Applied Statistics Commons^™

A Generative Statistical Approach For Data Classification In A Biologically Inspired Design Tool, Marvin Manuel Arroyo Rujano

Graduate Theses and Dissertations

The objective of the research this thesis describes is to find a way to classify text-based descriptions of biological adaption to support Biologically Inspired design. Biologically inspired design is a fairly new field with ongoing research. There are different tools to assist designers and biologists in bio-inspired design. Some of the most common are BioTRIZ and AskNature. In recent years, more tools have been proposed to aid and make research in the field easier, for example, the Biologically Inspired Adaptive System Design (BIASD) tool. This tool was designed with the goal of helping designers in early design stages generate more …

Sequential Inference For Hidden Markov Models, Michael Ellis

Graduate Theses and Dissertations

In many applications data are collected sequentially in time with very short time intervals between observations. If one is interested in using new observations as they arrive in time then non-sequential Bayesian inference methods, such as Markov Chain Monte Carlo (MCMC) sampling, can be too slow. Increasingly, state space models are being used to model nonlinear and non-Gaussian systems. The structure of state space models allows for sequential Bayesian inference so that an approximation to the posterior distribution of interest can be updated as new observations arrive. In special cases, the exact posterior distribution can be updated through conjugate Bayesian …

Spatio-Temporal Reconstruction Of Remote Sensing Observations, Kamrul Khan

Graduate Theses and Dissertations

The USDA Forest Service aims to use satellite imagery for monitoring and predicting changes in forest conditions over time within the country. We specifically focus on a 230, 400 hectares region in north-central Wisconsin between 2003 - 2012. The auxiliary data collected from the satellite imagery of this region are relatively dense in space and time and can be used to efficiently predict how the forest condition changed over that decade. However, these records have a significant proportion of missing values due to weather conditions and system failures. To fill in these missing values, we build spaciotemporal models based on …

Comparison Of Correlation, Partial Correlation, And Conditional Mutual Information For Interaction Effects Screening In Generalized Linear Models, Ji Li

Graduate Theses and Dissertations

Numerous screening techniques have been developed in recent years for genome-wide association studies (GWASs) (Moore et al., 2010). In this thesis, a novel model-free screening method was developed and validated by an extensive simulation study. Many screening methods were mainly focused on main effects, while very few studies considered the models containing both main effects and interaction effects. In this work, the interaction effects were fully considered and three different methods (Pearson’s Correlation Coefficient, Partial Correlation, and Conditional Mutual Information) were tested and their prediction accuracies were compared.

Pearson’s Correlation Coefficient method, which is a direct interaction screening (DIS) procedure, …

A Bayesian Variable Selection Method With Applications To Spatial Data, Xiahan Tang

Graduate Theses and Dissertations

This thesis first describes the general idea behind Bayes Inference, various sampling methods based on Bayes theorem and many examples. Then a Bayes approach to model selection, called Stochastic Search Variable Selection (SSVS) is discussed. It was originally proposed by George and McCulloch (1993). In a normal regression model where the number of covariates is large, only a small subset tend to be significant most of the times. This Bayes procedure specifies a mixture prior for each of the unknown regression coefficient, the mixture prior was originally proposed by Geweke (1996). This mixture prior will be updated as data becomes …

Monte Carlo Methods In Bayesian Inference: Theory, Methods And Applications, Huarui Zhang

Graduate Theses and Dissertations

Monte Carlo methods are becoming more and more popular in statistics due to the fast development of efficient computing technologies. One of the major beneficiaries of this advent is the field of Bayesian inference. The aim of this thesis is two-fold: (i) to explain the theory justifying the validity of the simulation-based schemes in a Bayesian setting (why they should work) and (ii) to apply them in several different types of data analysis that a statistician has to routinely encounter. In Chapter 1, I introduce key concepts in Bayesian statistics. Then we discuss Monte Carlo Simulation methods in detail. Our …

Statistical Modeling Of The Temporal Dynamics In A Large Scale-Citation Network, Luis Javier Ek Jr.

Graduate Theses and Dissertations

Citation Networks of papers are vast networks that grow over time. The manner or the form a citation network grows is not entirely a random process, but a preferential attachment relationship; highly cited papers are more likely to be cited by newly published papers. The result is a network whose degree distribution follows a power law. This growth of citation network of papers will be modeled with a negative binomial regression coupled with logistic growth and/or Cauchy distribution curve. Then a Barabasi-Albert model, based on the negative binomial models, and a combination of the Dirichlet distribution and multinomial will be …

Identification Of Biomarkers For The Overall Survival Of Ovarian Cancer Patients, Kristi Mai

Graduate Theses and Dissertations

Rapid advance in sequencing technology has led to genome-wide analysis of genetic and epigenetic features simultaneously, making it possible to understand the biological mechanisms underlying cancer initiation and progression. However, how to identify important prognostic features poses a great challenge for both statistical modeling and computing. In this thesis, a network-based approach is applied to the Cancer Genome Atlas (TCGA) ovarian cancer data to identify important genes related to the overall survival of ovarian cancer patients. In the first step, a stepwise correlation-based selector is used to reduce the dimensionality of TCGA data, by filtering out a large number of …

Risk Estimation Toward A Natural History Model For Low Grade Glioma Patients, Anh Thi Hoang Pham

Graduate Theses and Dissertations

Glioma is a common type of primary brain tumor that represents 28% of all brain tumors and 80% of malignant tumors. According to a recent study by the Centers for Disease Control and Prevention (CDC), gliomas account for 53%, 35% and 29% of all brain tumors (68%, 74% and 81% of malignant brain tumors) among children (aged 0-14), teenagers (aged 15-19) and young adults, respectively. Gliomas are often diagnosed through radiological imaging and histopathology. There are two main groups of gliomas following World Health Organization’s classification: Low grade gliomas (LGG), or grade I and II gliomas; and high grade gliomas …

Spread Trading In Corn Futures Market, Ryan D. Napier

Graduate Theses and Dissertations

The non-linear relationship between old crop – new crop year spreads in corn futures market and stock-to-use (S-U) ratios published by the United States Department of Agriculture is analyzed. Using a non-linear logarithmic smooth transition regression (LSTR) model, we capture asymmetric market behaviors in high and low S-U regimes. Capturing this relationship and understanding the non-linear aspects of the relationship is of interest of grain merchandizers and speculators in the market. A spread trading strategy is simulated for the sample period, January 1985 through April 2015, to determine if the non-linear relationship is a profitable arbitrage opportunity in the market.

Calorimetry And Body Composition Research In Broilers And Broiler Breeders, Justina Victoria Caldas Cueva

Graduate Theses and Dissertations

Indirect calorimetry to study heat production (HP) and dual energy X-ray absorptiometry (DEXA) for body composition (BC) are powerful techniques to study the dynamics of energy and protein utilization in poultry. The first two chapters present the BC (dry matter, lean, protein, and fat, bone mineral, calcium and phosphorus) of modern broilers from 1 – 60 d of age analyzed by chemical analysis and DEXA. DEXA has been validated for precision, standardized for position, and equations and validations developed for chickens under two different feeding levels. These equations are unique to the machine and software in use. Research in broilers …

Probabilistic Graphical Modeling On Big Data, Ming-Hua Chung

Graduate Theses and Dissertations

The rise of Big Data in recent years brings many challenges to modern statistical analysis and modeling. In toxicogenomics, the advancement of high-throughput screening technologies facilitates the generation of massive amount of biological data, a big data phenomena in biomedical science. Yet, researchers still heavily rely on key word search and/or literature review to navigate the databases and analyses are often done in rather small-scale. As a result, the rich information of a database has not been fully utilized, particularly for the information embedded in the interactive nature between data points that are largely ignored and buried. For the past …

A Decision Support Tool For Appointment Scheduling To Reduce Patient No-Show Rate In An Outpatient Psychiatric Clinic, Kaitlyn N. Thomas

Industrial Engineering Undergraduate Honors Theses

The Walker Family Clinic in the Psychiatric Research Institute at the University of Arkansas for Medical Sciences in Little Rock, Arkansas provides general and specialty mental health and substance abuse services for adolescents and adults. As there is an increasing need for health services at the clinic, the current capacity may not be able to meet all demands. Patients may wait a long time before receiving care due to inefficiencies in the current system. Also, based on data collected from August 1, 2013 to November 26, 2014, the average daily no-show rate was 13.9% and the maximum daily no-show rate …

Analytical Comparison Of Contrasting Approaches To Estimating Competing Risks Models, Brian Stephen Rickard

Graduate Theses and Dissertations

Survival analysis is a commonly used tool in many fields but has seen little use in education research despite a common number of research questions for which it is well suited. Researchers often use logistic regression instead; however, this omits useful information. In research on retention and graduation for example, the timing of the event is an important piece of information omitted when using logistic regression. A simulation study was conducted to evaluate four methods of analyzing competing risks survival data, Cox proportional hazards regression, Weibull regression, Fine and Gray's Method, and Cox proportional hazards regression with frailty. College student …

Poisson Distributed Individuals Control Charts With Optimal Limits, Negin Enayaty Ahangar

Graduate Theses and Dissertations

The conventional method used in attribute control charts is the Shewhart three sigma limits. The implicit assumption of the Normal distribution in this approach is not appropriate for skewed distributions such as Poisson, Geometric and Negative Binomial. Normal approximations perform poorly in the tail area of the these distributions. In this research, a type of attribute control chart is introduced to monitor the processes that provide count data. The economic objective of this chart is to minimize the cost of its errors which is determined by the designer. This objective is a linear function of type I and II errors. …

An Economic Alternative To The C Chart, Ryan William Black

Graduate Theses and Dissertations

Because the probability of Type I error is not evenly distributed beyond upper and lower three-sigma limits the c chart is theoretically inappropriate for a monitor of Poisson distributed phenomena. Furthermore, the normal approximation to the Poisson is of little use when c is small. These practical and theoretical concerns should motivate the computation of true error rates associated with individuals control assuming the Poisson distribution. An economic alternative to the c chart is described as a statistical model of upward shift from c0 to c1 and the two charts are compared in theory. For a range of c chart …

Investigating The Sensitivity Of Goodness-Of-Fit Indices To Detect Measurement Invariance In The Bifactor Model, Jam Khojasteh

Graduate Theses and Dissertations

A Monte Carlo simulation study was conducted to evaluate the sensitivities of five commonly used goodness-of-fit indices to detect metric invariance properties of the bifactor model. The fit indices that performed the best in terms of power were Gamma and Mc. In addition, Gamma, Mc, CFI, and RMSEA all held Type I error to a minimum. However, only Gamma and CFI are recommended to use in the bifactor model because the other GOF indices have cutoff values that are too large. For Gamma and CFI values of -.026 to -.045 and -.004 to -.009, respectively indicate a lack of metric …

The Relationship Of Quarterback Stability And Success In The Nfl, Jeffrey Wittke

Management Undergraduate Honors Theses

This thesis was developed using a research study of all 32 organizations in the National Football League. Information was specifically gathered on the number of quarterbacks each team has used from 2002-2011. Along with that, additional data including winning percentage, total wins, Super Bowl appearances, Super Bowl victories, and number of head coaches was compiled. The teams were then split up into two separate groups based on the number of QBs they have had. The purpose of this research was to determine if there were statistically significant differences in the winning percentages, championships, and number of head coaches between teams …

Comparative Analysis Of Forecasting Techniques With Intermittent Demand, John Deforest

Industrial Engineering Undergraduate Honors Theses

The world and life are filled with uncertainty. Statistics, and more specifically, forecasting techniques allow us to quantify uncertainty and make decisions based on that information. Many find forecasting advantageous in areas such as predicting consumer demand, stock prices, terrorist attacks, epidemiology, etc. This thesis will focus on forecasting intermittent demand, which is the study of analyzing sporadic demand. One application includes an airplane manufacturer’s sporadic or intermittent demand for spare parts in their distribution center. Since spare parts are not needed on any regular schedule, it is thought of as intermittent. Knowing the projected quantity for a given time …

Identifying Minimum G Aberration Designs For Hadamard Matrices Of Order 28, Steffany Belcher-Novosad, Debra Ingram

Journal of the Arkansas Academy of Science

No abstract provided.

Curing A Summing Error That Occurs Automatically When Fitting A Function To Binomial Or Poisson Distributed Data, Edwin S. Braithwaite, Wilfred J. Braithwaite

Journal of the Arkansas Academy of Science

Without special precautions a sum-rule error occurs automatically when a chi-squared procedure is used to fit a funtion to binomial or Poisson distributed histogram data if the function has at least one linear parameter. Since the square of the variance per channel is equal to the mean population, errors are usually approximated using (G2~=yi>0)}; this choice for approximating the variance gives a per-channel error weighting of 1/yi that automatically results in a sum-rule error. This sum-rule error consistently and systematically underestimates the total sum of the data points by an amount equal to the value of %*, resulting in …