Longitudinal Data Analysis and Time Series Commons^™

Using Hac Estimators For Intervention Analysis, Ashok K. Singh, Rohan J. Dalpatadu

Hospitality Faculty Research

The purpose of this article is to present an alternative method for intervention analysis of time series data that is simpler to use than the traditional method of fitting an explanatory Autoregressive Integrated Moving Average (ARIMA) model. Time series regression analysis is commonly used to test the effect of an event on a time series. An econometric modeling method, which uses a heteroskedasticity and autocorrelation consistent (HAC) estimator of the covariance matrix instead of fitting an ARIMA model, is proposed as an alternative. The method of parametric bootstrap is used to compare the two approaches for intervention analysis. The results …

Zero-Inflated Longitudinal Mixture Model For Stochastic Radiographic Lung Compositional Change Following Radiotherapy Of Lung Cancer, Viviana A. Rodríguez Romero

Theses and Dissertations

Compositional data (CD) is mostly analyzed as relative data, using ratios of components, and log-ratio transformations to be able to use known multivariable statistical methods. Therefore, CD where some components equal zero represent a problem. Furthermore, when the data is measured longitudinally, observations are spatially related and appear to come from a mixture population, the analysis becomes highly complex. For this matter, a two-part model was proposed to deal with structural zeros in longitudinal CD using a mixed-effects model. Furthermore, the model has been extended to the case where the non-zero components of the vector might a two component mixture …

Home Sales As A Time Series Model, Noah R. Hellenthal

Williams Honors College, Honors Research Projects

Rational Expectations Hypothesis is an economic theorem that states that our best way to predict the future is by looking at the past. While this theory is typically used to address inflation, the same concept can be used when predicting future home sales. With the failure of subprime mortgages and the burst of the housing market bubble in 2008, home sales are proven to be an appropriate indication of how the U.S. economy is performing. Through time series analysis, I will be able to construct a model with monthly home sales data from the U.S. Census Bureau. Due to seasonality …

Tropical Cyclone Hazards In Relation To Propagation Speed, Jiehao Huang

Dissertations and Theses

As the population and infrastructure along the US East Coast increase, it becomes increasingly important to study the characteristics of tropical cyclones that can impact the coast. A recent study shows that the propagation speed of tropical cyclones has slowed over the past 60 years, which can lead to greater accumulation of precipitation and greater storm surge impacts. The study presented herein is meant to examine and analyze the relationships that exist between the propagation speed of tropical cyclones, their surface wind strength, displacement angles, and cyclone averaged winds. This analysis is focused on tropical cyclones spanning from 1950-2015 in …

Three Essays On Health Economics And Policy Evaluation, Shishir Shakya

Graduate Theses, Dissertations, and Problem Reports (ETD)

This dissertation consists of three essays on the U.S. Health care policy. Each paragraph below refers to the three abstracts for the three chapters in this dissertation, respectively. I provide quantitative evidence on how much Prescription Drug Monitoring Programs (PDMPs) affects the retail opioid prescribing behaviors. Using the American Community Survey (ACS), I retrieve county-level high dimensional panel data set from 2010 to 2017. I employ three separate identification strategies: difference-in-difference, double selection post-LASSO, and spatial difference-in-difference. I compare how the retail opioid prescribing behaviors of counties, that are mandatory for prescribers to check the PDMP before prescribing controlled substances …

Phenotype Extraction: Estimation And Biometrical Genetic Analysis Of Individual Dynamics, Kevin L. Mckee

Theses and Dissertations

Within-person data can exhibit a virtually limitless variety of statistical patterns, but it can be difficult to distinguish meaningful features from statistical artifacts. Studies of complex traits have previously used genetic signals like twin-based heritability to distinguish between the two. This dissertation is a collection of studies applying state-space modeling to conceptualize and estimate novel phenotypic constructs for use in psychiatric research and further biometrical genetic analysis. The aims are to: (1) relate control theoretic concepts to health-related phenotypes; (2) design statistical models that formally define those phenotypes; (3) estimate individual phenotypic values from time series data; (4) consider hierarchical …

Seasonal Time Series Models With Application To Weather And Lake Level Data, Mengqing Qin

Graduate Theses/Dissertations

This work studies seasonal time series models with application to lake level and weather data. The thesis includes related time series concepts, integrated autoregressive moving average models (abbreviated as ARIMA), parameter estimation, model diagnostics, and forecasting. The studied time series models are applied to the data of daily lake level in Beaver Lake (1988-2017) and the data of daily maximum temperature in New York Central Park (1870-2017). Due to seasonality of the data, three different approaches are proposed to the modeling: regression method, functional ARIMA method and multiplicative seasonal ARIMA method. The forecasted values of the year 2018 are compared …

Diabetes And Its Effect On Abdominal Aortic Aneurysm Growth Rate In Hispanic Patients, Monica Betancourt-Garcia, Kristina Vatcheva, Amrit Thakur, Prateek Gupta, Eugene Postevka, Ricardo Martinez, R. Armour Forse

School of Mathematical & Statistical Sciences Faculty Publications

Background

The growth rate of abdominal aortic aneurysms (AAA) can vary depending on age, baseline diameter, blood pressure, race, and history of smoking. Paradoxically, previous studies show evidence of a protective effect of diabetes on the rate of AAA expansion despite its well-established role in the morbidity and mortality of cardiovascular disease. This study aims to investigate the impact diabetes plays on AAA growth within a Hispanic population.

Methods

Data were collected from patients who were predominantly Mexican-American at a single hospital site. Baseline and follow-up measures for AAA diameter were obtained from serial imaging studies. Demographics, medical history, the …

Predicting Wind Turbine Blade Erosion Using Machine Learning, Casey Martinez, Festus Asare Yeboah, Scott Herford, Matt Brzezinski, Viswanath Puttagunta

SMU Data Science Review

Using time-series data and turbine blade inspection assessments, we present a classification model in order to predict remaining turbine blade life in wind turbines. Capturing the kinetic energy of wind requires complex mechanical systems, which require sophisticated maintenance and planning strategies. There are many traditional approaches to monitoring the internal gearbox and generator, but the condition of turbine blades can be difficult to measure and access. Accurate and cost- effective estimates of turbine blade life cycles will drive optimal investments in repairs and improve overall performance. These measures will drive down costs as well as provide cheap and clean electricity …

Longitudinal Analysis With Modes Of Operation For Aes, Dana Geislinger, Cory Thigpen, Daniel W. Engels

SMU Data Science Review

In this paper, we present an empirical evaluation of the randomness of the ciphertext blocks generated by the Advanced Encryption Standard (AES) cipher in Counter (CTR) mode and in Cipher Block Chaining (CBC) mode. Vulnerabilities have been found in the AES cipher that may lead to a reduction in the randomness of the generated ciphertext blocks that can result in a practical attack on the cipher. We evaluate the randomness of the AES ciphertext using the standard key length and NIST randomness tests. We evaluate the randomness through a longitudinal analysis on 200 billion ciphertext blocks using logistic regression and …

Sample Size Calculation Of Clinical Trials With Correlated Outcomes, Dateng Li

Statistical Science Theses and Dissertations

In this thesis, we investigate sample size calculation for three kinds of clinical trials: (1). Randomized controlled trials (RCTs) with longitudinal count outcomes; (2). Cluster randomized trials (CRTs) with count outcomes; (3). CRTs with multiple binary co-primary endpoints.

Estimation Of Association Between A Longitudinal Marker And Interval-Censored Progression Times, Naghmeh Daneshi

Dissertations and Theses

In longitudinal studies, we observe the subjects who are likely to progress to a new state during the study time. For example, in clinical trials the stage of a progressing disease is recorded at each follow-up visit. The primary goal is to estimate the relationship between the attributes and the subject's progression state. In such studies, some subjects complete all their follow-up visits and their progression state are observed without any missingness. However, others miss their follow-up visits and when they come back, they learn that they have progressed to a new state. In this case, not only are their …

Copula-Based Zero-Inflated Count Time Series Models, Mohammed Sulaiman Alqawba

Mathematics & Statistics Theses & Dissertations

Count time series data are observed in several applied disciplines such as in environmental science, biostatistics, economics, public health, and finance. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this dissertation, we propose two classes of copula-based time series models for zero-inflated counts with the presence of covariates. Zero-inflated Poisson (ZIP), zero-inflated negative binomial (ZINB), and zero-inflated Conway-Maxwell-Poisson (ZICMP) distributed marginals of the …

Field Drilling Data Cleaning And Preparation For Data Analytics Applications, Daniel Cardoso Braga

LSU Master's Theses

Throughout the history of oil well drilling, service providers have been continuously striving to improve performance and reduce total drilling costs to operating companies. Despite constant improvement in tools, products, and processes, data science has not played a large part in oil well drilling. With the implementation of data science in the energy sector, companies have come to see significant value in efficiently processing the massive amounts of data produced by the multitude of internet of thing (IOT) sensors at the rig. The scope of this project is to combine academia and industry experience to analyze data from 13 different …

Bias Reduction In Machine Learning Classifiers For Spatiotemporal Analysis Of Coral Reefs Using Remote Sensing Images, Justin J. Gapper

Computational and Data Sciences (PhD) Dissertations

This dissertation is an evaluation of the generalization characteristics of machine learning classifiers as applied to the detection of coral reefs using remote sensing images. Three scientific studies have been conducted as part of this research: 1) Evaluation of Spatial Generalization Characteristics of a Robust Classifier as Applied to Coral Reef Habitats in Remote Islands of the Pacific Ocean 2) Coral Reef Change Detection in Remote Pacific Islands using Support Vector Machine Classifiers 3) A Generalized Machine Learning Classifier for Spatiotemporal Analysis of Coral Reefs in the Red Sea. The aim of this dissertation is to propose and evaluate a …

Demand Forecasting: An Open-Source Approach, Murtada Shubbar, Jared Smith

SMU Data Science Review

In this paper, we compare demand forecasting methods used by the supply chain department at Bilports to open-source forecasting methods. The design and implementation of the open-source forecasting system also attempts to use several external datasets such as consumer sentiment, housing permit starts, and weather to improve prediction quality. Additionally, the performance of the forecast is evaluated by the reduction of shipment lead times from China, the company’s primary vendor. The objective of our paper is to improve Bilports’s forecasting capabilities. The primary motivation of this paper is to increase forecasting accuracy and identify the weaknesses of the methods used …

Sampling Studies For Longitudinal Functional Data, Toni Jassel

Theses, Dissertations and Culminating Projects

We study the data setting consisting of functional data sets repeatedly observed over time. The focus is on the dynamic prediction of the future trajectory for a subject. Regression methods based on dynamic functional models are used for dynamic prediction of individual trajectories. We propose strategies for the selection of the study sampling design in the context of longitudinal functional data. An application to simulated child growth data is presented. The height-for-age z-score (HAZ) was the response variable in the functional dynamic models for prediction. The intent was to recommend four months for removal in our initial historic data set. …

A Bayesian Framework For Estimating Seismic Wave Arrival Time, Hua Zhong

Graduate Theses and Dissertations

Because earthquakes have a large impact on human society, statistical methods for better studying earthquakes are required. One characteristic of earthquakes is the arrival time of seismic waves at a seismic signal sensor. Once we can estimate the earthquake arrival time accurately, the earthquake location can be triangulated, and assistance can be sent to that area correctly. This study presents a Bayesian framework to predict the arrival time of seismic waves with associated uncertainty. We use a change point framework to model the different conditions before and after the seismic wave arrives. To evaluate the performance of the model, we …

Feasibility Of Multi-Year Forecast For The Colorado River Water Supply: Time Series Modeling, Brian Plucinski

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

The Colorado River is one of the largest resources for water in the United States, as well as being an important asset to the economy. Previous studies have shown a connection between the Great Salt Lake and the Colorado River. This study used time series analysis to build models to predict the water supply of the Colorado River ten years out. These models used data from the Colorado River in addition to Great Salt Lake water elevation. Several models suggest a decline in water supply from 2013 – 2020, before starting to increase. These predictions differ from predictions published by …

Rates Of Relative Sea Level Rise Along The United States East Coast, Jesse N. Beckman, Joseph E. Garcia

Virginia Journal of Science

Recent studies have indicated that some coastal areas, including the East Coast of the United States, are experiencing higher rates of sea level rise than the global average. Rates of relative sea level rise are affected by changes in ocean dynamics, as well as by surface elevation fluctuations due to local land subsidence or uplift. In this study, we derived long-term trends in annual mean relative sea level using tide gauge data obtained from the Permanent Service for Mean Sea Level for stations along the United States East Coast. Stations were grouped by location into the Northeast, Mid-Atlantic, and Southeast …