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Articles 511 - 540 of 595
Full-Text Articles in Statistics and Probability
Continuous And Discrete Models For Optimal Harvesting In Fisheries, Nagham Abbas Al Qubbanchee
Continuous And Discrete Models For Optimal Harvesting In Fisheries, Nagham Abbas Al Qubbanchee
Masters Theses
"This work focuses on the logistic growth model, where the Gordon-Schaefer model is considered in continuous time. We view the Gordon-Schaefer model as a bioeconomic equation involved in the fishing business, considering biological rates, carrying capacity, and total marginal costs and revenues. In [25], the authors illustrate the analytical solution of the Schaefer model using the integration by parts method and two theorems. The theorems have many assumptions with many different strategies. Due to the nature of the problem, the optimal control system involves many equations and functions, such as the second root of the equation. We concentrate on Theorem …
Investigaion Of The Gamma Hurdle Model For A Single Population Mean, Alissa Jacobs
Investigaion Of The Gamma Hurdle Model For A Single Population Mean, Alissa Jacobs
Electronic Theses and Dissertations
A common issue in some statistical inference problems is dealing with a high frequency of zeroes in a sample of data. For many distributions such as the gamma, optimal inference procedures do not allow for zeroes to be present. In practice, however, it is natural to observe real data sets where nonnegative distributions would make sense to model but naturally zeroes will occur. One example of this is in the analysis of cost in insurance claim studies. One common approach to deal with the presence of zeroes is using a hurdle model. Most literary work on hurdle models will focus …
Non-Inferiority Testing: Kernel Estimation And Overlap Measure, Larie C. Ward
Non-Inferiority Testing: Kernel Estimation And Overlap Measure, Larie C. Ward
College of Graduate Studies: Theses & Dissertations
In non-inferiority testing, the decision of whether a proposed treatment is non-inferior to a reference treatment depends on model assumptions and choices of acceptable tolerance limits. Here, we consider a method that employs kernels to estimate the probability density functions of both the experimental and reference populations from two independent samples. Based on these densities, we introduce a quantity called the overlap coefficient or overlap measure. A bootstrap technique is helpful in exploring the distribution and variance empirically. We derive the distribution of this measure and define a hypothesis test that can be applied to the non-inferiority setting under some …
Modelling Muscle Activation Using Emg Signal, Mercy U. Okonna
Modelling Muscle Activation Using Emg Signal, Mercy U. Okonna
College of Graduate Studies: Theses & Dissertations
(EMG) is a method for measuring muscle activity by an electrical signal, and is useful in studying motor control, postural control, and in physical therapy. A current research topic is creating an algorithm that can use the EMG signal to reliably classify a muscle as active or inactive. This thesis presents a classification algorithm for leg muscles with a single activation spike while walking. Time is rescaled into steps, which are identified using data from cameras measuring joint angles while walking. The algorithm is based on moving averages and a convex combination of mean signal strength in active and inactive …
Colonial Markets, Consumers, And Trade: A Comparative Analysis Of Historic Ceramics From The Bluefields Bay Area, Westmoreland, Jamaica, Lacy Risner
Murray State Theses and Dissertations
The ceramic assemblages from a British colonial settlement in Bluefields Bay, Jamaica, provide a unique window into the market availability, exchange routes, and consumption patterns of the eighteenth century. This study compares the historic ceramics collected from two sites in Bluefields Bay to one another and to other intra-island (Jamaica), intraregional (Lesser Antilles), and international (North America) colonial and postcolonial sites to reveal patterns of individual and global ceramic consumption and distribution in the emergent capitalist networks and markets of the colonial era. Integrating small British colonial sites into the networks of other more extensive studies focusing primarily on plantations …
Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris
Approximating Bayesian Optimal Sequential Designs Using Gaussian Process Models Indexed On Belief States, Joseph Burris
Theses and Dissertations
Fully sequential optimal Bayesian experimentation can offer greater utility than both traditional Bayesian designs and greedy sequential methods, but practically cannot be solved due to numerical complexity and continuous outcome spaces. Approximate solutions can be found via approximate dynamic programming, but rely on surrogate models of the expected utility at each trial of the experiment with hand-chosen features or use methods which ignore the underlying geometry of the space of probability distributions. We propose the use of Gaussian process models indexed on the belief states visited in experimentation to provide utility-agnostic surrogate models for approximating Bayesian optimal sequential designs which …
Using Deep Neural Networks To Analyze Precision Agriculture Data, Stephanie Liebl
Using Deep Neural Networks To Analyze Precision Agriculture Data, Stephanie Liebl
Electronic Theses and Dissertations
As the population of the Earth increases, there is a growing need for food to feed the inhabitants. Precision agriculture offers techniques and tools that can be used to help accommodate the growing population. One specific precision agriculture tool is remote sensing data, which can be used to image fields as an effort to better predict or understand the crops. In this thesis, deep neural networks are used to evaluate various spatial, spectral, and temporal resolutions of three different satellite images to determine which best predicts corn yield. The main metrics we used to evaluate the models were R-squared (R2), …
Finding The Best Predictors For Foot Traffic In Us Seafood Restaurants, Isabel Paige Beaulieu
Finding The Best Predictors For Foot Traffic In Us Seafood Restaurants, Isabel Paige Beaulieu
Honors Theses and Capstones
COVID-19 caused state and nation-wide lockdowns, which altered human foot traffic, especially in restaurants. The seafood sector in particular suffered greatly as there was an increase in illegal fishing, it is made up of perishable goods, it is seasonal in some places, and imports and exports were slowed. Foot traffic data is useful for business owners to have to know how much to order, how many employees to schedule, etc. One issue is that the data is very expensive, hard to get, and not available until months after it is recorded. Our goal is to not only find covariates that …
Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar
Using Short Bursts To Optimize Redistricting In Georgia, Vedika Vishweshwar
CMC Senior Theses
Identifying extreme outliers in large state spaces is a difficult prob-
lem. I consider this problem in the context of finding political district-
ing plans that maximize the number of districts in which the majority
of the population is from a minority group, such as African Americans.
Since the set of all possible districting plans is enormous and unfeasi-
ble to examine in practice, this paper proposes a sampling method to
find these outlying plans. Specifically, this paper experiments with short
bursts in the context of minority voting rights in Georgia. Short bursts
are a type of Markov Chain in …
Sampling Distribution Of Non-Overlap Indices Using Bootstrapping Procedure : A Monte Carlo Simulation Study And Empirical Demonstration, Xinyun Xu
Legacy Theses & Dissertations (2009 - 2024)
Statistics can be either parametric or non-parametric, depending on whether distributional assumptions about the data and sampling distributions are required. Parametric and non-parametric approaches each include a variety of inferential methods. These methods can be seen in the field of single-case experimental design (SCED). By reviewing one of the most used groups of statistics for SCED research (Jamshidi et al., 2022; Maggin et al., 2011), the non-overlap indices, one major issue arose. It is challenging to make inferences and interpretations about non-overlap indices. The main reason for this issue is that non-overlap indices have inconsistent and unknown sampling distributions (under …
Maximum Likelihood Estimator Method To Estimate Flaw Parameters For Different Glass Types, Nabhajit Goswami
Maximum Likelihood Estimator Method To Estimate Flaw Parameters For Different Glass Types, Nabhajit Goswami
Dissertations, Master's Theses and Master's Reports
Glass is commonly used in architectural applications, such as windows and in-fill panels and structural applications, such as beams and staircases. Despite the popularity of structural glass use in buildings, an engineering design standard to determine the required component or member strength for design loads does not exist. Glass is a brittle material that lacks a well-defined yield or ultimate stress, unlike ductile materials. The traditional engineering methods used to design a ductile material cannot be used to design a glass component. Glass fails in tension primarily due to the presence of microscopic flaws present on the surface that acts …
The Role Of Health Expenditure On Health Outcomes: Evidence In West Africa Countries., Festus Efosa Eriamiatoe
The Role Of Health Expenditure On Health Outcomes: Evidence In West Africa Countries., Festus Efosa Eriamiatoe
Graduate Research Theses & Dissertations
This study investigates the role of health expenditure on health outcomes in West Africa countries. Using the Grossman theoretical framework, other variables that affect health outcomes were also examined. Sixteen countries of West Africa with yearly data spanning between the period of 19 years (2000-2019) was used in this study. The health outcomes examined include life expectancy and neonatal and under-5 mortality rates. The regressors used in the study include domestic government health expenditure per capita, domestic private health expenditure per capita, external health expenditure per capita, carbon-dioxide emission metric ton per capita, human immunodeficiency virus (HIV), unemployment, GDP per …
A Simple And Robust Alternative To Bland-Altman Method Of Assessing Clinical Agreement, Abhaya Indrayan Prof
A Simple And Robust Alternative To Bland-Altman Method Of Assessing Clinical Agreement, Abhaya Indrayan Prof
COBRA Preprint Series
Clinical agreement between two quantitative measurements on a group of subjects is generally assessed with the help of the Bland-Altman (B-A) limits. These limits only describe the dispersion of disagreements in 95% cases and do not measure the degree of agreement. The interpretation regarding the presence or absence of agreement by this method is based on whether B-A limits are within the pre-specified externally determined clinical tolerance limits. Thus, clinical tolerance limits are necessary for this method. We argue in this communication that the direct use of clinical tolerance limits for assessing agreement without the B-A limits is more effective …
Review Of Copula For Bivariate Distributions Of Zero-Inflated Count Time Series Data, Dimuthu Fernando, Mohammed Alqawba, Manar Samad, Norou Diawara
Review Of Copula For Bivariate Distributions Of Zero-Inflated Count Time Series Data, Dimuthu Fernando, Mohammed Alqawba, Manar Samad, Norou Diawara
Mathematics & Statistics Faculty Publications
The class of bivariate integer-valued time series models, described via copula theory, is gaining popularity in the literature because of applications in health sciences, engineering, financial management and more. Each time series follows a Markov chain with the serial dependence captured using copula-based distribution functions from the Poisson and the zero-inflated Poisson margins. The copula theory is again used to capture the dependence between the two series.
However, the efficiency and adaptability of the copula are being challenged because of the discrete nature of data and also in the case of zero-inflation of count time series. Likelihood-based inference is used …
Methods Of Anomaly Detection: An Applied Framework And Application To Health Economics, Nathaniel Eric Islip
Methods Of Anomaly Detection: An Applied Framework And Application To Health Economics, Nathaniel Eric Islip
EWU Masters Thesis Collection
No abstract provided.
Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng
Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng
Theses and Dissertations--Statistics
Radiogenomics is a new direction in cancer research that focuses on the associations among radiomics, genomics and clinical outcome. Currently, the major challenge for Radiogenomics lies in the effective integration of genomics and imaging data for promising clinical outcome prediction. Herein, we propose a multivariate joint model that can integrate imaging and genomic data for better predicting the clinical outcome. Specifically, we jointly consider two multivariate group lasso models, one regresses imaging features on genomic features, and the other regresses patient’s clinical outcome on genomic features. An L1 penalty term is introduced for each variable, and weight in the penalty …
Statistical Theory For Specialized Linear Regression Adjustment Methods Compared To Multiple Linear Regression In The Presence And Absence Of Interaction Effects, Leon Su
Theses and Dissertations--Statistics
When building models to investigate outcomes and variables of interest, researchers often want to adjust for other variables. There is a variety of ways that these adjustments are performed. In this work, we will consider four approaches to adjustment utilized by researchers in various fields. We will compare the efficacy of these methods to what we call the ”true model method”, fitting a multiple linear regression model in which adjustment variables are model covariates. Our goal is to show that these adjustment methods have inferior performance to the true model method by comparing model parameter estimates, power, type I error, …
Deriving The Distributions And Developing Methods Of Inference For R2-Type Measures, With Applications To Big Data Analysis, Gregory S. Hawk
Deriving The Distributions And Developing Methods Of Inference For R2-Type Measures, With Applications To Big Data Analysis, Gregory S. Hawk
Theses and Dissertations--Statistics
As computing capabilities and cloud-enhanced data sharing has accelerated exponentially in the 21st century, our access to Big Data has revolutionized the way we see data around the world, from healthcare to investments to manufacturing to retail and supply-chain. In many areas of research, however, the cost of obtaining each data point makes more than just a few observations impossible. While machine learning and artificial intelligence (AI) are improving our ability to make predictions from datasets, we need better statistical methods to improve our ability to understand and translate models into meaningful and actionable insights.
A central goal in the …
Beta Mixture And Contaminated Model With Constraints And Application With Micro-Array Data, Ya Qi
Beta Mixture And Contaminated Model With Constraints And Application With Micro-Array Data, Ya Qi
Theses and Dissertations--Statistics
This dissertation research is concentrated on the Contaminated Beta(CB) model and its application in micro-array data analysis. Modified Likelihood Ratio Test (MLRT) introduced by [Chen et al., 2001] is used for testing the omnibus null hypothesis of no contamination of Beta(1,1)([Dai and Charnigo, 2008]). We design constraints for two-component CB model, which put the mode toward the left end of the distribution to reflect the abundance of small p-values of micro-array data, to increase the test power. A three-component CB model might be useful when distinguishing high differentially expressed genes and moderate differentially expressed genes. If the null hypothesis above …
Addressing Ascertainment Bias In The Study Of Cardiovascular Disease Burden In Opioid Use Disorders - Application Of Natural Language Processing Of Electronic Health Records, Jade Huang Singleton
Addressing Ascertainment Bias In The Study Of Cardiovascular Disease Burden In Opioid Use Disorders - Application Of Natural Language Processing Of Electronic Health Records, Jade Huang Singleton
Theses and Dissertations--Epidemiology and Biostatistics
In the United States, the prevalence of long-term exposure to opioid drugs, for both medically and nonmedically indicated purposes, has increased considerably since the mid-1990’s. Concerns have emerged about the potential health effects of opioid use. There is also growing interest in other possible connections with opioid use including cardiovascular disease. Electronic health records (EHR) contain information about patient care in the form of structured codes and unstructured notes. Natural language processing (NLP) provides a tool for processing unstructured textual data in EHR clinical notes and extracts useful information for research with structured formats. The purpose of this dissertation was …
Opioid Use Disorder Treatment With Buprenorphine: Analysis Of Treatment Utilization And Associated Outcomes In Kentucky, Feitong Lei
Theses and Dissertations--Epidemiology and Biostatistics
Opioid use disorder (OUD) is chronic opioid use that results in clinically significant suffering, impairment, or even death. The opioid epidemic in the United States has become a public health and economic crisis, affecting patients' well-being and the nation's overall health and welfare. Eastern Kentucky was among the first regions affected by the opioid crisis, and Kentucky has historically ranked among the top five states for age-adjusted drug overdose mortality rate.
There are three medications (buprenorphine, methadone, naltrexone) approved by the U.S. Food and Drug Administration to treat OUD. As a partial opioid agonist, buprenorphine is a safe medication for …
Framework For The Evaluation Of Perturbations In The Systems Biology Landscape And Inter-Sample Similarity From Transcriptomic Datasets — A Digital Twin Perspective, Mariah Marie Hoffman
Framework For The Evaluation Of Perturbations In The Systems Biology Landscape And Inter-Sample Similarity From Transcriptomic Datasets — A Digital Twin Perspective, Mariah Marie Hoffman
Dissertations and Theses
One approach to interrogating the complexities of human systems in their well-regulated and dysregulated states is through the use of digital twins. Digital twins are virtual representations of physical systems that are descriptive of an individual's state of health, an object fundamentally related to precision medicine. A key element for building a functional digital twin type for a disease or predicting the therapeutic efficacy of a potential treatment is harmonized, machine-parsable domain knowledge. Hypothesis-driven investigations are the gold standard for representing subsystems, but their results encompass a limited knowledge of the full biosystem. Multi-omics data is one rich source of …
Perception Of Health Care Access In Rural Georgia: Findings From A Community Health Needs Assessment Survey, Elisa M. Childs, Tiffany R. Washington
Perception Of Health Care Access In Rural Georgia: Findings From A Community Health Needs Assessment Survey, Elisa M. Childs, Tiffany R. Washington
Journal of the Georgia Public Health Association
Background: Limited access to health care services has been cited as a barrier to care for individuals who live in rural areas, contributing to significant health disparities in this population. While perception of services has been cited as a determinant of utilization of health services, it is unknown how perception of services influences health care access in rural areas. The paucity of studies specific to areas in the United States that are medically underserved, necessitated this study and its quantification of the issues that are relevant to individuals living in rural Georgia.
Methods: This study examined the perception of health …
Think-Aloud Interviews: A Tool For Exploring Student Statistical Reasoning, A. Reinhart, C. Evans, Amanda Luby, J. Orellana, M. Meyer, J. Wieczorek, P. Elliott, P. Burckhardt, R. Nugent
Think-Aloud Interviews: A Tool For Exploring Student Statistical Reasoning, A. Reinhart, C. Evans, Amanda Luby, J. Orellana, M. Meyer, J. Wieczorek, P. Elliott, P. Burckhardt, R. Nugent
Mathematics & Statistics Faculty Works
Think-aloud interviews have been a valuable but underused tool in statistics education research. Think-alouds, in which students narrate their reasoning in real time while solving problems, differ in important ways from other types of cognitive interviews and related education research methods. Beyond the uses already found in the statistics literature—mostly validating the wording of statistical concept inventory questions and studying student misconceptions—we suggest other possible use cases for think-alouds and summarize best-practice guidelines for designing think-aloud interview studies. Using examples from our own experiences studying the local student body for our introductory statistics courses, we illustrate how research goals should …
A Simple Algorithm For Generating A New Two Sample Type-Ii Progressive Censoring With Applications, E. M. Shokr, Rashad Mohamed El-Sagheer, Mahmoud Mansour, H. M. Faied, B. S. El-Desouky
A Simple Algorithm For Generating A New Two Sample Type-Ii Progressive Censoring With Applications, E. M. Shokr, Rashad Mohamed El-Sagheer, Mahmoud Mansour, H. M. Faied, B. S. El-Desouky
Basic Science Engineering
In this article, we introduce a simple algorithm to generating a new type-II progressive censoring scheme for two samples. It is observed that the proposed algorithm can be applied for any continues probability distribution. Moreover, the description model and necessary assumptions are discussed. In addition, the steps of simple generation algorithm along with programming steps are also constructed on real example. The inference of two Weibull Frechet populations are discussed under the proposed algorithm. Both classical and Bayesian inferential approaches of the distribution parameters are discussed. Furthermore, approximate confidence intervals are constructed based on the asymptotic distribution of the maximum …
Identifying Patterns In The Structural Drivers Of Intrastate Conflict, Jonathan D. Moyer, Austin S. Matthews, Mickey Rafa, Yutang Xiong
Identifying Patterns In The Structural Drivers Of Intrastate Conflict, Jonathan D. Moyer, Austin S. Matthews, Mickey Rafa, Yutang Xiong
Global and Public Affairs: Faculty Scholarship
Quantitative methods have been used to: (1) better predict civil conflict onset; and (2) understand causal mechanisms to inform policy intervention and theory. However, an exploration of individual conflict onset cases illustrates great variation in the characteristics describing the outbreak of civil war, suggesting that there is not one single set of factors that lead to intrastate war. In this article, we use descriptive statistics to explore persistent clusters in the drivers of civil war onset, finding evidence that some arrangements of structural drivers cluster robustly across multiple model specifications (such as young, poorly developed states with anocratic regimes). Additionally, …
Realtime Event Detection In Sports Sensor Data With Machine Learning, Mallory Cashman
Realtime Event Detection In Sports Sensor Data With Machine Learning, Mallory Cashman
Honors Theses and Capstones
Machine learning models can be trained to classify time series based sports motion data, without reliance on assumptions about the capabilities of the users or sensors. This can be applied to predict the count of occurrences of an event in a time period. The experiment for this research uses lacrosse data, collected in partnership with SPAITR - a UNH undergraduate startup developing motion tracking devices for lacrosse. Decision Tree and Support Vector Machine (SVM) models are trained and perform with high success rates. These models improve upon previous work in human motion event detection and can be used a reference …
Data, Knowledge Practices, And Naturecultural Worlds: Vehicle Emissions In The Anthropocene, Lindsay Poirier
Data, Knowledge Practices, And Naturecultural Worlds: Vehicle Emissions In The Anthropocene, Lindsay Poirier
Statistical and Data Sciences: Faculty Books
This chapter details the various techno-cultural assemblages giving rise to data collected to model and measure anthropogenic worlds, arguing that data-based technologies both represent and co-produce the Anthropocene. It begins with a review of scholarship emerging at the intersection of science and technology studies and information studies that advances understanding of data infrastructure and knowledge practices, and their role within the anthropogenic assemblages that shape history. Drawing on a case study describing how vehicle emissions are measured and regulated in the US, I examine the materialities and mutability of technologies designed to produce data about air quality, along with the …
Ga Pilot Perceptions Of Speech Systems To Transcribe And Submit Pireps, Deborah S. Carstens Ph.D., Pmp, Michael S. Harwin, J.D., M.S., Tianhua Li, Ph.D., Brandon J. Pitts, Ph.D., Mel Futrell, M.A., Barrett Caldwell, Ph.D.
Ga Pilot Perceptions Of Speech Systems To Transcribe And Submit Pireps, Deborah S. Carstens Ph.D., Pmp, Michael S. Harwin, J.D., M.S., Tianhua Li, Ph.D., Brandon J. Pitts, Ph.D., Mel Futrell, M.A., Barrett Caldwell, Ph.D.
International Journal of Aviation, Aeronautics, and Aerospace
Flying into hazardous weather can be a cause of aviation incidents and accidents. Accidents involving general aviation (GA) pilots who are not instrument rated who fly into instrument meteorological conditions (IMC) are often fatal. Pilot weather reports (PIREPs) can increase the accuracy and timeliness of current and forecasted weather conditions. They are an essential tool used by pilots to avoid flying into hazardous weather as well as meteorologists to develop and update aviation forecasts. Thus, a large number of accurate PIREPs with the best source of current weather coming from pilots and air traffic controllers are needed. Pilots are often …
Mindfulness And Pain Regulation: The Role Of Acceptance And Commitment Therapy For Individuals With Chronic Pain, Ariana C. White
Mindfulness And Pain Regulation: The Role Of Acceptance And Commitment Therapy For Individuals With Chronic Pain, Ariana C. White
Honors Theses and Capstones
Chronic pain is a significant and widely prevalent health condition which requires comprehensive care to address the many facets contributing to symptomatology. In 2016, 20% of American adults (about 50 million) reported experiencing chronic pain, of which 7.4% indicated that chronic pain frequently limited their life and participation in activities within the past 3 months (CDC, 2018). As a result, many individuals with chronic pain turn to opioid-based medication for pain relief, but long-term use of opioids actually increases pain sensation (Tobin, 2019). Moreover, opioid medication is unable to target underlying mental health components which emerge as part of chronic …