Now showing items 14-33 of 37

    • Generalization of boosting algorithms and applications of Bayesian inference for massive datasets 

      Ridgeway, Gregory Kirk, 1973- (1999)
      In recent years statisticians, computational learning theorists, and engineers have developed more advance techniques to learn complex non-linear relationships from datasets. However, not only have models increased in ...
    • Generalized linear mixed models: development and comparison of different estimation methods 

      Nelson, Kerrie P (2002)
      The use of generalized linear mixed models is growing in popularity in the modelling of correlated data. To date, methods available are either computationally intensive or asymptotically biased. The following work examines ...
    • Genetic restoration on complex pedigrees 

      Sheehan, Nuala A. (Nuala Ann), 1959- (1990)
      Analyses of genetic data observed on groups of related individuals frequently require the computation of probabilities on pedigrees. Existing methods are computationally intensive and can be infeasible on large and complex ...
    • Gravimetric Anomaly Detection using Compressed Sensing 

      Kappedal, Ryan D.
      We address the problem of identifying underground anomalies (e.g. holes) based on gravity measurements. This is a theoretically well-studied yet difficult problem. In all except a few special cases, the inverse problem has ...
    • Latent models for cross-covariance 

      Wegelin, Jacob A (2001)
      Cross-covariance problems arise in the analysis of multivariate data that can be divided naturally into two blocks of variables, X and Y, observed on the same units. In a cross-covariance problem we are interested, not in ...
    • Learning and Manifolds: Leveraging the Intrinsic Geometry 

      Perrault-Joncas, Dominique Chipman (2013-07-23)
      In this work, we explore and exploit the use of differential operators on manifolds - the Laplace-Beltrami operator in particular - in learning tasks. In particular, we are interested in uncovering the geometric structure ...
    • The Likelihood Pivot: Performing Inference with Confidence 

      Harmon, James Warren
      Maximum likelihood estimation is a popular statistical method. To account for possible model misspecification, the sandwich estimate of variance can be used to generate asymptotically correct confidence intervals. Several ...
    • Lord's Paradox and Targeted Interventions: The Case of Special Education 

      Theobald, Roderick Jenkins
      Lord (1967) describes a hypothetical “paradox” in which two statisticians, analyzing the same dataset using different but defensible methods, come to very different conclusions about the effects of an intervention on student ...
    • Maximum likelihood estimation in Gaussian AMP chain graph models and Gaussian ancestral graph models 

      Drton, Mathias, 1975- (2004)
      Graphical Markov models use graphs to represent dependencies between stochastic variables. Via Markov properties, missing edges in the graph are translated into conditional independence statements, which, in conjunction ...
    • Modeling Heterogeneity within and between Matrices and Arrays 

      Fosdick, Bailey Kathryn (2013-11-14)
      Datasets in the form of matrices and arrays arise frequently in the social and biological sciences and are characterized by measurements indexed by two or more factors. In this dissertation we address two problems relating ...
    • Monte Carlo estimation of identity by descent in populations 

      Glazner, Chris
      Genetic similarity between organisms arises from segments of shared genome, which are said to be identical by descent (IBD). Modeling IBD in pedigrees forms the basis of classical linkage analysis and has been a fruitful ...
    • Monte Carlo likelihood calculation for identity by descent data 

      Browning, Sharon, 1973- (1999)
      Two individuals are identical by descent at a genetic locus if they share the same gene copy at that locus due to inheritance from a recent common ancestor. Identity by descent can be thought of as a continuous process ...
    • Portfolio Optimization with Tail Risk Measures and Non-Normal Returns 

      Zhu, Minfeng (2010-08-20)
      The traditional Markowitz mean-variance portfolio optimization theory uses volatility as the sole measure of risk. However, volatility is flawed both intuitively and theoretically: being symmetric it does not differentiate ...
    • Predictive Modeling of Cholera Outbreaks in Bangladesh 

      Koepke, Amanda Allen
      Despite seasonal cholera outbreaks in Bangladesh, little is known about the relationship between environmental conditions and cholera cases. We seek to develop a predictive model for cholera outbreaks in Bangladesh based ...
    • Probabilistic Population Projection for Countries with Generalized HIV/AIDS Epidemics 

      He, Yanjun
      Population projection has long been an issue for researchers, governments and international organizations so that they can monitor and plan development and resources. The United Nation Population Division (UNPD) publishes ...
    • R-squared inference under non-normal error 

      Xu, Lei
      Assessment of the relationship between diet and health status, especially association between diet and chronic disease risk, has attracted lot of research interest in statistical and epidemiologic studies. However, due to ...
    • R-squared inference under non-normal error 

      Xu, Lei
      Assessment of the relationship between diet and health status, especially association between diet and chronic disease risk, has attracted lot of research interest in statistical and epidemiologic studies. However, due to ...
    • A resampling approach to clustering with confidence 

      Chiam, Yuan (2012-09-13)
      We propose a method for estimating the number of groups in a data set. Our method is an extension of Generalized Single Linkage clustering (GSL) (Stuetzle and Nugent 2010), a nonparametric clustering method based on the ...
    • Robust estimation of factor models in finance 

      Bailer, Heiko Manfred (2005)
      Standard asset-pricing models entail expressions for expected returns in terms of coefficients relative to risk factors. Methods to estimate premiums of risk factors have, at its core, a single or multiple linear regression ...
    • Shape-Constrained Inference for Concave-Transformed Densities and their Modes 

      Doss, Charles R. (2013-11-14)
      We consider inference about functions estimated via shape constraints based on concavity. We consider log-concave densities and other “concave-transformed” densities on the real line, where a concave-transformed class is ...