Design of Experiments and Sample Surveys Commons^™

How’S It Growing? Tools For Observing Snow And Sea Ice In A Changing Arctic Ocean, Ian Alexander Raphael

Dartmouth College Ph.D Dissertations

September Arctic sea ice extent has diminished by roughly 50% in the 45 years since satellite observations began. The Arctic Ocean may experience ice-free summers within the next decade, with implications for habitat, resource extraction, geopolitics, and local and global climate change. To predict how Arctic sea ice will change in the future, we need to understand its behavior in the present. In situ sea ice mass balance measurements (snow accumulation, ice growth, snow and ice surface melt, and bottom melt) are essential for studying the processes driving rapid changes in the ice pack, and for validating remote sensing measurements …

Reinforcement Learning, Modeling Markets, And Professional Basketball Free Agency, Jacob Cohn

Computational and Data Sciences (PhD) Dissertations

This dissertation presents a reinforcement learning-based approach to modeling and optimizing decision-making in professional basketball free agency and related economic environments. A Markov Decision Process (MDP) framework is introduced to capture the strategic interactions of NBA teams bidding for free agents under budgetary and roster constraints. To address computational scalability challenges, a reinforcement learning (RL) environment is developed, leveraging Proximal Policy Optimization (PPO) to approximate optimal policies for team decision-making.

Empirical results demonstrate that the RL agent successfully learns strategic bidding behavior that aligns with dynamic programming benchmarks in simplified settings while scaling effectively to larger, intractable environments. The study …

Exploring Healthcare Chatbot Information Presentation: Applying Hierarchical Bayesian Regression And Inductive Thematic Analysis In A Mixed Methods Study, Samuel Nelson Koscelny

All Theses

High blood pressure, also known as hypertension, significantly increases the risk of heart disease and stroke, which are leading causes of death in the United States. While contributing to over 691,000 deaths in 2021 alone in the United States (U.S.), it also imposes immense economic burden on the healthcare system, costing approximately $131 billion annually. One way to address this issue is for increased self-care behaviors and medication adherence, both of which require sufficient health literacy. Despite the importance of health literacy, 90% of U.S. adults struggle with health-related subjects. Overcoming the issues associated with health literacy requires addressing the …

Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, Daniel C. Tisdale

Master's Theses

We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation …

Stock Market Volatility In The United Kingdom: Simulating Post-Covid-19 Recovery, Bala A. Dahiru, Mohammed Shuaibu, Najibullah Hassanov

CBN Journal of Applied Statistics (JAS)

This paper investigates the time it would take for the FTSE-100 index to reach its post-COVID-19 peak. The paper utilises an exponential generalised autoregressive conditional heteroscedasticity (EGARCH) model that accounts for leverage effect and asymmetries. The preferred models amongst competing variants was the Autoregressive Moving Average (ARMA)-EGARCH(2,1) specification and was used to predict daily FTSE-100 data from 5th January 2000 to 21st June 2024. The empirical exercise showed that the COVID-19-induced financial crisis negatively affected the United Kingdom’s stock market performance. The results show that the FTSE100 index could reach its post-pandemic peak around 27th August, 2024 (two months after …

Reducing Food Scarcity: The Benefits Of Urban Farming, S.A. Claudell, Emilio Mejia

Journal of Nonprofit Innovation

Urban farming can enhance the lives of communities and help reduce food scarcity. This paper presents a conceptual prototype of an efficient urban farming community that can be scaled for a single apartment building or an entire community across all global geoeconomics regions, including densely populated cities and rural, developing towns and communities. When deployed in coordination with smart crop choices, local farm support, and efficient transportation then the result isn’t just sustainability, but also increasing fresh produce accessibility, optimizing nutritional value, eliminating the use of ‘forever chemicals’, reducing transportation costs, and fostering global environmental benefits.

Imagine Doris, who is …

Improving The Efficiency Of Exponential Ratio-Type Estimator For Population Median: A Calibration Weight Adjustment Approach, Mathew J. Iseh, Kufre J. Bassey

CBN Journal of Applied Statistics (JAS)

This paper modifies the Bahl and Tuteja exponential ratio-type estimator for population median under simple random and stratified sampling schemes using calibration weight adjustment technique with supplementary information to vary the stratum weights. The bias and mean square error of the modified estimator were obtained up to the second-order approximation, which satisfies the necessary conditions for efficiency. The findings show that the new estimator surpasses existing estimators in efficiency gain. This suggests the appropriateness of calibration weight modification in boosting the efficiency of a population parameter estimator under stratified random sampling especially where the population parameter of the auxiliary variable …

Uconn Baseball Batting Order Optimization, Gavin Rublewski, Gavin Rublewski

Honors Scholar Theses

Challenging conventional wisdom is at the very core of baseball analytics. Using data and statistical analysis, the sets of rules by which coaches make decisions can be justified, or possibly refuted. One of those sets of rules relates to the construction of a batting order. Through data collection, data adjustment, the construction of a baseball simulator, and the use of a Monte Carlo Simulation, I have assessed thousands of possible batting orders to determine the roster-specific strategies that lead to optimal run production for the 2023 UConn baseball team. This paper details a repeatable process in which basic player statistics …

Machine Learning-Based Data And Model Driven Bayesian Uncertanity Quantification Of Inverse Problems For Suspended Non-Structural System, Zhiyuan Qin

All Dissertations

Inverse problems involve extracting the internal structure of a physical system from noisy measurement data. In many fields, the Bayesian inference is used to address the ill-conditioned nature of the inverse problem by incorporating prior information through an initial distribution. In the nonparametric Bayesian framework, surrogate models such as Gaussian Processes or Deep Neural Networks are used as flexible and effective probabilistic modeling tools to overcome the high-dimensional curse and reduce computational costs. In practical systems and computer models, uncertainties can be addressed through parameter calibration, sensitivity analysis, and uncertainty quantification, leading to improved reliability and robustness of decision and …

Effect Of Monetary Policy Rate On Market Interest Rates In Nigeria: A Threshold And Nardl Approach, Oluwafemi E. Awopegba, Joseph O. Afolabi, Lydia T. Adeoye, Godwin O. Akpokodje

CBN Journal of Applied Statistics (JAS)

This study examines the effect of monetary policy rate (MPR) on market interest rates in Nigeria. For parsimony, we develop two indexes called the short-term interest rate (SINT) and Lending interest rate (LINT) to represent deposit and lending rates respectively. The nonlinear autoregressive distributed lag (NARDL) and threshold regression models are adopted. The study uses monthly data from 2002:M1 to 2019:M12. The results of the threshold regression model indicate that the degree of the effect of MPR on SINT and LINT above the estimated threshold of 11 and 13 percent respectively is greater and significant than if MPR were to …

Social Dimension Of Inclusive Growth In Ecowas: Implication For Poverty Reduction, Toriola K. Anu, Goerge O. Emmanuel, Ajayi O. Felix

CBN Journal of Applied Statistics (JAS)

This study investigates the implication of the social dimension of inclusive growth on poverty reduction in Economic Community of West African States (ECOWAS) countries. It specifically examines how social indices of inclusive growth comprising of income inequality, education, and health outcomes affect poverty reduction. The study uses a panel dataset of the six (6) lower-middle income countries in ECOWAS which was analysed via panel Difference Generalised Method of Moment (D-GMM). The results show that GDP per capita exerts significant negative effect on poverty while inequality, education and health outcomes do not show significant effect on poverty. Although, the estimates of …

Effect Of Fdi Inflows On Employment Generation In Selected Ecowas Countries: Heterogeneous Panel Analysis, Timothy A. Aderemi, Olawunmi Omitogun, Bukonla G. Osisanwo

CBN Journal of Applied Statistics (JAS)

The aim of this study is to examine the effect of FDI on employment in ECOWAS sub region between 1990 and 2019. The study utilizes a panel autoregressive distributed lag model to analyse the short run and long run relationship between FDI and employment across ECOWAS sub region. In the short run, the impact of FDI on employment is negative and statistically not significant. Meanwhile, in the long run FDI has a positive and statistically significant impact on employment rate. This implies that FDI has the capacity to generate employment in countries in ECOWAS sub region. Therefore, this study recommends …

Impact Of Covid-19 Pandemic On The Nigeria Stock Market: A Sectoral Stock Prices Analysis, Peter A. Adekunle, Yakubu A. Bello, Udochukwu G. Nwachukwu

CBN Journal of Applied Statistics (JAS)

This study examines the impact of the COVID-19 pandemic on sectoral stock prices in Nigeria stock market using daily data covering from February 28, 2020 to June 26, 2020. Applying the autoregressive distributed lag (ARDL) bounds test, the study finds that COVID-19 pandemic had adverse impact on the stock market indices in the short run. Furthermore, the study documents negative response of sectoral stock prices to the pandemic while the stock prices of the banking sub-sector are the worst hit. Compared to the consumer goods, and industrial subsector indices, the speed of adjustment to long run equilibrium is faster for …

Increasing Perceived Realism Of Objects In A Mixed Reality Environment Using 'Diminished Virtual Reality', Logan Scott Parker

Honors Theses

With the recent explosion of popularity of virtual and mixed reality, an important question has arisen: “Is there a way to create a better blend of real and virtual worlds in a mixed reality experience?” This research attempts to determine whether a visual filter can be created and applied to virtual objects to better convince the brain into interpreting a composite of virtual and real views as one seamless view. The method devised in this thesis is being called 'Diminished Virtual Reality'. The results found in this study show that when presented with a scene composed of a combination of …

Characterizing Convolutional Neural Network Early-Learning And Accelerating Non-Adaptive, First-Order Methods With Localized Lagrangian Restricted Memory Level Bundling, Benjamin O. Morris

Theses and Dissertations

This dissertation studies the underlying optimization problem encountered during the early-learning stages of convolutional neural networks and introduces a training algorithm competitive with existing state-of-the-art methods. First, a Design of Experiments method is introduced to systematically measure empirical second-order Lipschitz upper bound and region size estimates for local regions of convolutional neural network loss surfaces experienced during the early-learning stages. This method demonstrates that architecture choices can significantly impact the local loss surfaces traversed during training. Next, a Design of Experiments method is used to study the effects convolutional neural network architecture hyperparameters have on different optimization routines' abilities to …

Ensemble Data Fitting For Bathymetric Models Informed By Nominal Data, Samantha Zambo

Dissertations

Due to the difficulty and expense of collecting bathymetric data, modeling is the primary tool to produce detailed maps of the ocean floor. Current modeling practices typically utilize only one interpolator; the industry standard is splines-in-tension.

In this dissertation we introduce a new nominal-informed ensemble interpolator designed to improve modeling accuracy in regions of sparse data. The method is guided by a priori domain knowledge provided by artificially intelligent classifiers. We recast such geomorphological classifications, such as ‘seamount’ or ‘ridge’, as nominal data which we utilize as foundational shapes in an expanded ordinary least squares regression-based algorithm. To our knowledge …

Preparing For The Future: The Effects Of Financial Literacy On Financial Planning For Young Professionals, Tanay Singh

Senior Theses

Purpose – Many people between the age of 20 and 34 have not considered planning financially for the future in any significant capacity and in doing so, they limit their potential savings. The purpose of this study is to examine what financial expectations are for people in the early stages of their career and determine if improving financial literacy and revealing financial realities helps to produce more accurate or realistic expectations. Ultimately, the goal is to better prepare participants in the study for the working world and increased responsibilities outside of the college/university environment by getting them to start thinking …

Snap Scholar: The User Experience Of Engaging With Academic Research Through A Tappable Stories Medium, Ieva Burk

CMC Senior Theses

With the shift to learn and consume information through our mobile devices, most academic research is still only presented in long-form text. The Stanford Scholar Initiative has explored the segment of content creation and consumption of academic research through video. However, there has been another popular shift in presenting information from various social media platforms and media outlets in the past few years. Snapchat and Instagram have introduced the concept of tappable “Stories” that have gained popularity in the realm of content consumption.

To accelerate the growth of the creation of these research talks, I propose an alternative to video: …

Digital Forensics Tool Selection With Multi-Armed Bandit Problem, Umit Karabiyik, Tugba Karabiyik

Annual ADFSL Conference on Digital Forensics, Security and Law

Digital forensics investigation is a long and tedious process for an investigator in general. There are many tools that investigators must consider, both proprietary and open source. Forensics investigators must choose the best tool available on the market for their cases to make sure they do not overlook any evidence resides in suspect device within a reasonable time frame. This is however hard decision to make, since learning and testing all available tools make their job only harder. In this project, we define the digital forensics tool selection for a specific investigative task as a multi-armed bandit problem assuming that …

Applying Ahp And Clustering Approaches For Public Transportation Decisionmaking: A Case Study Of Isfahan City, Alireza Salavati, Hossein Haghshenas, Bahador Ghadirifaraz, Jamshid Laghaei, Ghodrat Eftekhari

Journal of Public Transportation

The main purpose of this paper is to define appropriate criteria for the systematic approach to evaluate and prioritize multiple candidate corridors for public transport investment simultaneously to serve travel demand, regarding supply of current public transportation system and road network conditions of Isfahan, Iran. To optimize resource allocation, policymakers need to identify proper corridors to implement a public transportation system. In fact, the main question is to adopt the best public transportation system for each main corridor of Isfahan. In this regard, 137 questionnaires were completed by experts, directors, and policymakers of Isfahan to identify goals and objectives in …

A Fault-Based Model Of Fault Localization Techniques, Mark A. Hays

Theses and Dissertations--Computer Science

Every day, ordinary people depend on software working properly. We take it for granted; from banking software, to railroad switching software, to flight control software, to software that controls medical devices such as pacemakers or even gas pumps, our lives are touched by software that we expect to work. It is well known that the main technique/activity used to ensure the quality of software is testing. Often it is the only quality assurance activity undertaken, making it that much more important.

In a typical experiment studying these techniques, a researcher will intentionally seed a fault (intentionally breaking the functionality of …

Short-Term Inflation Forecasting Models For Nigeria, Sani I. Doguwa, Sarah O. Alade

CBN Journal of Applied Statistics (JAS)

Short-term inflation forecasting is an essential component of the monetary policy projections at the Central Bank of Nigeria. This paper proposes four short-term headline inflation forecasting models using the SARIMA and SARIMAX processes and compares their performance using the pseudo-out-of-sample forecasting procedure over July 2011 to September 2013. According to the results the best forecasting performance is demonstrated by the model based on the all items CPI estimated using the SARIMAX model. This model is, therefore, recommended for use in short-term forecasting of headline inflation in Nigeria. The forecasting performance up to eight months ahead, of the models based on …

An Efficient Two Sample Capture-Recapture Model With High Recaptures, Danjuma Jibasen, Yusuf J. Adams

CBN Journal of Applied Statistics (JAS)

This paper proposed an efficient two sample capture-recapture model (Ma) with high recaptures and compared it with the existing models like the model of no factor effect (Mo), behavioral response model (Mb) and the Petersen model (Ms), using simulated data. We found that the Petersen model provides a better estimate of the population size when the observations follow a hypergeometric distribution and the population is overestimated when recapture is high. It was also found that the proposed model provides a better estimator of the population size than the existing ones when the recapture is high. This model is particularly useful …

Causal Relationship Between Stock Market Index And Exchange Rate: Evidence From Nigeria, Abdulrasheed Zubair

CBN Journal of Applied Statistics (JAS)

This paper uses Johansen’s cointegration to test for the possibility of cointegration and Granger-causality to estimate the causal relationship between stock market index and monetary indicators (exchange rate and M2) before and during the global financial crisis for Nigeria, using monthly data for the period 2001–2011. Results suggest absence of long-run relationship before and during the crisis. The Granger-causality tests show a uni-directional causality running from M2 to ASI before the crisis while during the period of the crisis there is absence of causality between the variables. This suggests that ASI show responsiveness to M2. Thus, absence of the direct …

Investigating Chaos In The Nigerian Asset And Resource Management (Arm) Discovery Fund, Ibiyinka A. Fuwape, Samuel T. Ogunjo

CBN Journal of Applied Statistics (JAS)

This paper investigates chaos in a Nigerian mutual fund, Asset and Resource Management Company Limited (ARM) for a period of eleven years. The existence of chaotic signals in the data was identified by the reconstruction of the phase space of the daily closing price of the fund and the delay time was quantified using mutual information function and the embedding dimension by the false nearest neighbours, where the values were identified to be 15 and 20 respectively. The presence of chaotic signals in the ARM data was further confirmed by the correlation dimension method which yielded a dimension of 2.2 …

Modeling The Nigerian Inflation Rates Using Periodogram And Fourier Series Analysis, Chukwuemeka O. Omekara,, Emmanuel J. Ekpenyong, Micheal P. Ekerete

CBN Journal of Applied Statistics (JAS)

This work considers the application of Periodogram and Fourier Series Analysis to model all-items monthly inflation rates in Nigeria from 2003 to 2011. The main objectives are to identify inflation cycles, fit a suitable model to the data and make forecasts of future values. To achieve these objectives, monthly all-items inflation rates for the period were obtained from the Central Bank of Nigeria (CBN) website. Periodogram and Fourier series methods of analysis are used to analyze the data. Based on the analysis, it was found that inflation cycle within the period was fifty one (51) months, which coincides with the …

Nigerian Stock Index: A Search For Optimal Garch Model Using High Frequency Data, Olaoluwa Simon Yaya

CBN Journal of Applied Statistics (JAS)

This paper attempts to fit the best Generalized Autoregressive Conditional Heteroscedastic (GARCH) model for All Share Index (ASI) of Nigerian Stock Exchange (NSE) returns. A search is made on various GARCH variants specified on the assumptions of stationarity and asymmetry. Fractionally integrated types are also considered to capture the possibility of return series having property of long range dependency. The parameter estimations are carried out on the assumptions of normality and non-normality of GARCH innovations, with models and forecasts evaluated using information criteria and loss functions respectively. Under normality assumption, Hyperbolic GARCH (HYGARCH(1,d,1)) model is selected and Integrated GARCH (IGARCH(1,1)) …

Time Series Modeling Of Nigeria External Reserves, Iheanyichukwu S. Iwueze, Eleazar C. Nwogu, Valentine U. Nlebedim

CBN Journal of Applied Statistics (JAS)

This paper discusses the levels and trend of external reserves in Nigeria. The relevance of this lies in the fact that it could help to monitor the reserves and throw early warning signal about any economic crisis. Monthly data on Nigeria external reserves for the period January 1999 to December, 2008 derived from the 2008 CBN Statistical Bulletin was analyzed using ARIMA model. Results of the analyses show that (i) the data requires logarithmic transformation to stabilize the variance and make the distribution normal (ii) the appropriate model that best describes the pattern in the transformed data is the Autoregressive- …

A Markov Decision Process Approach To Optimal Control Of A Multi-Level Hierarchical Manpower System, Akaninyene U. Udom

CBN Journal of Applied Statistics (JAS)

A recurrent problem in manpower control is how to attain the desired structural configuration in an optimal way, since it is possible to reach a desired structural configuration using different control inputs. The major aim of this paper is to develop a Markov Decision Process for optimal control of a Multi-level Hierarchical Manpower System (MHMS) by promotion and interdepartmental transfers. This is examined under control by intervention and contraction cost Markov Decision Process.

Contributions Of Financial Sector Reforms And Credit Supply To Nigerian Agricultural Sector (1978-2009), Anthony O. Onoja, M. E. Onu, S. Ajodo-Ohiemi

CBN Journal of Applied Statistics (JAS)

This study analyzed the trends and pattern of institutional credit supply to agriculture during pre- and post-financial reforms along with their determinants. It then compared the effects of reform policies on access to institutional credits in Nigerian agricultural sector before and after the reforms (1978 - 1985; and 1986 -2009). Relying mainly on time series data from CBN and NBS, it used ordinary least squares method (linear, semi-log and double log) to model the determinants of banking sector lending to the agricultural sector during the review period. The models were subjected to several econometric tests before accepting one. Chow test …