Physical Sciences and Mathematics Commons^™

A Statistical Model For The Prediction Of Dissolved Oxygen Dynamics And The Potential For Hypoxia In The Mississippi Sound And Bight, Andreas Moshogianis

Master's Theses

Hypoxia events occur when dissolved oxygen concentrations fall below the minimum threshold (dissolved oxygen concentrations < 2 mg O₂ L^-1) necessary to avoid respiratory distress among aquatic organisms. In the Mississippi Sound and Bight, hypoxia is most prevalent from late-spring through late summer. Since hypoxia events can have dramatic effects on coastal fisheries, the spatial and temporal magnitude of hypoxia presents a clear threat to the productive fisheries in the northern Gulf of Mexico. Long-term hydrographic data were collected from eight sampling stations on a monthly basis from January 2009 to December 2011 along a cross-shelf transect from the mouth of …

Predicting Intraday Financial Market Dynamics Using Takens' Vectors; Incorporating Causality Testing And Machine Learning Techniques, Abubakar-Sadiq Bouda Abdulai

Electronic Theses and Dissertations

Traditional approaches to predicting financial market dynamics tend to be linear and stationary, whereas financial time series data is increasingly nonlinear and non-stationary. Lately, advances in dynamical systems theory have enabled the extraction of complex dynamics from time series data. These developments include theory of time delay embedding and phase space reconstruction of dynamical systems from a scalar time series. In this thesis, a time delay embedding approach for predicting intraday stock or stock index movement is developed. The approach combines methods of nonlinear time series analysis with those of causality testing, theory of dynamical systems and machine learning (artificial …

Niche-Based Modeling Of Japanese Stiltgrass (Microstegium Vimineum) Using Presence-Only Information, Nathan Bush

Masters Theses

The Connecticut River watershed is experiencing a rapid invasion of aggressive non-native plant species, which threaten watershed function and structure. Volunteer-based monitoring programs such as the University of Massachusetts’ OutSmart Invasives Species Project, Early Detection Distribution Mapping System (EDDMapS) and the Invasive Plant Atlas of New England (IPANE) have gathered valuable invasive plant data. These programs provide a unique opportunity for researchers to model invasive plant species utilizing citizen-sourced data. This study took advantage of these large data sources to model invasive plant distribution and to determine environmental and biophysical predictors that are most influential in dispersion, and to identify …

Estimation Problems In Complex Field Studies With Deep Interactions: Time-To-Event And Local Regression Models For Environmental Effects On Vital Rates, Krzysztof M. Sakrejda

Doctoral Dissertations

Field studies that measure vital rates in context over extended time periods are a cornerstone of our understanding of population processes. These studies inform us about the relationship between biological process and environmental noise in an irreplaceable way. These data sets bring ``big data'' and ``big model'' challenges, which limit the application of standard software (e.g., \textbf{BUGS}). The environmental sensitivity of vital rates is also expected to exhibit interactions and non-linearity, which typically result in difficult model selection questions in large data sets. Finally, long-term ecological data sets often contain complex temporal structure. In commonly applied discrete-time models complex temporal …

Variable Selection In Single Index Varying Coefficient Models With Lasso, Peng Wang

Doctoral Dissertations

Single index varying coefficient model is a very attractive statistical model due to its ability to reduce dimensions and easy-of-interpretation. There are many theoretical studies and practical applications with it, but typically without features of variable selection, and no public software is available for solving it. Here we propose a new algorithm to fit the single index varying coefficient model, and to carry variable selection in the index part with LASSO. The core idea is a two-step scheme which alternates between estimating coefficient functions and selecting-and-estimating the single index. Both in simulation and in application to a Geoscience dataset, we …

The Impact Of Panama Canal Expansion On The U.S. Gateway Ports’ Attractiveness To The Discretionary Cargo Shippers, Jie Xu

World Maritime University Dissertations

No abstract provided.

The Optimization Research Of Southeast Asian Container Liner Routes Of Sitc Company, Sheng Sheng

World Maritime University Dissertations

No abstract provided.

The Analysis Of Bdti In Tanker Transport Market, Zhisen Wang

World Maritime University Dissertations

No abstract provided.

Research On Port Network Layout From The Perspective Of Sea Ports And Dry Ports Linked Development Under The Background Of “Obor”, Yameng Guo

World Maritime University Dissertations

No abstract provided.

Research On Liner Shipping Schedule Recovery, Xiaye Tang

World Maritime University Dissertations

No abstract provided.

Tropical Cyclone Wind Hazard Assessment For Southeast Part Of Coastal Region Of China, Sihan Li

Electronic Thesis and Dissertation Repository

Tropical cyclone (TC) or typhoon wind hazard and risk are significant for China. The return period value of the maximum typhoon wind speed is used to characterize the typhoon wind hazard and assign wind load in building design code. Since the historical surface observations of typhoon wind speed are often scarce and of short period, the typhoon wind hazard assessment is often carried out using the wind field model and TC track model. For a few major cities in the coastal region of mainland China, simple or approximated wind field models and a circular subregion method (CSM) have been used …

Comparison Of Two Parameter Estimation Techniques For Stochastic Models, Thomas C. Robacker

Electronic Theses and Dissertations

Parameter estimation techniques have been successfully and extensively applied to deterministic models based on ordinary differential equations but are in early development for stochastic models. In this thesis, we first investigate using parameter estimation techniques for a deterministic model to approximate parameters in a corresponding stochastic model. The basis behind this approach lies in the Kurtz limit theorem which implies that for large populations, the realizations of the stochastic model converge to the deterministic model. We show for two example models that this approach often fails to estimate parameters well when the population size is small. We then develop a …

Computational Modeling Of Rna-Small Molecule And Rna-Protein Interactions, Lu Chen

Dissertations & Theses (Open Access)

The past decade has witnessed an era of RNA biology; despite the considerable discoveries nowadays, challenges still remain when one aims to screen RNA-interacting small molecule or RNA-interacting protein. These challenges imply an immediate need for cost-efficient while predictive computational tools capable of generating insightful hypotheses to discover novel RNA-interacting small molecule or RNA-interacting protein. Thus, we implemented novel computational models in this dissertation to predict RNA-ligand interactions (Chapter 1) and RNA-protein interactions (Chapter 2).

Targeting RNA has not garnered comparable interest as protein, and is restricted by lack of computational tools for structure-based drug design. To test the potential …

Modelling Supercomputer Maintenance Interrupts: Maintenance Policy Recommendations, Jagadish Cherukuri

Masters Theses

A supercomputer is a repairable system with large number of compute nodes interconnected to work in harmony to achieve superior computational performance. Reliability of such a complex system depends on an effective maintenance strategy that involves both emergency and preventive maintenance. This thesis analyzes the maintenance records of four supercomputers operational at The National Institute of Computational Science located at Oak Ridge National Laboratory. We propose to use the generalized proportional intensities model (GPIM) to model the maintenance interrupts as it can capture both the reliability parameters and maintenance parameters and allows the inclusion of both emergency and preventive maintenance. …

Statistical Consulting - Senior Project, Cary Hernandez

Statistics

No abstract provided.

Using Spatiotemporal Methods To Fill Gaps In Energy Usage Interval Data, Kristin K. Graves

Theses and Dissertations

Researchers analyzing spatiotemporal or panel data, which varies both in location and over time, often find that their data has holes or gaps. This thesis explores alternative methods for filling those gaps and also suggests a set of techniques for evaluating those gap-filling methods to determine which works best.

Two Essays In Financial Economics, Kyle J. Putnam

University of New Orleans Theses and Dissertations

The following dissertation contains two distinct empirical essays which contribute to the overall field of Financial Economics. Chapter 1, entitled “The Determinants of Dynamic Dependence: An Analysis of Commodity Futures and Equity Markets,” examines the determinants of the dynamic equity-commodity return correlations between five commodity futures sub-sectors (energy, foods and fibers, grains and oilseeds, livestock, and precious metals) and a value-weighted equity market index (S&P 500). The study utilizes the traditional DCC model, as well as three time-varying copulas: (i) the normal copula, (ii) the student’s t copula, and (iii) the rotated-gumbel copula as dependence measures. Subsequently, the determinants of …

Quantitative Techniques For Spread Trading In Commodity Markets, Mir Hashem Moosavi Avonleghi

Electronic Thesis and Dissertation Repository

This thesis investigates quantitative techniques for trading strategies on two commodities, the difference of whose prices exhibits a long-term historical relationship known as mean-reversion. A portfolio of two commodity prices with very similar characteristics, the spread may be regarded as a distinct process from the underlying price processes so deserves to be modeled directly. To pave the way for modeling the spread processes, the fundamental concepts, notions, properties of commodity markets such as the forward prices, the futures prices, and convenience yields are described. Some popular commodity pricing models including both one and two factor models are reviewed. A new …

The Effects Of Quantitative Easing In The United States: Implications For Future Central Bank Policy Makers, Matthew Q. Rubino

Senior Honors Projects, 2010-2019

The purpose of this thesis is to examine the effects of the Federal Reserve’s recent bond buying programs, specifically Quantitative Easing 1, Quantitative Easing 2, Operation Twist (or the Fed’s Maturity Extension Program), and Quantitative Easing 3. In this study, I provide a picture of the economic landscape leading up to the deployment of the programs, an overview of quantitative easing including each program’s respective objectives, and how and why the Fed decided to implement the programs. Using empirical analysis, I measure each program’s effectiveness by applying four models including a yield curve model, an inflation model, a money supply …

Using Capture-Mark-Recapture Techniques To Estimate Detection Probabilities & Fidelity Of Expression For The Critically Endangered James Spinymussel (Pleurobema Collina)., Alaina C. Esposito

Masters Theses, 2010-2019

The critically endangered James Spinymussel (Pleurobema collina) is a species of freshwater mussel endemic to Virginia’s James and Dan River basins. In the last 20 years, P. collina has experienced a substantial decline in numbers and currently occupies approximately 10% of its original habitat; however, little information is known about this species to assist in conservation. A 230-meter reach of transitional habitat in Swift Run was selected for repeat observations to estimate detection probabilities using a Capture-Mark-Recapture framework. In June 2014, visual scouting began to locate and tag P. collina (including other mussels in the community) with PIT …

The Effects Of A Planned Missingness Design On Examinee Motivation And Psychometric Quality, Matthew S. Swain

Dissertations, 2014-2019

Assessment practitioners in higher education face increasing demands to collect assessment and accountability data to make important inferences about student learning and institutional quality. The validity of these high-stakes decisions is jeopardized, particularly in low-stakes testing contexts, when examinees do not expend sufficient motivation to perform well on the test. This study introduced planned missingness as a potential solution. In planned missingness designs, data on all items are collected but each examinee only completes a subset of items, thus increasing data collection efficiency, reducing examinee burden, and potentially increasing data quality. The current scientific reasoning test served as the Long …

Examining The Performance Of The Metropolis-Hastings Robbins-Monro Algorithm In The Estimation Of Multilevel Multidimensional Irt Models, Bozhidar M. Bashkov

Dissertations, 2014-2019

The purpose of this study was to review the challenges that exist in the estimation of complex (multidimensional) models applied to complex (multilevel) data and to examine the performance of the recently developed Metropolis-Hastings Robbins-Monro (MH-RM) algorithm (Cai, 2010a, 2010b), designed to overcome these challenges and implemented in both commercial and open-source software programs. Unlike other methods, which either rely on high-dimensional numerical integration or approximation of the entire multidimensional response surface, MH-RM makes use of Fisher’s Identity to employ stochastic imputation (i.e., data augmentation) via the Metropolis-Hastings sampler and then apply the stochastic approximation method of Robbins and Monro …

Relationship Between High School Math Course Selection And Retention Rates At Otterbein University, Lauren A. Fisher

Undergraduate Honors Thesis Projects

Binary logistic regression was used to study the relationship between high school math course selection and retention rates at Otterbein University. Graduation rates from postsecondary institutions are low in the United States and, more specifically, at Otterbein. This study is important in helping to determine what can raise retention rates, and ultimately, graduation rates. It directs focus toward high school math course selection and what should be changed before entering a post-secondary institution. Otterbein will have a better idea of what type of students to recruit and which students may be good candidates with some extra help. Recruiting is expensive, …

A Generalized Inflated Geometric Distribution, Ram Datt Joshi

Theses, Dissertations and Capstones

A count data that have excess number of zeros, ones, twos or threes are commonplace in experimental studies. But these inflated frequencies at particular counts may lead to over dispersion and thus may cause difficulty in data analysis. So, to get appropriate results from them and to overcome the possible anomalies in parameter estimation, we may need to consider suitable inflated distribution.

In this thesis, we have considered a Swedish fertility dataset with inflated values at some particular counts. Generally, Inflated Poisson or Inflated Negative Binomial distribution are the most common distributions for analyzing such data. Geometric distribution can be …

The Simulation & Evaluation Of Surge Hazard Using A Response Surface Method In The New York Bight, Michael H. Bredesen

UNF Graduate Theses and Dissertations

Atmospheric features, such as tropical cyclones, act as a driving mechanism for many of the major hazards affecting coastal areas around the world. Accurate and efficient quantification of tropical cyclone surge hazard is essential to the development of resilient coastal communities, particularly given continued sea level trend concerns. Recent major tropical cyclones that have impacted the northeastern portion of the United States have resulted in devastating flooding in New York City, the most densely populated city in the US. As a part of national effort to re-evaluate coastal inundation hazards, the Federal Emergency Management Agency used the Joint Probability Method …

A Predictive Modeling System: Early Identification Of Students At-Risk Enrolled In Online Learning Programs, Mary L. Fonti

CCE Theses and Dissertations

Predictive statistical modeling shows promise in accurately predicting academic performance for students enrolled in online programs. This approach has proven effective in accurately identifying students who are at-risk enabling instructors to provide instructional intervention. While the potential benefits of statistical modeling is significant, implementations have proven to be complex, costly, and difficult to maintain. To address these issues, the purpose of this study is to develop a fully integrated, automated predictive modeling system (PMS) that is flexible, easy to use, and portable to identify students who are potentially at-risk for not succeeding in a course they are currently enrolled in. …

Applications Of Monte Carlo Methods In Statistical Inference Using Regression Analysis, Ji Young Huh

CMC Senior Theses

This paper studies the use of Monte Carlo simulation techniques in the field of econometrics, specifically statistical inference. First, I examine several estimators by deriving properties explicitly and generate their distributions through simulations. Here, simulations are used to illustrate and support the analytical results. Then, I look at test statistics where derivations are costly because of the sensitivity of their critical values to the data generating processes. Simulations here establish significance and necessity for drawing statistical inference. Overall, the paper examines when and how simulations are needed in studying econometric theories.

Acceptance-Rejection Sampling With Hierarchical Models, Christian A. Ayala

CMC Senior Theses

Hierarchical models provide a flexible way of modeling complex behavior. However, the complicated interdependencies among the parameters in the hierarchy make training such models difficult. MCMC methods have been widely used for this purpose, but can often only approximate the necessary distributions. Acceptance-rejection sampling allows for perfect simulation from these often unnormalized distributions by drawing from another distribution over the same support. The efficacy of acceptance-rejection sampling is explored through application to a small dataset which has been widely used for evaluating different methods for inference on hierarchical models. A particular algorithm is developed to draw variates from the posterior …

A Model For Determining Drivers Of Phenology In Western United States Rangelands, Joseph R. St. Peter

Graduate Student Theses, Dissertations, & Professional Papers

Plant phenology has long been used as an indicator of climate. Recent changes in plant phenology are evidence of the influence of climate change. Modeling plant phenology has become an effective tool to understand the impacts of climate change. Using machine learning techniques I developed a modeling process for accurately predicting phenology across a diverse landscape. This model uses individual site data to set site specific climate thresholds for plant phenology. This model also identifies the limiting factors to vegetation phenology for rangelands in the western United States. NDVI remotely sensed data was used to quantify land surface phenology and …

New Results In Ell_1 Penalized Regression, Edward A. Roualdes

Theses and Dissertations--Statistics

Here we consider penalized regression methods, and extend on the results surrounding the l1 norm penalty. We address a more recent development that generalizes previous methods by penalizing a linear transformation of the coefficients of interest instead of penalizing just the coefficients themselves. We introduce an approximate algorithm to fit this generalization and a fully Bayesian hierarchical model that is a direct analogue of the frequentist version. A number of benefits are derived from the Bayesian persepective; most notably choice of the tuning parameter and natural means to estimate the variation of estimates – a notoriously difficult task for the …