Applied Statistics Commons^™

Analysis Of Ranked Gene Tree Probability Distributions Under The Coalescent Process For Detecting Anomaly Zones, Anastasiia Kim

Shared Knowledge Conference

In phylogenetic studies, gene trees are used to reconstruct species tree. Under the multispecies coalescent model, gene trees topologies may differ from that of species trees. The incorrect gene tree topology (one that does not match the species tree) that is more probable than the correct one is termed anomalous gene tree (AGT). Species trees that can generate such AGTs are said to be in the anomaly zone (AZ). In this region, the method of choosing the most common gene tree as the estimate of the species tree will be inconsistent and will converge to an incorrect species tree when …

Development And Internal Validation Of An Aneurysm Rupture Probability Model Based On Patient Characteristics And Aneurysm Location, Morphology, And Hemodynamics, Felicitas J. Detmer, Bong Jae Chung, Fernando Mut, Martin Slawski, Farid Hamzei-Sichani, Christopher Putman, Carlos Jiménez, Juan R. Cebral

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

Purpose: Unruptured cerebral aneurysms pose a dilemma for physicians who need to weigh the risk of a devastating subarachnoid hemorrhage against the risk of surgery or endovascular treatment and their complications when deciding on a treatment strategy. A prediction model could potentially support such treatment decisions. The aim of this study was to develop and internally validate a model for aneurysm rupture based on hemodynamic and geometric parameters, aneurysm location, and patient gender and age. Methods: Cross-sectional data from 1061 patients were used for image-based computational fluid dynamics and shape characterization of 1631 aneurysms for training an aneurysm rupture probability …

Statistical Investigation Of Road And Railway Hazardous Materials Transportation Safety, Amirfarrokh Iranitalab

Department of Civil and Environmental Engineering: Dissertations, Theses, and Student Research

Transportation of hazardous materials (hazmat) in the United States (U.S.) constituted 22.8% of the total tonnage transported in 2012 with an estimated value of more than 2.3 billion dollars. As such, hazmat transportation is a significant economic activity in the U.S. However, hazmat transportation exposes people and environment to the infrequent but potentially severe consequences of incidents resulting in hazmat release. Trucks and trains carried 63.7% of the hazmat in the U.S. in 2012 and are the major foci of this dissertation. The main research objectives were 1) identification and quantification of the effects of different factors on occurrence and …

Crustal Seismic Anisotropy Of The Ruby Mountains Core Complex And Surrounding Northern Basin And Range, Justin T. Wilgus

Earth and Planetary Sciences ETDs

Metamorphic core complexes (MCC) are distinctive uplifts that expose deeply exhumed and deformed crustal rocks due to localized extensional deformation. Consequently, their detailed structure provide a window into deep crustal mechanics. The North American Cordillera contains numerous MCC, one of which is the Ruby Mountains core complex (RMCC) located in the highly extended northern Basin and Range. To constrain the extent to which anisotropy below the RMCC deviates from the regional Basin and Range average and test the depth dependence of crustal anisotropy we conduct a radial anisotropy investigation below the RMCC and surrounding northern Basin and Range. Data from …

Probabilities Involving Standard Trirectangular Tetrahedral Dice Rolls, Rulon Olmstead, Doneliezer Baize

Rose-Hulman Undergraduate Mathematics Journal

The goal is to be able to calculate probabilities involving irregular shaped dice rolls. Here it is attempted to model the probabilities of rolling standard tri-rectangular tetrahedral dice on a hard surface, such as a table top. The vertices and edges of a tetrahedron were projected onto the surface of a sphere centered at the center of mass of the tetrahedron. By calculating the surface areas bounded by the resultant geodesics, baseline probabilities were achieved. Using a 3D printer, dice were constructed of uniform density and the results of rolling them were recorded. After calculating the corresponding confidence intervals, the …

Quantitative Appraisal Of Non-Irrigated Cropland In South Dakota, Shelby Riggs

Honors Program: Senior Projects (Public)

This appraisal attempts to remove subjectivity from the appraisal process and replace it with quantitative analysis of known data to generate a fair market value of the subject property. Two methods of appraisal were used, the income approach and the comparable sales approach. For the income approach, I used the average cash rent for the region, the current property taxes for the subject property, and a capitalization rate based on Stokes' (2018) capitalization rate formula to arrive at my income-based valuation. For the comparable sales approach, I utilized Stokes' (2018) research in optimization modeling to estimate a market value for …

Using Cyclical Components To Improve The Forecasts Of The Stock Market And Macroeconomic Variables, Kenneth R. Szulczyk, Shibley Sadique

Journal of Modern Applied Statistical Methods

Economic variables such as stock market indices, interest rates, and national output measures contain cyclical components. Forecasting methods excluding these cyclical components yield inaccurate out-of-sample forecasts. Accordingly, a three-stage procedure is developed to estimate a vector autoregression (VAR) with cyclical components. A Monte Carlo simulation shows the procedure estimates the parameters accurately. Subsequently, a VAR with cyclical components improves the root-mean-square error of out-of-sample forecasts by 50% for a stock market model with macroeconomic variables.

Understanding Sexual Violence Against Women, Maria Martinez

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Season-Ahead Forecasting Of Water Storage And Irrigation Requirements – An Application To The Southwest Monsoon In India, Arun Ravindranath, Naresh Devineni, Upmanu Lall, Paulina Concha Larrauri

Publications and Research

Water risk management is a ubiquitous challenge faced by stakeholders in the water or agricultural sector. We present a methodological framework for forecasting water storage requirements and present an application of this methodology to risk assessment in India. The application focused on forecasting crop water stress for potatoes grown during the monsoon season in the Satara district of Maharashtra. Pre-season large-scale climate predictors used to forecast water stress were selected based on an exhaustive search method that evaluates for highest ranked probability skill score and lowest root-mean-squared error in a leave-one-out cross-validation mode. Adaptive forecasts were made in the years …

Identification Of Hostile Hemodynamics And Geometries Of Cerebral Aneurysms: A Case-Control Study, Bong Jae Chung, F. Mut, C. M. Putman, F. Hamzei-Sichani, W. Brinjikji, D. Kallmes, C. M. Jimenez, Juan R. Cebral

Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works

BACKGROUND AND PURPOSE: Hostile hemodynamic conditions and geometries are thought to predispose aneurysms for instability and rupture. This study compares stable, unstable, and ruptured aneurysms while controlling for location and patient characteristics. MATERIALS AND METHODS: The hemodynamics and geometries of 165 stable, 65 unstable, and 554 ruptured aneurysms were compared. Hemodynamics was modeled using image-based computational fluid dynamics. Case-control pairs were selected matching aneurysm location, patient age, and sex. Paired Wilcoxon tests were used to compare hemodynamic and geometric variables among different aneurysm groups. The pairing was repeated 100 times, and the combined P values were calculated and adjusted for …

Statistical Design Of Experiment Techniques In Manufacturing, Caroline M. Kerfonta

Senior Theses

There are many statistical techniques used to design experiments. These techniques are used in many different fields. This thesis will focus on the use of the three most common techniques used to design statistical experiments in manufacturing.

The three techniques that will be investigated are completely randomized design, randomized block design, and factorial design. These techniques will be compared, contrasted, and explained. Research examples will be presented along with sample R code for each technique. These examples will be accompanied by analysis of the techniques as well as an overview of the uses and history of experiments in manufacturing

Habitat Preferences Of Blue Marlin (Makaira Nigricans) And Black Marlin (Istiompax Indica) In The Eastern Pacific Ocean, Nima Farchadi, Michael G. Hinton, Andrew R. Thompson, Zhi-Yong Yin

Theses

Overexploitation and climate change can reduce the abundance and shift the spatial distribution of marine species. Determining the habitat suitability of a mobile pelagic species, such as Makaira nigricans (BUM) and Istiompax indica (BLM), can help describe their spatiotemporal distribution patterns over a broad spatial scale, which is a crucial need for fisheries management. Using 14 years (1997-2010) of Inter-American Tropical Tuna Commission (IATTC) catch data from purse-seine vessels in the eastern Pacific Ocean (EPO), we modeled the dynamic habitat suitability of BUM and BLM in response to environmental variables within the EPO using a species distribution model (MaxEnt) with …

Comparison Of Multiple Imputation Methods For Categorical Survey Items With High Missing Rates: Application To The Family Life, Activity, Sun, Health And Eating (Flashe) Study, Benmei Liu, Erin Hennessy, April Oh, Laura A. Dwyer, Linda Nebeling

Journal of Modern Applied Statistical Methods

Two multiple imputation methods, the Sequential Regression Multivariate Imputation Algorithm and the Cox-Lannacchione Weighted Sequential Hotdeck, were examined and compared to impute highly missing categorical variables from the Family Life, Activity, Sun, Health and Eating (FLASHE) study. This paper describes the imputation approaches and results from the study.

Dealing With Sensitive Quantitative Variables: A Comparison Of Sampling Designs For The Procedure Of Gupta And Thornton, Carlos Narciso Bouza Herrera, Prayas Sharma

Journal of Modern Applied Statistical Methods

The use of randomized response procedures allows diminishing the number of non-responses and increasing the accuracy of the responses. A new sampling strategy is developed where the reports are scrambled using the procedure of Gupta and Thornton. The estimator of the mean as well as the errors are developed for the Rao-Hartley-Cochran and Ranked Sets Sampling designs. The proposals are compared with the original model based on the use of simple random sampling.

Bayesian And Semi-Bayesian Estimation Of The Parameters Of Generalized Inverse Weibull Distribution, Kamaljit Kaur, Kalpana K. Mahajan, Sangeeta Arora

Journal of Modern Applied Statistical Methods

Bayesian and semi-Bayesian estimators of parameters of the generalized inverse Weibull distribution are obtained using Jeffreys’ prior and informative prior under specific assumptions of loss function. Using simulation, the relative efficiency of the proposed estimators is obtained under different set-ups. A real life example is also given.

Random Forest Vs Logistic Regression: Binary Classification For Heterogeneous Datasets, Kaitlin Kirasich, Trace Smith, Bivin Sadler

SMU Data Science Review

Selecting a learning algorithm to implement for a particular application on the basis of performance still remains an ad-hoc process using fundamental benchmarks such as evaluating a classifier’s overall loss function and misclassification metrics. In this paper we address the difficulty of model selection by evaluating the overall classification performance between random forest and logistic regression for datasets comprised of various underlying structures: (1) increasing the variance in the explanatory and noise variables, (2) increasing the number of noise variables, (3) increasing the number of explanatory variables, (4) increasing the number of observations. We developed a model evaluation tool capable …

Predicting National Basketball Association Success: A Machine Learning Approach, Adarsh Kannan, Brian Kolovich, Brandon Lawrence, Sohail Rafiqi

SMU Data Science Review

In this paper, we present a machine learning based approach to projecting the success of National Basketball Association (NBA) draft prospects. With the proliferation of data, analytics have increasingly be- come a critical component in the assessment of professional and collegiate basketball players. We leverage player biometric data, college statistics, draft selection order, and positional breakdown as modelling features in our prediction algorithms. We found that a player's draft pick and their college statistics are the best predictors of their longevity in the National Basketball Association.

Yelp’S Review Filtering Algorithm, Yao Yao, Ivelin Angelov, Jack Rasmus-Vorrath, Mooyoung Lee, Daniel W. Engels

SMU Data Science Review

In this paper, we present an analysis of features influencing Yelp's proprietary review filtering algorithm. Classifying or misclassifying reviews as recommended or non-recommended affects average ratings, consumer decisions, and ultimately, business revenue. Our analysis involves systematically sampling and scraping Yelp restaurant reviews. Features are extracted from review metadata and engineered from metrics and scores generated using text classifiers and sentiment analysis. The coefficients of a multivariate logistic regression model were interpreted as quantifications of the relative importance of features in classifying reviews as recommended or non-recommended. The model classified review recommendations with an accuracy of 78%. We found that reviews …

Cryptocurrency Price Prediction Using Tweet Volumes And Sentiment Analysis, Jethin Abraham, Daniel Higdon, John Nelson, Juan Ibarra

SMU Data Science Review

In this paper, we present a method for predicting changes in Bitcoin and Ethereum prices utilizing Twitter data and Google Trends data. Bitcoin and Ethereum, the two largest cryptocurrencies in terms of market capitalization represent over \$160 billion dollars in combined value. However, both Bitcoin and Ethereum have experienced significant price swings on both daily and long term valuations. Twitter is increasingly used as a news source influencing purchase decisions by informing users of the currency and its increasing popularity. As a result, quickly understanding the impact of tweets on price direction can provide a purchasing and selling advantage to …

Of Typicality And Predictive Distributions In Discriminant Function Analysis, Lyle W. Konigsberg, Susan R. Frankenberg

Human Biology Open Access Pre-Prints

While discriminant function analysis is an inherently Bayesian method, researchers attempting to estimate ancestry in human skeletal samples often follow discriminant function analysis with the calculation of frequentist-based typicalities for assigning group membership. Such an approach is problematic in that it fails to account for admixture and for variation in why individuals may be classified as outliers, or non-members of particular groups. This paper presents an argument and methodology for employing a fully Bayesian approach in discriminant function analysis applied to cases of ancestry estimation. The approach requires adding the calculation, or estimation, of predictive distributions as the final step …