Statistics and Probability Commons^™

Functional Generalized Linear Mixed Models, Harmony Luce

Dissertations

With the advancements in data collection technologies, researchers in various fields such as epidemiology, chemometrics, and environmental science face the challenges of obtaining useful information from more detailed, complex, and intricately-structured data. Since the existing methods often are not suitable for such data, new statistical methods are developed to accommodate the complicated data structures.

As a part of such efforts, this dissertation proposes Functional Generalized Linear Mixed Model (FGLMM), which extends classical generalized linear mixed models to include functional covariates. Functional Data Analysis (FDA) is a rapidly developing area of statistics for data which can be naturally viewed as smooth …

Nonparametric Tests For Replicated Latin Squares, Joseph Yang

Dissertations

Two classes of nonparametric procedures for a replicated Latin square design that test for both general and increasing alternatives are developed. The two classes of procedures are similar in the sense that both transform the data so that existing well-known tests for randomized complete block designs can be utilized. On the other hand, the two classes differ in the way that the data is transformed - one class essentially aggregates the data while the other class aligns the data. Within these contexts, the exact distributions and asymptotic distributions are discussed, when applicable. The exact distributions are easily computed using the …

Population Modeling With Machine Learning Can Enhance Measures Of Mental Health - Open-Data Replication, Ty Easley, Ruiqi Chen, Kayla Hannon, Rosie Dutt, Janine Bijsterbosch

Statistical and Data Sciences: Faculty Publications

Efforts to predict trait phenotypes based on functional MRI data from large cohorts have been hampered by low prediction accuracy and/or small effect sizes. Although these findings are highly replicable, the small effect sizes are somewhat surprising given the presumed brain basis of phenotypic traits such as neuroticism and fluid intelligence. We aim to replicate previous work and additionally test multiple data manipulations that may improve prediction accuracy by addressing data pollution challenges. Specifically, we added additional fMRI features, averaged the target phenotype across multiple measurements to obtain more accurate estimates of the underlying trait, balanced the target phenotype's distribution …

Evaluating The Performance Of Estimators In Sem And Irt With Ordinal Variables, Bo Klauth

Dissertations

In conducting confirmatory factor analysis with ordered response items, the literature suggests that when the number of responses is five and item skewness (IS) is approximately normal, researchers can employ maximum likelihood with robust standard errors (MLR). However, MLR can yield biased factor loadings (FL) and FL standard errors (FLSE) when the variables are ordinal. Other estimators are available. Unweighted least squares and weighted least squares with adjusted mean and variance (ULSMV and WLSMV) are known as the estimators for CFA with ordinal variables (CFA-OV). Another estimator, marginal maximum likelihood (MML), is used in the item response theory (IRT), specifically …

(R2031) M/M/1 Retrial Queue With Working Vacation And Interruption In Bernoulli Schedule Under N-Control Pattern, P. Manoharan, S. Pazhani Bala Murugan, A. Sobanappriya

Applications and Applied Mathematics: An International Journal (AAM)

An M/M/1 retrial queue with working vacation and interruption in Bernoulli schedule under N-control pattern is investigated in this article. To describe the system, we employ a QBD analogy. The model’s stability condition is deduced. The stationary probability distribution is generated by utilizing the matrix-analytic technique. The performance measures and special cases are designed. The model’s firmness is demonstrated numerically

(R2027) A New Class Of Pareto Distribution: Estimation And Its Applications, Anitta Susan Aniyan, Dais George

Applications and Applied Mathematics: An International Journal (AAM)

The classical Pareto distribution is a positively skewed and right heavy-tailed lifetime distribution having a lot many applications in various fields of science and social science. In this work, via logarithmic trans-formed method, a new three parameter lifetime distribution, an extension of classical Pareto distribution is generated. The different structural properties of the new distribution are studied. The model parameters are estimated by the method of maximum likelihood and Bayesian procedure. When all the three parameters of the distribution are unknown, the Bayes estimators cannot be obtained in a closed form and hence, the Lindley’s approximation under squared error loss …

A Proposed Fair Approach For Disseminating Geospatial Information System Maps, P. Travis Thompson, Sweta Ojha, Christian D. Powell, Kelly G. Pennell, Hunter N. B. Moseley

Markey Cancer Center Faculty Publications

We present a draft Minimum Information about Geospatial Information System (MIaGIS) standard for facilitating public deposition of geospatial information system (GIS) datasets that follows the FaIR (Findable, accessible, Interoperable and Reusable) principles. the draft MIaGIS standard includes a deposition directory structure and a minimum javascript object notation (JSON) metadata formatted file that is designed to capture critical metadata describing GIS layers and maps as well as their sources of data and methods of generation. the associated miagis Python package facilitates the creation of this MIAGIS metadata file and directly supports metadata extraction from both Esri JSON and GEOJSON GIS data …

Identifying And Sharing Per-And Polyfluoroalkyl Substances Hot-Spot Areas And Exposures In Drinking Water, Sweta Ojha, P. Travis Thompson, Christian D. Powell, Hunter N. B. Moseley, Kelly G. Pennell

Markey Cancer Center Faculty Publications

Exposure to per- and polyfluoroalkyl substances (PFAS) in drinking water is widely recognized as a public health concern. Decision-makers who are responsible for managing PFAS drinking water risks lack the tools to acquire the information they need. In response to this need, we provide a detailed description of a Kentucky dataset that allows decision-makers to visualize potential hot-spot areas and evaluate drinking water systems that may be susceptible to PFAS contamination. The dataset includes information extracted from publicly available sources to create five different maps in ArcGIS Online and highlights potential sources of PFAS contamination in the environment in relation …

An Empirical Evaluation Of Neural Process Meta-Learners For Financial Forecasting, Kevin G. Patel

Master's Theses

Challenges of financial forecasting, such as a dearth of independent samples and non- stationary underlying process, limit the relevance of conventional machine learning towards financial forecasting. Meta-learning approaches alleviate some of these is- sues by allowing the model to generalize across unrelated or loosely related tasks with few observations per task. The neural process family achieves this by con- ditioning forecasts based on a supplied context set at test time. Despite promise, meta-learning approaches remain underutilized in finance. To our knowledge, ours is the first application of neural processes to realized volatility (RV) forecasting and financial forecasting in general.

We …

Digital Economy, Institutional Quality And Economic Growth In Selected Countries, Olabode P. Olofin Mr.

CBN Journal of Applied Statistics (JAS)

This study examines the role of digital economy and institutional quality on economic growth of Bangladesh, Ethiopia, Kenya, and Nigeria. The study adopts the feasible generalized least square method with annual panel data from 1985 to 2017. Results show that digital economy, human capital and knowledge worker, and democratic accountability promote economic growth, while corruption, socioeconomic conditions, and bureaucratic quality retard economic growth. Furthermore, interaction of digital economy with corruption promotes growth. However, the interaction of digital economy with institutional quality retards economic growth, which could be due to the deteriorating institutional quality and low level of economic digitalization in …

Food Price And Inflation Adjustments In Nigeria: Evidence From Threshold Cointegration, Usman A. Bello, Aliyu R. Sanusi

CBN Journal of Applied Statistics (JAS)

This paper investigates two stages of transmission through which inflation stabilization policy affects headline inflation by estimating a threshold cointegration model. The paper finds that asymmetric monetary shocks passing-through food prices exerts inflationary pressure on consumer prices, and is characterized by deep asymmetric movement, large degree of stickiness in adjusting downward, while exhibiting upward momentum in correcting food price fall. In addition, asymmetries were found in consumer price adjustment as food price shock transmits substantial inflationary pressure to consumer prices, while disinflationary effect originating from a fall in food price is inconsequential. The coefficients of adjustment were found to be …

Dynamic Effect Of Exchange Rate Gap Shocks On Stock Market Deepening: Evidence From Nigeria, Kareem Abidemi Arikewuyo

CBN Journal of Applied Statistics (JAS)

The study examines the exchange rate gap shock–stock market deepening nexus in Nigeria using the structural VAR-X (SVAR-X) technique for the period 1986Q1 to 2018Q4. Findings reveal that exchange rate gap shock has a negative but statistically not significant effect on stock market deepening in Nigeria. It was also found that exchange rate passed–through interest rate from second to thirteen quarter, and further through financial openness whose effect, like exchange rate gap, was negative. This implies that exchange rate gap is significantly and negatively related to interest rate and financial openness in Nigeria. It is therefore recommended that the monetary …

Modelling The Impact Of Government Expenditure On Economic Growth In Nigeria: The Moderating Effects Of Oil And Non-Oil Revenue, Victor U. Ijirshar, Gaius M. Asombo, Florence D. Bundepuun, Ashifa Tersugh, Ayila Ngutsav

CBN Journal of Applied Statistics (JAS)

This study examines the relationship between government expenditure and economic growth and assesses the moderating effects of oil revenue and non-oil revenue in Nigeria from 1981 to 2021. The study uncovered short-term asymmetry in the government expenditure-economic growth nexus while the long-term relationship was symmetric. The study found that government expenditure is a significant determinant of economic growth in Nigeria and that oil and non-oil revenue influences the nexus between government expenditure and economic growth in Nigeria positively. The study recommends efficient management of oil revenue, directing investments during high revenue periods and ensuring fiscal sustainability. Government should also establish …

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 …

Predicting Hiv Vaccine-Mediated Protection Level To Identify Immune Correlates Using Positive Unlabeled Learning, Shiwei Xu

Dartmouth College Ph.D Dissertations

The development of a vaccine for Human Immunodeficiency Virus type 1 (HIV-1) is a crucial step in preventing the global spread of AIDS. To ensure the progress and effectiveness of this vaccine, it is essential to establish efficient biotechnology platforms and data mining methods. These methods would help identify immune characteristics that distinguish individuals with varying levels of vaccine-induced protection and determine the underlying factors that contribute to protection against HIV acquisition. While previous studies have focused on identifying immune markers associated with infection outcomes among vaccinated patients, it is important to acknowledge the limitations of traditional case-control analytical protocols …

Statistical And Biological Analyses Of Acoustic Signals In Estrildid Finches, Moises Rivera

Dissertations, Theses, and Capstone Projects

Acoustic communication is a process that involves auditory perception and signal processing. Discrimination and recognition further require cognitive processes and supporting mechanisms in order to successfully identify and appropriately respond to signal senders. Although acoustic communication is common across birds, classical research has largely disregarded the perceptual abilities of perinatal altricial taxa. Chapter 1 reviews the literature of perinatal acoustic stimulation in birds, highlighting the disproportionate focus on precocial birds (e.g., chickens, ducks, quails). The long-held belief that altricial birds were incapable of acoustic perception in ovo was only recently overturned, as researchers began to find behavioral and physiological evidence …

Characterization Of Boreal-Arctic Vegetation Growth Phases And Active Soil Layer Dynamics In The High-Latitudes Of North America: A Study Combining Multi-Year In Situ And Satellite-Based Observations, Michael G. Brown

Dissertations, Theses, and Capstone Projects

This dissertation examined the seasonal freeze/thaw activity in boreal-Arctic soils and vegetation physiology in Alaska, USA and Alberta, Canada, using in situ environmental measurements and passive microwave satellite observations. The boreal-Arctic high-latitudes have been experiencing ecosystem changes more rapidly in comparison to the rest of Earth due to the presently warming climatic conditions having a magnified effect over Polar Regions. Currently, the boreal-Arctic is a carbon sink; however, recent studies indicate a shift over the next century to become a carbon source. High-latitude vegetation and cold soil dynamics are influenced by climatic shifts and are largely responsible for the regions …

A Survey On Online Matching And Ad Allocation, Ryan Lee

Theses

One of the classical problems in graph theory is matching. Given an undirected graph, find a matching which is a set of edges without common vertices. In 1990s, Richard Karp, Umesh Vazirani, and Vijay Vazirani would be the first computer scientists to use matchings for online algorithms [8]. In our domain, an online algorithm operates in the online setting where a bipartite graph is given. On one side of the graph there is a set of advertisers and on the other side we have a set of impressions. During the online phase, multiple impressions will arrive and the objective of …

Data-Optimized Spatial Field Predictions For Robotic Adaptive Sampling: A Gaussian Process Approach, Zachary Nathan

Computer Science Senior Theses

We introduce a framework that combines Gaussian Process models, robotic sensor measurements, and sampling data to predict spatial fields. In this context, a spatial field refers to the distribution of a variable throughout a specific area, such as temperature or pH variations over the surface of a lake. Whereas existing methods tend to analyze only the particular field(s) of interest, our approach optimizes predictions through the effective use of all available data. We validated our framework on several datasets, showing that errors can decline by up to two-thirds through the inclusion of additional colocated measurements. In support of adaptive sampling, …

Dimensions Of Vaccination Attitudes In Nigeria: A Study Of The Impacts Of Covid-19 Vaccine Risk Perception And Acceptance, Abiodun Musbau Lawal, Babatola Dominic Olawa, Ikenna Maximillian Odoh, Ayodeji Olorunfemi Olawole, Olubukola Ajayi, Judith Chineye Azikiwe, Israel Oluwatosin Ayodele, Emmanuel Kolawole Odusina, Thomas Attah, Ezekiel Adeyemi Odedokun, Stephen Ishola Babatunde, Teslim Alabi Oladejo, Confidence Chioma Otoghile, Saheed Abiola Saka

Kesmas

Nigeria has been affected by the COVID-19 pandemic, and vaccination is a key strategy. However, the country faces vaccination hesitancy, poor risk perception, and low acceptance. This study aimed to assess the direct and interactive impacts of COVID-19 vaccine risk perception and acceptability on COVID-19 vaccination attitudes in the general Nigerian population. In a cross-sectional approach, participants completed a structured questionnaire including demographics, COVID-19 vaccine risk perception, acceptance, and vaccination attitude from April 2-30, 2021. The sample included 1,026 participants from different ethnicities across four regions (Southwest, South, Southeast, and North Central) in Nigeria, which were selected using the convenience …