primarily motivated by the analysis of microbiomial composition, which has been increasingly relevant and important ...
  • Chen, Xi (2017)
    <p>Streaming network data of various forms arises in many applications, raising interest in research to model and quantify the nature of stochasticity and structure in dynamics underlying such data. One example context is ...
  • Irie, Kaoru (2016)
    <p>The advances in three related areas of state-space modeling, sequential Bayesian learning, and decision analysis are addressed, with the statistical challenges of scalability and associated dynamic sparsity. The key ...
  • Li, Yingbo (2013)
    <p>With the development of modern data collection approaches, researchers may collect hundreds to millions of variables, yet may not need to utilize all explanatory variables available in predictive models. Hence, choosing ...
  • Johndrow, James Edward (2016)
    <p>Many modern applications fall into the category of "large-scale" statistical problems, in which both the number of observations n and the number of features or parameters p may be large. Many existing methods focus on ...
  • Crawford, Lorin Anthony (2017)
    <p>The main contribution of this thesis is to examine the utility of kernel regression ap- proaches and variance component models for solving complex problems in statistical genetics and molecular biology. Many of these ...
  • Soriano, Jacopo (2015)
    <p>Two-sample comparison is a fundamental problem in statistics. Given two samples of data, the interest lies in understanding whether the two samples were generated by the same distribution or not. Traditional two-sample ...
  • Schwartz, Scott Lee (2010)
    <p>This thesis examines causal inference related topics involving intermediate variables, and uses Bayesian methodologies to advance analysis capabilities in these areas. First, joint modeling of outcome variables with ...
  • Zhong, Jianling (2015)
    <p>As fundamental structural units of the chromatin, nucleosomes are involved in virtually all aspects of genome function. Different methods have been developed to map genome-wide nucleosome positions, including MNase-seq ...
  • Wang, Jianyu (2013)
    <p>The first part of the thesis focuses on the development of Bayesian modeling motivated by geophysics applications. In Chapter 2, we model the frequency of pyroclastic flows collected from the Soufriere Hills volcano. ...
  • Shirota, Shinichiro (2017)
    <p>This thesis focuses on solving some problems associated with complex spatial point patterns from each modeling and computational perspective. Chapter 1 reviews spatial point patterns and introduces repulsive point ...
  • Cui, Kai (2012)
    <p>Multivariate or high-dimensional data with mixed types are ubiquitous in many fields of studies, including science, engineering, social science, finance, health and medicine, and joint analysis of such data entails both ...