Statistics and Probability Commons^™

Using Spatiotemporal Methods To Fill Gaps In Energy Usage Interval Data, Kristin K. Graves

Theses and Dissertations

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

Second Order Inference For The Mean Of A Variable Missing At Random, Ivan Diaz, Marco Carone, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We present a second order estimator of the mean of a variable subject to missingness, under the missing at random assumption. The estimator improves upon existing methods by using an approximate second order expansion of the parameter functional, in addition to the first order expansion employed by standard doubly robust methods. This results in weaker assumptions about the convergence rates necessary to establish consistency, local efficiency, and asymptotic linearity. The general estimation strategy is developed under the targeted minimum loss based estimation (TMLE) framework. We present a simulation comparing the sensitivity of the first and second order estimators to the …

Bayesian Model For Antarctic Accumulation And Proposing Field Measurement, Philip White, Shane Reese

Journal of Undergraduate Research

Antarctica’s significance to the global climate is due to the vast amounts of water stored in its ice sheet. Indeed, its ice sheet stores enough water to increase the global sea level by about 200 feet if it were to melt. Even though radical climate change could not melt the entire Antarctic ice sheet for thousands of years, smaller, more realistic changes would still make a significant impact in the global climate, sea level, and growing seasons. For this reason, climatologists and geologists model water accumulation and loss over the Antarctic ice sheet. Accumulation, as defined here, is the net …

Image Segmentation Using Fuzzy-Spatial Taxon Cut, Lauren Barghout

MODVIS Workshop

Images convey multiple meanings that depend on the context in which the viewer perceptually organizes the scene. This presents a problem for automated image segmentation, because it adds uncertainty to the process of selecting which objects to include or not include within a segment. I’ll discuss the implementation of a fuzzy-logic-natural-vision-processing engine that solves this problem by assuming the scene architecture prior to processing. The scene architecture, a standardized natural-scene-perception-taxonomy comprised of a hierarchy of nested spatial-taxons. Spatial-taxons are regions (pixel-sets) that are figure-like, in that they are perceived as having a contour, are either `thing-like', or a `group of …

Two Essays In Financial Economics, Kyle J. Putnam

LSU New Orleans Theses and Dissertations

The following dissertation contains two distinct empirical essays which contribute to the overall field of Financial Economics. Chapter 1, entitled “The Determinants of Dynamic Dependence: An Analysis of Commodity Futures and Equity Markets,” examines the determinants of the dynamic equity-commodity return correlations between five commodity futures sub-sectors (energy, foods and fibers, grains and oilseeds, livestock, and precious metals) and a value-weighted equity market index (S&P 500). The study utilizes the traditional DCC model, as well as three time-varying copulas: (i) the normal copula, (ii) the student’s t copula, and (iii) the rotated-gumbel copula as dependence measures. Subsequently, the determinants of …

A Hierarchical Bayesian Model For The Unmixing Analysis Of Compositional Data Subject To Unit-Sum Constraints, Shiyong Yu

LSU New Orleans Theses and Dissertations

Modeling of compositional data is emerging as an active area in statistics. It is assumed that compositional data represent the convex linear mixing of definite numbers of independent sources usually referred to as end members. A generic problem in practice is to appropriately separate the end members and quantify their fractions from compositional data subject to nonnegative and unit-sum constraints. A number of methods essentially related to polytope expansion have been proposed. However, these deterministic methods have some potential problems.

In this study, a hierarchical Bayesian model was formulated, and the algorithms were coded in MATLAB^Ò. A test …

Video Event Understanding With Pattern Theory, Fillipe Souza, Sudeep Sarkar, Anuj Srivastava, Jingyong Su

MODVIS Workshop

We propose a combinatorial approach built on Grenander’s pattern theory to generate semantic interpretations of video events of human activities. The basic units of representations, termed generators, are linked with each other using pairwise connections, termed bonds, that satisfy predefined relations. Different generators are specified for different levels, from (image) features at the bottom level to (human) actions at the highest, providing a rich representation of items in a scene. The resulting configurations of connected generators provide scene interpretations; the inference goal is to parse given video data and generate high-probability configurations. The probabilistic structures are imposed using energies that …

Metacognition: Using Confidence Ratings For Type 2 And Type 1 Roc Curves, S A. Klein

MODVIS Workshop

In the past five years there has been a surge of renewed interest in metacognition ("thinking about thinking"). The typical experiment involves a binary judgment followed by a multilevel confidence rating. It is a confusing topic because the rating could be made either on one's confidence in the binary response (standard rating Type 1 ROC) or on one's confidence sorted by whether the response was correct (Type 2 ROC). Both are metacognition. After a few remarks on challenging aspects of the Type 2 approach, I will present some interesting results for Type 1 ROC for both memory and vision research. …

Binocular 3d Motion Perception As Bayesian Inference, Martin Lages, Suzanne Heron

MODVIS Workshop

The human visual system encodes monocular motion and binocular disparity input before it is integrated into a single 3D percept. Here we propose a geometric-statistical model of human 3D motion perception that solves the aperture problem in 3D by assuming that (i) velocity constraints arise from inverse projection of local 2D velocity constraints in a binocular viewing geometry, (ii) noise from monocular motion and binocular disparity processing is independent, and (iii) slower motions are more likely to occur than faster ones. In two experiments we found that instantiation of this Bayesian model can explain perceived 3D line motion direction under …

Adaptive Pre-Specification In Randomized Trials With And Without Pair-Matching, Laura B. Balzer, Mark J. Van Der Laan, Maya L. Petersen

U.C. Berkeley Division of Biostatistics Working Paper Series

In randomized trials, adjustment for measured covariates during the analysis can reduce variance and increase power. To avoid misleading inference, the analysis plan must be pre-specified. However, it is unclear a priori which baseline covariates (if any) should be included in the analysis. Consider, for example, the Sustainable East Africa Research in Community Health (SEARCH) trial for HIV prevention and treatment. There are 16 matched pairs of communities and many potential adjustment variables, including region, HIV prevalence, male circumcision coverage and measures of community-level viral load. In this paper, we propose a rigorous procedure to data-adaptively select the adjustment set …

Double Robust Estimation Of Encouragement-Design Intervention Effects Transported Across Sites, Kara E. Rudolph, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

We develop double robust targeted maximum likelihood estimators (TMLE) for transporting intervention effects from one population to another. Specifically, we develop TMLE estimators for three transported estimands: intent-to-treat average treatment effect (ATE) and complier ATE, which are relevant for encouragement-design interventions and instrumental variable analyses, and the ATE of the exposure on the outcome, which is applicable to any randomized or observational study. We demonstrate finite sample performance of these TMLE estimators using simulation, including in the presence of practical violations of the positivity assumption. We then apply these methods to the Moving to Opportunity trial, a multi-site, encouragement-design intervention …

The Effects Of Quantitative Easing In The United States: Implications For Future Central Bank Policy Makers, Matthew Q. Rubino

Senior Honors Projects, 2010-2019

The purpose of this thesis is to examine the effects of the Federal Reserve’s recent bond buying programs, specifically Quantitative Easing 1, Quantitative Easing 2, Operation Twist (or the Fed’s Maturity Extension Program), and Quantitative Easing 3. In this study, I provide a picture of the economic landscape leading up to the deployment of the programs, an overview of quantitative easing including each program’s respective objectives, and how and why the Fed decided to implement the programs. Using empirical analysis, I measure each program’s effectiveness by applying four models including a yield curve model, an inflation model, a money supply …

Stochastic Optimization Via Forward Slice, Bob A. Salim, Lurdes Y. T. Inoue

UW Biostatistics Working Paper Series

Optimization consists of maximizing or minimizing a real-valued objective function. In many problems, the objective function may not yield closed-form solutions. Over many decades, optimization methods, both deterministic and stochastic, have been developed to provide solutions to these problems. However, some common limitations of these methods are the sensitivity to the initial value and that often current methods only find a local (non-global) extremum. In this article, we propose an alternative stochastic optimization method, which we call "Forward Slice", and assess its performance relative to available optimization methods.

Expectations For Methodology And Translation Of Animal Research: A Survey Of Health Care Workers, Ari Joffe, Meredith Bara, Natalie Anton, Nathan Nobis

Experimentation Collection

Background: Health care workers (HCW) often perform, promote, and advocate use of public funds for animal research (AR); therefore, an awareness of the empirical costs and benefits of animal research is an important issue for HCW. We aim to determine what health-care-workers consider should be acceptable standards of AR methodology and translation rate to humans.

Methods: After development and validation, an e-mail survey was sent to all pediatricians and pediatric intensive care unit nurses and respiratory-therapists (RTs) affiliated with a Canadian University. We presented questions about demographics, methodology of AR, and expectations from AR. Responses of pediatricians and nurses/RTs were …

The Effects Of A Planned Missingness Design On Examinee Motivation And Psychometric Quality, Matthew S. Swain

Dissertations, 2014-2019

Assessment practitioners in higher education face increasing demands to collect assessment and accountability data to make important inferences about student learning and institutional quality. The validity of these high-stakes decisions is jeopardized, particularly in low-stakes testing contexts, when examinees do not expend sufficient motivation to perform well on the test. This study introduced planned missingness as a potential solution. In planned missingness designs, data on all items are collected but each examinee only completes a subset of items, thus increasing data collection efficiency, reducing examinee burden, and potentially increasing data quality. The current scientific reasoning test served as the Long …

Examining The Performance Of The Metropolis-Hastings Robbins-Monro Algorithm In The Estimation Of Multilevel Multidimensional Irt Models, Bozhidar M. Bashkov

Dissertations, 2014-2019

The purpose of this study was to review the challenges that exist in the estimation of complex (multidimensional) models applied to complex (multilevel) data and to examine the performance of the recently developed Metropolis-Hastings Robbins-Monro (MH-RM) algorithm (Cai, 2010a, 2010b), designed to overcome these challenges and implemented in both commercial and open-source software programs. Unlike other methods, which either rely on high-dimensional numerical integration or approximation of the entire multidimensional response surface, MH-RM makes use of Fisher’s Identity to employ stochastic imputation (i.e., data augmentation) via the Metropolis-Hastings sampler and then apply the stochastic approximation method of Robbins and Monro …

Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito

Masters Theses, 2010-2019

The critically endangered James Spinymussel (Pleurobema collina) is a species of freshwater mussel endemic to Virginia’s James and Dan River basins. In the last 20 years, P. collina has experienced a substantial decline in numbers and currently occupies approximately 10% of its original habitat; however, little information is known about this species to assist in conservation. A 230-meter reach of transitional habitat in Swift Run was selected for repeat observations to estimate detection probabilities using a Capture-Mark-Recapture framework. In June 2014, visual scouting began to locate and tag P. collina (including other mussels in the community) with PIT …

Distance Correlation Measures Applied To Analyze Relation Between Variables In Liver Cirrhosis Marker Data, Atanu Bhattacharjee Dr.

COBRA Preprint Series

Distance Correlation is another newer choice to compute the relation between variables. However, the Bayesian counterpart of Distance Correlation is not established. In this paper, Bayesian counterpart of Distance Correlation is pro- posed. Proposed method is illustrated with Liver Chirrhosis Marker data. The relevant studies information about relation between AST and ALT is used to formulate the prior information for Bayesian computation. The Distance Correlation between AST and ALT (both are liver performance marker) is computed with 0.44. The credible interval is observed with (0.41, 0.46).Bayesian counter- part to compute Distance correlation is simple and handy.

No-Arbitrage Option Pricing And The Binomial Asset Pricing Model, Nicholas S. Hurley

Honors College Theses

Financial markets often employ the use of securities, which are defined to be any kind of tradable financial asset. Common types of securities include stocks and bonds. A particular type of security, known as a derivative security (or simply, a derivative), are financial instruments whose value is derived from another underlying security or asset (such as a stock). A common kind of derivative is an option, which is a contract that gives the holder the right but not the obligation to go through with the terms of said contract. An example of an option is the European Option, which we …

Directed Energy For Relativistic Propulsion And Interstellar Communications, Philip Lubin, Gary Hughes, J Bible, Isabella Johansson

Statistics

An orbital planetary defense system that is also capable of beamed power propulsion allows mildly relativistic spacecraft speeds using existing technologies. While designed to heat the surface of potentially hazardous objects to the evaporation point to mitigate asteroid threats the system is inherently multi-functional with one mode being relativistic beamed spacecraft propulsion. The system is called DE-STAR for Directed Energy Solar Targeting of Asteroids and exploRation. DE-STAR is a proposed orbital platform that is a modular phased array of lasers, powered by the sun. Modular design allows for incremental development, test and initial deployment, lowering cost, minimizing risk and allowing …