Statistics and Probability Commons^™

Family-Wise Error Rate Control In Quantitative Trait Loci (Qtl) Mapping And Gene Ontology Graphs With Remarks On Family Selection, Garrett Saunders

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

One of the great aims of statistics, the science of collecting, analyzing, and interpreting data, is to protect against the probability of falsely rejecting an accepted claim, or hypothesis, given observed data stemming from some experiment. This is generally known as protecting against a Type I Error, or controlling the Type I Error rate. The extension of this protection against Type I Errors to the situation where thousands upon thousands of hypothesis are examined simultaneously is known as multiple hypothesis testing. This dissertation presents an improvement to an existing multiple hypothesis testing approach, the Focus Level method, specific to gene …

Beetles, Fungi And Trees: A Story For The Ages? Modeling And Projecting The Multipartite Symbiosis Between The Mountain Pine Beetle, Dendroctonus Ponderosae, And Its Fungal Symbionts, Grosmannia Clavigera And Ophiostoma Montium, Audrey L. Addison

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

As data collection and modeling improve, ecologists increasingly discover that interspecies dynamics greatly affect the success of individual species. Models accounting for the dynamics of multiple species are becoming more important. In this work, we explore the relationship between mountain pine beetle (MPB, Dendroctonus ponderosae Hopkins) and two mutualistic fungi, Grosmannia clavigera and Ophiostoma montium. These species are involved in a multipartite symbiosis, critical to the survival of MPB, in which each species benefits.

Extensive phenological modeling has been done to determine how temperature affects the timing of life events and cold-weather mortality of MPB. The fungi have also …

Computational Topics In Lie Theory And Representation Theory, Thomas J. Apedaile

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The computer algebra system Maple contains a basic set of commands for working with Lie algebras and matrices. The purpose of this thesis was to extend the functionality of these Maple packages in a number of important areas. First, programs for defining multiplication in several different types of algebras were created to allow users to perform a wider variety of calculations. Second, commands were created for calculating some basic properties of matrix representations of semisimple Lie algebras. This allows a user to identify a given matrix representation by a collection of integers which do not change when the basis of …

Physically Based Preconditioning Techniques Applied To The First Order Particle Transport And To Fluid Transport In Porous Media, Michael Rigley

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Solving linear systems is at the heart of many scientific applications from the PreAlgebra's student solving for x and y for basic geometry problems to the computational scientist solving billions of equations with billions of variables for weather forecasting, modeling fusion reactions, or web search algorithms. In this study we look at improving the efficiency of solving large linear systems that result from two applications. The first includes linear systems that result from solving differential equations for the movement of atomic particles in particle emitting, void, and absorbing regions. The second includes solving linear systems that result from solving differential …

Implementation And Application Of The Curds And Whey Algorithm To Regression Problems, John Kidd

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

A common statistical problem is trying to predict two or more variables using a set of predictor variables. The simplest model for this situation is called multivariate linear regression. This method uses each set of predictor variables to predict each of the response variables separately. This approach seems counter-intuitive as any possible relationship between the variables being predicted is ignored.

Breiman and Friedman found a way to take advantage of relationships among the response variables to increase the accuracy of the predictions for each of the predicted variables with an algorithm they called Curds and
Whey. It uses other statistical …

Statistical Modeling, Exploration, And Visualization Of Snow Water Equivalent Data, James Beguah Odei

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Due to a continual increase in the demand for water as well as an ongoing regional drought, there is an imminent need to monitor and forecast water resources in the Western United States. In particular, water resources in the Intermountain West rely heavily on snow water storage. Thus, the need to improve seasonal forecasts of snowpack and considering new techniques would allow water resources to be more effectively managed throughout the entire water-year. Many available models used in forecasting snow water equivalent (SWE) measurements require delicate calibrations.

In contrast to the physical SWE models most commonly used for forecasting, we …

Probability Estimation In Random Forests, Chunyang Li

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Random Forests is a useful ensemble approach that provides accurate predictions for classification, regression and many different machine learning problems. Classification has been a very useful and popular application for Random Forests. However, it is preferable to have the probability of a membership rather than the simple knowledge that one belongs to whichever group. Votes and the regression method are current probability estimation methods that have been developed in Random Forests. In this thesis, we introduce two new methods, proximity weighting and the out-of-bag method, trying to improve the current methods. Several different simulations are designed to evaluate the new …

Enhancement Of Random Forests Using Trees With Oblique Splits, Andrejus Parfionovas

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Statistical classification is widely used in many areas where there is a need to make a data-driven decision, or to classify complicated cases or objects. For instance: disease diagnostics (is a patient sick or healthy, based on the blood test results?); weather forecasting (will there be a storm tomorrow, based on today's atmospheric pressure, air temperature, and wind velocity?); speech recognition (what was said over the phone, based on the caller's voice level and articulation); spam detection (can the unsolicited commercial e-mails be identified by their content?); and so on.

Classification trees …

Statistical Algorithms For Optimal Experimental Design With Correlated Observations, Chang Li

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The first part of my dissertation demonstrates that a modified simulated annealing algorithm can successfully determine highly efficient D-optimal designs for second order polynomial regression for a variety of correlated error structures.

In the second part, I solved weak universal optimal block designs for the nearest neighbor correlation structure and multiple block sizes, for the hub correlation structure with any block size, and for circulant correlation with odd block size.

In the third part, we propose an improved Particle Swarm Optimization (PSO) algorithm with time varying parameters. Then combining the theorem of decision making and PSO, we innovated nested PSO …

Spatially Indexed Functional Data, Oleksandr Gromenko

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The increased concentration of greenhouse gases is associated with the global warming in the lower troposphere. For over twenty years, the space physics community has studied a hypothesis of global cooling in the thermosphere, attributable to greenhouse gases. While the global temperature increase in the lower troposphere has been relatively well established, the existence of global changes in the thermosphere is still under investigation.

A central difficulty in reaching definite conclusions is the absence of data with sufficiently long temporal and sufficiently broad spatial coverage. Time series of data that cover several decades exist only in a few separated (industrialized) …

Applications Of Bayesian Statistics In Fluvial Bed Load Transport, Mark L. Schmelter

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The science of fluvial sediment transport studies the processes involved in the movement of river sediments. It is commonly understood that when rivers flood they have a great capacity to move sand, gravel, and even larger cobbles and boulders. This process is not only limited to the big floods that usually attract so much attention, but also the more common river flows play a very important role in forming a river. As engineers and scientists, we like to be able to develop equations and relationships that describe some natural phenomenon—in this case, fluvial sediment transport. While we are able to …

Empirical Properties Of Functional Regression Models And Application To High-Frequency Financial Data, Xi Zhang

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Functional data analysis (FDA) has grown into a substantial field of statistical research, with new methodology, numerous useful applications and interesting novel theoretical developments. My dissertation focuses on the empirical properties of functional regression models and their application to financial data. We start from testing the empirical properties of forecasts with the functional autoregressive models based on simulated and real data. We define intraday returns and consider their prediction from such returns on a market index. This is an extension to intraday data of the Capital Asset Pricing model. Finally we investigate multifactor functional models and assess their suitability for …

Existence And Multiplicity Results On Standing Wave Solutions Of Some Coupled Nonlinear Schrodinger Equations, Rushun Tian

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Coupled nonlinear Schrodinger equations (CNLS) govern many physical phenomena, such as nonlinear optics and Bose-Einstein condensates. For their wide applications, many studies have been carried out by physicists, mathematicians and engineers from different respects. In this dissertation, we focused on standing wave solutions, which are of particular interests for their relatively simple form and the important roles they play in studying other wave solutions. We studied the multiplicity of this type of solutions of CNLS via variational methods and bifurcation methods.

Variational methods are useful tools for studying differential equations and systems of differential equations that possess the so-called variational …

Curds And Whey: Little Miss Muffit's Contribution To Multivariate Linear Regression, John Cameron Kidd

Undergraduate Honors Capstone Projects

A common multivariate statistical problem is the prediction of two or more response variables using two or more predictor variables. The simplest model for this situation is the multivariate linear regression model. The standard least squares estimation for this model involves regressing each response variable separately on all the predictor variables. Breiman and Friedman [1] show how to take advantage of correlations among the response variables to increase the predictive accuracy for each of the response variable with an algorithm they call Curds and Whey. In this report, I describe an implementation of the Curds and Whey algorithm in …

Visual Data Mining Techniques For Functional Actigraphy Data: An Object-Oriented Approach In R, Abbass Sharif

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Actigraphy, a technology for measuring a subject's overall activity level almost continuously over time, has gained a lot of momentum over the last few years. An actigraph, a watch-like device that can be attached to the wrist or ankle of a subject, uses an accelerometer to measure human movement every minute or even every 15 seconds. Actigraphy data is often treated as functional data. In this dissertation, we discuss what has been done regarding the visualization of actigraphy data, and then we will explain the three main goals we achieved: (i) develop new multivariate visualization techniques for actigraphy data; (ii) …

Assessing Changes In The Abundance Of The Continental Population Of Scaup Using A Hierarchical Spatio-Temporal Model, Beth E. Ross

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

In ecological studies, the goal is often to describe and gain further insight into ecological processes underlying the data collected during observational studies. Because of the nature of observational data, it can often be difficult to separate the variation in the data from the underlying process or 'state dynamics.' In order to better address this issue, it is becoming increasingly common for researchers to use hierarchical models. Hierarchical spatial, temporal, and spatio-temporal models allow for the simultaneous modeling of both first and second order processes, thus accounting for underlying autocorrelation in the system while still providing insight into overall spatial …

Interactive Random Forests Plots, Anna T. Quach

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Random Forests is a useful data mining tool that is quite popular in finding variable importance. However, many people don’t make use of the Random Forests results in interactive graphs. Partly, this is because software packages that can do interactive graphs can’t handle large data sets and those that use Random Forests have large data sets or many variables. A new software package in R, known as iPlots eXtreme, that is still in development makes it simple to explore large data sets interactively. I have created a function, called irfplot (interactive random forests plot) that specifically uses Random Forests to …

Simulating Loan Repayment By The Sinking Fund Method (Sinking Fund Governed By A Sequence Of Interest Rates), Placede Judicaelle Gangnang Fosso

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The sinking fund method is a way to repay a loan where the borrower pays the amount of interest accrued by the principal at the end of each time period and puts a certain amount in a sinking fund in order to repay the principal at the end of the loan. Usually, we assume that the interest rate on the sinking fund is the same during the entire time of the loan. In the study, we will depart from the usual assumptions and will look at different scenarios, including when changes of the interest rate on the sinking fund follows …

Ignoring The Spatial Context In Intro Statistics Classes - And Some Simple Graphical Remedies, Nathan Voge

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Statistical data often have a spatial (geographic) context, be it countries of the world, states in the US, counties within a state, cities across the globe, or locations where measurements have been taken. However, most introductory statistics books do not even suggest that such data often are not independent from location, but rather are eected by some spatial association. Remedies are simple: Display data via various map views and brie y discuss which additional information can be extracted from such a graphical representation. In this report, we will visit a variety of popular introductory statistics textbooks and show how some …

Robust Computational Tools For Multiple Testing With Genetic Association Studies, William L. Welbourn Jr.

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

The mapping of the human genome and the completion of the Human HapMap project over the past decade have significantly altered how research is conducted with respect to the genetic epidemiology of human disease. Study designs and analytic approaches have evolved rapidly from investigations involving relatively few targeted candidate genes to hypothesis-free genome-wide association studies, where thousands – and now even millions – of single molecular mutations are simultaneously analyzed to identify regions of the genome that may influence disease. As laboratory techniques continue to improve and costs decrease, the volume of genetic data will inexorably rise, and robust tools …

Dietary Patterns And Cognitive Decline In Aged Populations, Austin J. Bowles

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

In this paper, we discuss distinctive features of longitudinal studies, and illustrate two regression-based methods for the analysis of longitudinal data. A study of dietary patterns and cognitive decline (Cache County Memory Study) is used to motivate our discussion and analysis. Cognitive decline is a risk factor for Alzheimer’s disease, the sixth leading cause of all deaths among Americans. The study attempted to identify dietary patterns associated with reduced risk of age-related cognitive decline in elderly populations. Higher levels of adherence to the Dietary Approaches to Stop Hypertension (DASH) and/or Mediterranean diets were found to be associated with increased cognitive …

Stressors Across The Lifespan And Dementia Risk: A Statistical Method Analysis, Megan Platt Borrowman

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

The Cache Lifespan Stressors and Alzheimer's Disease (LSAD) study has access to data from the Cache County Study on Memory Health and Aging (CCS) that have been linked to the extensive genealogical and vital records from the Utah Population Database (UPDB). Information about stressful life events experienced by the original 5092 CCS participants has been extracted objectively from the UPDB, without the possibility of recall bias. This information was then statistically analyzed to look for relationships between key stressors and dementia risk. The LSAD study made it possible to examine the correlation between stressors as well as look at patterns …

Collecting, Analyzing And Interpreting Bivariate Data From Leaky Buckets: A Project-Based Learning Unit, Florence Funmilayo Obielodan

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Despite the significance and the emphasis placed on mathematics as a subject and field of study, achieving the right attitude to improve students‟ understanding and performance is still a challenge. Previous studies have shown that the problem cuts across nations around the world, both developing countries and developed alike. Teachers and educators of the subject have responsibilities to continuously develop innovative pedagogical approaches that will enhance students‟ interests and performance. Teaching approaches that emphasize real life applications of the subject have become imperative. It is believed that this will stimulate learners‟ interest in the subject as they will be able …

Climate Change And Community Dynamics: A Hierarchical Bayesian Model Of Resource-Driven Changes In A Desert Rodent Community, Glenda M. Yenni

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Predicting effects of climate change on species persistence often assumes that those species are responding to abiotic effects alone. However, biotic interactions between community members may affect species’ ability to respond to abiotic changes. Latent Gaussian models of resource availability using precipitation and NDVI and accounting for spatial autocorrelation and rodent group-level uncertainty in the process are developed to detect differences in seasons, groups, and the experimental removal of one group. Precipitation and NDVI have overall positive effects on rodent energy use as expected, but meaningful differences were detected. Differences in the importance of seasonality when the dominant group was …

Estimation Of Beta In A Simple Functional Capital Asset Pricing Model For High Frequency Us Stock Data, Yan Zhang

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

This project applies the methods of functional data analysis (FDA) to intra-daily returns of US corporations. It focuses on an extension of the Capital Asset Pricing Model (CAPM) to such returns. The CAPM is essentially a linear regression with the slope coefficient β. Returns of an asset are regressed on index return. We compare the estimates of β obtained for the daily and intra-daily returns. The variability of these estimates is assessed by two bootstrap methods. All computations are performed using statistical software R. Customized functions are developed to process the raw data, estimate the parameters and assess their variability. …

Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

It is a typical feature of high dimensional data analysis, for example a microarray study, that a researcher allows thousands of statistical tests at a time. All inferences for the tests are determined using the p-values; a smaller p-value than the α-level of the test signifies a statistically significant test. As the number of tests increases, the chance of observing some small p-values is very high even when all null hypotheses are true. Consequently, we make wrong conclusions on the hypotheses. This type of potential problem frequently happens when we test several hypotheses simultaneously, i.e., the multiple testing problem. …

Examining Child Sexual Abuse And Future Parenting: An Application Of Latent Class Modeling, Kimberly W. D'Zatko

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

This study was designed to empirically derive latent classes of mothers who were sexually abused during childhood and to assess the association between depression, alcohol/drug use, supportive intimate partner, and specific classes.

One hundred six women between the ages of 20 and 44 years (M = 27) who reported having been sexually abused during childhood (CSA) and 158 non-CSA mothers between the ages of 20 and 43 years (M = 23) were interviewed and assessed along six parenting dimensions. Logistic regression models evaluated the association between psychoemotional variables and specific classes.

The final model consisted of three classes—53.2%, …

On The Use Of Log-Transformation Vs. Nonlinear Regression For Analyzing Biological Power-Laws, Xiao Xiao

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Power-law relationships are among the most well-studied functional relationships in biology . Recently the common practice of fitting power-laws using linear regression on log-transformed data (LR) has been criticized, calling into question the conclusions of hundreds of studies. It has been suggested that nonlinear regression (NLR) is preferable, but no rigorous comparison of these two methods has been conducted. Using Monte Carlo simulations we demonstrate that the error distribution determines which method performs better, with LR better characterizing data with multiplicative lognormal error and NLR better characterizing data with additive normal error. Analysis of 471 biological power-laws shows that both …

Development And Implementation Of A Bayesian Model For Sediment Transport In Fluvial Systems, Mark Schmelter

All Graduate Plan B and other Reports, Spring 1920 to Spring 2023

Recent studies in the field of fluvial sediment transport underscore the difficulty in reliably estimating transport model parameters, collecting accurate observations, and making predictions due to measurement error and conceptual model uncertainty. There is a pressing need to develop models that can account for measurement error, conceptual model uncertainty, and natural variability while providing probability-based predictions as well as a means for conceptual model discrimination. The model presented in this research employs an excess shear sediment transport equation for a uni-size sediment bed developed in a Bayesian statistical framework. This statistical model provides a means to rigorously estimate distributions of …

Psychometric Properties Of Postsecondary Students' Course Evaluations, Michael J. Drysdale

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Several experts in the area of postsecondary student evaluations of courses have concluded that they are stable or reliable measures as well as being measures that provide ways of making valid inferences regarding teacher effectiveness. Often these experts have offered these conclusions without supporting evidence. Surprisingly, a thorough review of the literature revealed very few reported test-retest reliability studies of course evaluations and the results from these studies are contradictory. In the area of validity, the conclusions offered by scholars who conducted meta-analyses of mutlisection course studies are inconsistent. This leads to the following two research questions:

1. What is …