[PAST EVENT] Chris Weld, Applied Science - Ph.D. Dissertation Defense
LocationISC3 (Integrated Science Center), Room 0280
540 Landrum Dr
Williamsburg, VA 23185Map this location
Access & Features
- Open to the public
Title: Computational Graphics and Statistical Analysis: Mixed Type Random Variables, Confidence Regions, and Golden Quantile Rank Sets
Abstract: This dissertation has three principle areas of research: mixed type random variables, confidence regions, and golden quantile rank sets. While each offers a specific focus, some common themes persist; broadly stated, there are three. First, computational graphics play a critical role. Second, software development facilitates implementation and accessibility. Third, statistical analysis---often attributable to the aforementioned automation---provides valuable insights and applications. Each of the principle research areas are briefly summarized next.
Mixed type random variables are a hybrid of continuous and discrete random variables, having components of both continuous probability density and discrete probability mass. This dissertation illustrates the challenges inherent in plotting mixed type distributions, and introduces an algorithm that addresses those issues. It considers sums and products of mixed type random variables, and supports its conclusions using Monte Carlo simulation experiments. Lastly, it introduces MixedAPPL, a computer algebra system software package designed for manipulating mixed type random variables.
Confidence regions are a multi-dimensional version of a confidence interval. They are helpful to visualize and quantify uncertainty surrounding a point estimate. We begin by developing efficient plot algorithms for two-dimensional confidence regions. This research focuses specifically on likelihood-ratio based confidence regions for two-parameter univariate probability models, although the plot techniques are transferable to any two-dimensional setting. The R package 'conf' is introduced, which automates these confidence region plot algorithms for complete and right-censored data sets. Among its benefits, ‘conf' provides access to Monte Carlo simulation experiments for confidence region coverage to an extent not possible previously. The corresponding coverage analysis results include reference tables for the Weibull, normal, and log-logistic distributions. These reference tables yield confidence region plots with exact coverage.
The final topic is the introduction and analysis of a golden quantile rank set (GQRS). The term quantile rank set is used here to denote the population cumulative distribution function values corresponding to a sample. A GQRS can be thought of as “perfectly" representative of their population distribution because samples corresponding to a GQRS result in an estimator(s) matching the associated true population parameter(s). This unique characteristic is not applicable for all estimators and/or distributions, but when present, provides valuable insights and applications. Specifically, applications include an alternative (and at times computationally superior) method for parameter estimation and an exact actual coverage methodology for confidence regions (at times in which currently only estimates exist). Distributions with a GQRS associated with maximum likelihood estimation include the normal, exponential, Weibull, log logistic, and one-parameter exponential power distributions.
Bio: Christopher Weld was born and raised in a suburb of Buffalo, NY. He attended Cornell University where he earned a Bachelor of Science degree in Mechanical Engineering in 2000, and was commissioned into military service as an Army officer. He served assignments with the Special Operations Support Command (Airborne) at Fort Bragg, NC, and the 173rd Airborne Brigade Combat Team in Vicenza, Italy, prior to returning stateside for graduate school. He earned his M.S. in Computational Operations Research from William & Mary in 2010 with a follow-on assignment at the United States Military Academy (USMA) in West Point, NY. Over three years at USMA he taught courses in Mathematical Modeling, Differential Calculus, and Probability and Statistics. He then returned to Virginia where he was assigned to the Training and Doctrine Command, prior to returning to William & Mary in 2016 to pursue his PhD. He is married to the former Christine Jensen, and they have two daughters, Claire and Abigail.