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Learning Graphical Models Of Multivariate Functional Data With Applications To Neuroimaging, Jiajing Niu

All Dissertations

This dissertation investigates the functional graphical models that infer the functional connectivity based on neuroimaging data, which is noisy, high dimensional and has limited samples. The dissertation provides two recipes to infer the functional graphical model: 1) a fully Bayesian framework 2) an end-to-end deep model.

We first propose a fully Bayesian regularization scheme to estimate functional graphical models. We consider a direct Bayesian analog of the functional graphical lasso proposed by Qiao et al. (2019).. We then propose a regularization strategy via the graphical horseshoe. We compare both Bayesian approaches to the frequentist functional graphical lasso, and compare the …

(R1999) Analysis Of A Markovian Retrial Queue With Reneging And Working Vacation Under N-Control Pattern, P. Manoharan, S. Pazhani Bala Murugan, A. Sobanappriya

Applications and Applied Mathematics: An International Journal (AAM)

A Markovian retrial queue with reneging and working vacation 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 gotten by utilizing the matrix-analytic technique. The conditional stochastic decomposition of the line length in the orbit is calculated. The performance measures and special cases are designed. The model’s firmness is demonstrated numerically.

Metabolic Alterations And Cardiovascular Risk After Hepatitis C Cure In Subjects With Or At Risk For Hiv, Christophe Maxime Fokoua Dongmo

Legacy Theses & Dissertations (2009 - 2024)

Background. Hepatitis C virus (HCV) infection engenders substantial metabolic changes. These changes are altered when the virus is cleared after successful treatment. We measured these metabolic alterations that occur after HCV cure; further, we assessed whether these alterations differed in subgroups defined by patients’ characteristics.

Evaluating The Health Impacts Of Fruit And Vegetable Intake At The Individual Level And Food Pantry Level Among Food Pantry Users, Jiacheng Chen

Legacy Theses & Dissertations (2009 - 2024)

Background: Chronic diseases impose heavy burdens on individuals and the healthcare system in the US. Many factors were found to be associated with chronic diseases, including demographics, family history, social environmental factors, and individual behavioral factors such as diet and physical activity. Among those factors, fruit and vegetable intake can have substantial health impacts via a variety of causal pathways. Fruit and vegetable (F&V) consumption is generally lower among individuals living in households experiencing food insecurity and rely on food assistance programs. Decreased F&V intake among food pantry users may negatively impact health. However, conducting quantitative analysis on this population …

A Multistate Competing Risks Framework For Preconception Prediction Of Pregnancy Outcomes, Kaitlyn Cook, Neil J. Perkins, Enrique Schisterman, Sebastien Haneuse

Statistical and Data Sciences: Faculty Publications

Background: Preconception pregnancy risk profiles—characterizing the likelihood that a pregnancy attempt results in a full-term birth, preterm birth, clinical pregnancy loss, or failure to conceive—can provide critical information during the early stages of a pregnancy attempt, when obstetricians are best positioned to intervene to improve the chances of successful conception and full-term live birth. Yet the task of constructing and validating risk assessment tools for this earlier intervention window is complicated by several statistical features: the final outcome of the pregnancy attempt is multinomial in nature, and it summarizes the results of two intermediate stages, conception and gestation, whose outcomes …

A Probabilistic Formalisation Of Contextual Bias: From Forensic Analysis To Systemic Bias In The Criminal Justice System, M. Cuellar, J. Mauro, Amanda Luby

Mathematics & Statistics Faculty Works

Researchers have found evidence of contextual bias in forensic science, but the discussion of contextual bias is currently qualitative. We formalise existing empirical research and show quantitatively how biases can be propagated throughout the legal system, all the way up to the final determination of guilt in a criminal trial. We provide a probabilistic framework for describing how information is updated in a forensic analysis setting by using the ratio form of Bayes’ rule. We analyse results from empirical studies using this framework and employ simulations to demonstrate how bias can be compounded where experiments do not exist. We find …

(R1974) A Multi Server Markovian Working Vacation Queue With Server State Dependent Rates And With Partial Breakdown, A. Sundaramoorthy, R. Kalyanaraman

Applications and Applied Mathematics: An International Journal (AAM)

In this article, we consider an M/M/C queue in which the arrival rate and service rate depends on the state of the system. In addition, the servers takes working vacation and the system may breakdown. Whenever breakdown takes place, the repair process immediately commences. During the repair period the customers are given service in a reduced service rate. Based on the vacation termination point, two models have been defined. The steady state probability vector of the number of customers in the queue and the stability condition are obtained using Matrix-Geometric method. The stationary waiting time distributions have been obtained. Some …

Weather Parameters Influencing The Incidence Of Citrus Canker Caused By Aw Strain In The Rio Grande Valley, Amit Sharma

Theses and Dissertations

Citrus canker caused by bacterium Xanthomonas citri subsp. citri (Xcc) seriously affects the citrus industry by making the fruit unmarketable due to unsightly lesions on the fruit. Canker caused by Aw strain of Xcc was reported in the citrus trees located in the residential areas of the Rio Grande Valley (RGV). Canker severity differs amongst cultivars/varieties, and it is influenced by prevailing environmental conditions. Multiple regression modeling of the disease incidence with the environmental variables such as temperature, humidity, windspeed, wind gust, and rainfall was performed to understand the environmental conditions that are favorable for spread of citrus …

Estimating The Distribution Of Ratio Of Paired Event Times In Phase Ii Oncology Trials, Li Chen, Mark Burkard, Jianrong Wu, Jill M. Kolesar, Chi Wang

Markey Cancer Center Faculty Publications

With the rapid development of new anti-cancer agents which are cytostatic, new endpoints are needed to better measure treatment efficacy in phase II trials. For this purpose, Von Hoff (1998) proposed the growth modulation index (GMI), that is, the ratio between times to progression or progression-free survival times in two successive treatment lines. An essential task in studies using GMI as an endpoint is to estimate the distribution of GMI. Traditional methods for survival data have been used for estimating the GMI distribution because censoring is common for GMI data. However, we point out that the independent censoring assumption required …

Bayesian Adaptive Clinical Trial Design, Mengyi Lu

Dissertations and Theses (Open Access)

The landscape of drug development in oncology has changed from conventional chemotherapies to molecular targeted therapies and immunotherapies, which provide innovative therapeutic modalities for treating cancers. These novel therapeutic agents work through mechanisms that fundamentally differ from standard chemotherapeutic agents, making the conventional trial design paradigm inefficient and dysfunctional. Specifically, the focus of dose-finding trials has shifted from finding the maximum tolerated dose (MTD) to the optimal biological dose (OBD), defined as the dose that optimizes the risk–benefit tradeoff. How to accurately identify the OBD and its dosing schedule is of great importance to maximize efficacy and safety of targeted …

Infrastructure Development For Personalized Risk Prediction To Reduce Cardiovascular Disease In Childhood Cancer Survivors, Suman Shrestha

Dissertations and Theses (Open Access)

Although childhood cancer survivors have lengthy life expectancies, they run the risk of experiencing long-term health issues as a result of their treatment. The most frequent non-cancerous cause of morbidity and mortality for these survivors is cardiac disease. Radiation therapy (RT) has been linked in numerous cohort studies to a higher chance of developing a late cardiac disease in these survivors, and this risk rises with higher mean heart doses and increased RT exposure to larger cardiac volumes. Since, the heart is a heterogeneous organ made up of several distinct substructures, RT dose received by the entire heart does not …

Statistical Methods For Modern Threats, Brandon Lumsden

All Dissertations

More than ever before, technology is evolving at a rapid pace across the broad spectrum of biological sciences. As data collection becomes more precise, efficient, and standardized, a demand for appropriate statistical modeling grows as well. Throughout this dissertation, we examine a variety of new age data arising from modern technology of the 21st century. We begin by employing a suite of existing statistical techniques to address research questions surrounding three medical conditions presenting in public health sciences. Here we describe the techniques used, including generalized linear models and longitudinal models, and we summarize the significant associations identified between research …

Estimation Of Disaggregated Import Demand Functions For Nigeria, Chekwube V. Madichie, Uche C. Nwogwugwu, Franklin N. Ngwu, Olisaemeka D. Mauka

CBN Journal of Applied Statistics (JAS)

This paper estimates disaggregated import demand function for Nigeria using annual data from 1970 to 2019. The study employs the Zivot-Andrews unit root and Gregory-Hansen cointegration tests to account for the role of structural breaks and the error correction mechanism for shortrun analysis, respectively. The results show that household consumption, industrial output and domestic investment are the major determinants of import demand for consumer, intermediate and investment goods, respectively. Furthermore, the import demand for investment goods is not sensitive to variations in relative prices. However, relative prices is negative and significant to import demand for consumer and intermediate goods. Exchange …

Size And Determinants Of The Shadow Economy In Nigeria: Evidence From A Monetary Approach, Tari M. Karimo, Mohammed M. Tumala, Ibrahim U, Wambai

CBN Journal of Applied Statistics (JAS)

Thiis study investigates the size and determinants of the shadow economy in Nigeria. It adopts an aggregation approach within the monetary framework and utilises the ARDL estimation technique to analyse quarterly data from 2010 Q1 to 2019 Q4. On average, the results suggest that the quarterly size of the shadow economy is about 55 per cent of the country’s GDP. The findings show that government size reduces the size of the shadow economy in the short run but increases it in the long run. The study also finds that interest rate, which is the opportunity cost of holding cash, and …

Fiscal And Monetary Policy Interactions In A Developing Economy: A Dsge-Based Evidence From Nigeria, Queen E. Oye, Philip O. Alege

CBN Journal of Applied Statistics (JAS)

This study characterizes the nature of fiscal-monetary interaction in Nigeria and gauges its macroeconomic effects by estimating a New Keynesian Dynamic Stochastic General Equilibrium (NK DSGE) model. Two policy simulations were also conducted. The first experiment considers the desirable active-passive policy mix while the second experiment ranks alternative monetary policy rules among the differing objectives of price, output and exchange rate stabilization. The study finds that fiscal and monetary policies interact as complements in an active monetary and passive fiscal policy mix over the sample period. The result from the first policy simulation reveals that the active monetary and passive …

Market Risk Factors And Stock Returns In The Nigerian Bourse, Omorose A. Ogiemudia, Osagie Osifo, Igbinovia L. Eghosa

CBN Journal of Applied Statistics (JAS)

This study examines the link between market risk and equity return in Nigeria between 1980 to 2019. It employs the vector error correction model (VECM) to determine the short run dynamics and long run effect of market risk factors on stock return. The findings revealed that a dynamic relationship exists between market risk factors and stock returns in Nigeria. Also, exchange rate risk and oil price risks have significant influence on stock return, while inflation and interest rate risk, and political instability risks have a non-significant impact on stock return. Finally, a unidirectional relationship was detected between interest rate, oil …

Savings-Investment Gap In Sub-Saharan Africa: Does The Interaction Of Financial Sector Development And Migrant Remittances Matter?, Wasiu Adekunle, Oluwatosin Adeniyi, Joshua Afolabi, Musibau Babatunde, Edward Omiwale

CBN Journal of Applied Statistics (JAS)

This study analyses the interactive effects of migrant remittances and financial development on savings-investment gap for a panel of 18 Sub-Saharan Africa (SSA) countries from 1990-2017. Results from a panel ARDL model show that migrant remittances reduce savings-investment gap in the long run. The gap is further reduced when the individual effect of financial development, and the interactive effects of migrant remittances and financial development are taken into consideration. Further analysis reveals evidence of widening effects of rising real GDP growth and bank deposits over a long-term horizon, while higher private sector credit widened the savings-investment gap only in the …

Impact Of Exchange Rate On Trade Flow In Nigeria, Victor U. Ijirshar, Isa J. Okpe, Jerome T. Andohol

CBN Journal of Applied Statistics (JAS)

This study examines the impact of exchange rate on trade flow in Nigeria from 1986 to 2021. The study utilises linear and nonlinear autoregressive distributed lag (ARDL and NARDL) models to test the J-Curve hypothesis and the Marshall-Lerner condition in Nigeria. The study found symmetric effects of exchange rate on trade balance, exports, and imports. The findings also show that real exchange rate depreciation has a strong negative influence on trade balance and exports in the short run but positive in the long run, exhibiting the shape typology of the J-curve. Furthermore, the study reveals evidence of the Marshall-Lerner condition …

Mle And Eap Methods For Estimating Ability Scores For Data Of Varying Sample Size And Item Length, Sahar Taji

Graduate Theses and Dissertations

In this research, the performance of two popular estimators, Maximum Likelihood Estimator(MLE) and Bayesian Expected a Posteriori (EAP) is studied and compared in estimating the latent ability score in an Item Response Theory (IRT) model. The 2-Parameter Logistic (2PL) IRT model which is characterized by difficulty and discrimination item parameters is used to estimate the latent ability scores. Several datasets are generated for variety of sample size and item length values. The Monte-Carlo simulation is used to analyze the performance of the estimators. Results show that MLE produces reliable results with low root mean square error (RMSE) across all datasets. …

Lindley Processes With Correlated Changes, John Grant

All Dissertations

This dissertation studies a Lindley random walk model when the increment process driving the walk is strictly stationary. Lindley random walks govern customer waiting times in many queueing models and several natural and business processes, including snow depths, frozen soil depths, inventory quantities, etc. Probabilistic properties of a Lindley process with time-correlated stationary changes are explored. We provide a streamlined argument that the process admits a limiting stationary distribution when the mean of the incremental changes is negative and that the Lindley process is strictly stationary when starting from this stationary distribution. The Markov characteristics of the process are explored …

Bayesian Methods For Graphical Models With Neighborhood Selection., Sagnik Bhadury

Electronic Theses and Dissertations

Graphical models determine associations between variables through the notion of conditional independence. Gaussian graphical models are a widely used class of such models, where the relationships are formalized by non-null entries of the precision matrix. However, in high-dimensional cases, covariance estimates are typically unstable. Moreover, it is natural to expect only a few significant associations to be present in many realistic applications. This necessitates the injection of sparsity techniques into the estimation method. Classical frequentist methods, like GLASSO, use penalization techniques for this purpose. Fully Bayesian methods, on the contrary, are slow because they require iteratively sampling over a quadratic …

Hypothesis Testing And Parameter Estimation In Mixture Cure Models For Cancer Survival Data, Mohammod Mahmudur Rahman

Graduate Theses and Dissertations

In oncology clinical trials, when a treatment is administered to the patient population, a certain subset of patients may respond to the treatment while the other does not. The positive responders with long-term survival are considered “statistically cured” and can be referred to as cured patients or long-term survivors. When a proportion of patients achieve long-term survival, the hazard functions of two arms (control vs. treatment) are no longer proportional. As a result, the traditional log-rank test, which is the most popular test to evaluate the effectiveness of a treatment in clinical trials, tends to lose its power. In this …

Power Approximations For Generalized Linear Mixed Models In R Using Steep Priors On Variance Components, Sydney Geisler

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

When designing an experiment, researchers often want to know how likely they are to detect statistically significant effects in the resulting data, i.e., they want to estimate their statistical power. The probability distribution method is a flexible way to do this, and it is currently implemented in the statistical software package SAS. This method requires a hypothetical data set (showing the magnitude of hypothesized effects) and constant values of variance components, which are critical elements of the statistical models used. The statistical software package R is increasingly popular, but the probability distribution method has not yet been implemented in R, …

Statistical Methods For Meta-Analysis In Large-Scale Genomic Experiments, Wimarsha Thathsarani Jayanetti

Mathematics & Statistics Theses & Dissertations

Recent developments in high throughput genomic assays have opened up the possibility of testing hundreds and thousands of genes simultaneously. With the availability of vast amounts of public databases, researchers tend to combine genomic analysis results from multiple studies in the form of a meta-analysis. Meta-analysis methods can be broadly classified into two main categories. The first approach is to combine the statistical significance (pvalues) of the genes from each individual study, and the second approach is to combine the statistical estimates (effect sizes) from the individual studies. In this dissertation, we will discuss how adherence to the standard null …

Estimation Of The Parameters In A Mixture Of Two Normal Distributions And The Generalized Pivotal Quantity Method, Md Faruk Hossain

UNLV Theses, Dissertations, Professional Papers, and Capstones

A pivotal quantity is a random variable that is a function of both the random data and the unknown population parameters and whose probability distribution does not depend on any of the unknown parameters. The population parameters here may include nuisance parameters. Historically, pivotal quantities have been used for the construction of test statistics for hypothesis testing of some of these unknown parameters. They have also been used for the construction of confidence intervals for some of these parameters.Generalized pivotal quantities (GPQ) were introduced by Tsui and Weerahandi (1989) and Weerahandi (1993). A GPQ is a function, not only of …

Use Of Healthcare Utilization Records For Analyzing Trends In Clinical Toxoplasmosis: A Comparison Of Nevada And The United States, Elijah Kreutzer

UNLV Theses, Dissertations, Professional Papers, and Capstones

Toxoplasmosis, a zoonotic disease caused by the parasitic protist Toxoplasma gondii, is a ubiquitous, global public health concern with a wide variety of clinical manifestations. Surveillance for the disease is lacking even in developed countries, and what surveillance is present most often focuses on pregnant women. This research investigated trends in clinical toxoplasmosis in Nevada and nationally to address the lack of knowledge concerning how Nevada discharges compare to national discharges in cases of toxoplasmosis. Specifically, this research sought to determine what characterizes toxoplasmosis in Nevada across inpatient, outpatient, and emergency department settings, as well as how these cases differ …

Bayesian Nonparametric Regression Models For Insurance Claims Frequency And Severity, Mostafa Shams Esfand Abadi

UNLV Theses, Dissertations, Professional Papers, and Capstones

The prediction of future insurance claims frequency and severity is one of the most important problems in actuarial science. Such predictions help the actuary set insurance premiums based on observed risk factors, or covariates. Accuracy of these predictions is important from the point of view of both the insurance company as well as the insured customer. Typically, actuaries use parametric regression models to predict claims based on the covariate information. Such models assume the same functional form tying the response to the covariates for each data point. These models are not flexible enough and fail to accurately capture at the …

Retrospective Varying Coefficient Association Analysis Of Longitudinal Binary Traits, Gang Xu

UNLV Theses, Dissertations, Professional Papers, and Capstones

Many genetic studies contain rich information on longitudinal phenotypes that require powerful analytical tools for optimal analysis. Genetic analysis of longitudinal data that incorporates temporal variation is important for understanding the genetic architecture and biological variation of complex diseases. Most of the existing methods assume that the contribution of genetic variants is constant over time and fails to capture the dynamic pattern of disease progression. However, the relative influence of genetic variants on complex traits fluctuates over time.We developed several tests to fill the gap of analyzing time-varying genetic effects in longitudinal GWAS for binary traits. First, we propose a …

Efficient Hierarchical Space-Time Models For Large Areal Datasets With Application To Forest Inventory Mapping Using Remote Sensing Imagery, Md Kamrul Hasan Khan

Graduate Theses and Dissertations

The focus of this dissertation is development of a novel hierarchical framework, that can be used for predictive modeling of Forest Inventory and Analysis (FIA) data over large regions. This dissertation has two significant contributions. Based on a study region in north-central Wisconsin, we analyze satellite imagery, along with a sample of national forest inventory field plots, to monitor and predict changes in forest conditions over time. The auxiliary data from the satellite imagery of this region are relatively dense in space and time, and can be used to learn how forest conditions changed over that decade. However, these records …

Evaluation Of Effect Of Preprocessing Algorithms On Resting State Fmri Data, Hortencia Josefina Hernandez

Open Access Theses & Dissertations

Graph theory modeling is a common modeling approach in neurobiology research studies. These models are useful since they describe patterns of connection for regions of interest in the brain using resting state fMRI images. The standard rule of thumb is to threshold the observed activation levels prior to model building. It is reasonable to assume that the use of this threshold affects the statistical distribution of commonly reported centrality metrics from the graph theory model, such as degree, betweenness, and closeness. In this study we examine the differential effect of using the standard approaches versus alternative direct thresholds and incorporation …