Statistics and Probability Commons^™

(R1899) Asymptotic Normality Of The Conditional Hazard Function In The Local Linear Estimation Under Functional Mixing Data, Amina Goutal, Boubaker Mechab, Omar Fetitah, Torkia Merouan

Applications and Applied Mathematics: An International Journal (AAM)

In this study, we are interested in using the local linear technique to estimate the conditional hazard function for functional dependent data where the scalar response is conditioned by a functional random variable. The asymptotic normality of this constructed estimator is demonstrated under some extreme conditions. Our estimator’s performance is demonstrated through simulations.

(R1971) Analysis Of Feedback Queueing Model With Differentiated Vacations Under Classical Retrial Policy, Poonam Gupta, Naveen Kumar, Rajni Gupta

Applications and Applied Mathematics: An International Journal (AAM)

This paper analyzes an M/M/1 retrial queue under differentiated vacations and Bernoulli feedback policy. On receiving the service, if the customer is not satisfied, then he may join the retrial group again with some probability and demand for service or may leave the system with the complementary probability. Using the probability generating functions technique, the steady-state solutions of the system are obtained. Furthermore, we have obtained some of the important performance measures such as expected orbit length, expected length of the system, sojourn times and probability of server being in different states. Using MATLAB software, we have represented the graphical …

(R1984) Analysis Of M^[X1], M^[X2]/G1, G_2^(A,B)/1 Queue With Priority Services, Server Breakdown, Repair, Modified Bernoulli Vacation, Immediate Feedback, G. Ayyappan, S. Nithya, B. Somasundaram

Applications and Applied Mathematics: An International Journal (AAM)

In this investigation, the steady state analysis of two individualistic batch arrival queues with immediate feedback, modified Bernoulli vacation and server breakdown are introduced. Two different categories of customers like priority and ordinary are to be considered. This model propose nonpreemptive priority discipline. Ordinary and priority customers arrive as per Poisson processes. The server consistently afford single service for priority customers and the general bulk service for the ordinary customers and the service follows general distribution. The ordinary customers to be served only if the batch size should be greater than or equal to "a", else the server should not …

(R2024) A New Weighted Poisson Distribution For Over- And Under-Dispersion Situations, Michel Koukouatikissa Diafouka, Gelin Chedly Louzayadio, Rodnellin Onéime Malouata

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we propose a four-parameter weighted Poisson distribution that includes and generalizes the weighted Poisson distribution proposed by Castillo and Pérez-Casany and the Conway- Maxwell-Poisson distribution, as well as other well-known distributions. It is a distribution that is a member of the exponential family and is an exponential combination formulation between the weighted Poisson distribution proposed by Castillo and Pérez-Casany and the Conway-Maxwell- Poisson distribution. This new distribution with an additional parameter of dispersion is more flexible, and the Fisher dispersion index can be greater than, equal to, or less than one. This last property allows it to …

(R1953) M-Regression Estimation With The K Nearest Neighbors Smoothing Under Quasi-Associated Data In Functional Statistics, Bellatrach Nadjet, Bouabsa Wahiba, Attouch Mohammed Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

The main goal of this paper is to study the non parametric M-estimation under quasi-associated sequence with the k Nearest Neighbor’s method shortly (kNN). We construct an estimator of this nonparametric function and we study its asymptotic properties. Furthermore, a comparison study based on simulated data is also provided to illustrate the highly sensitive of the kNN approach to the presence of even a small proportion of outliers in the data.

A Comparison Of Logistic, Ridge, And Lasso Regression With Heart Failure Risk Data: Effects Of Sample Size, Predictor Correlation, And Predictor Weight On Outcome Accuracy, Mahmoud M. Aljuhani

Electronic Theses and Dissertations

Logistic Regression (LR), LASSO regression, and RIDGE regression are standard classification techniques for predicting a dichotomous output. Since these methods are applied for similar purposes and have different features, it is crucial to evaluate the performance of these methods under different controlled conditions. With this information, researchers can apply the optimal method for specific conditions.

Following previous research, which reported the effects of conditions such as sample size and multicollinearity on the performance of the classification methods, this research focused on the effects of when sample size, level of predictor collinearity, and predictor variable weight are controlled on the performance …

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 …

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 …

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 …

(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.

(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 …

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 …

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 …

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 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 …

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 …

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 …

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. …

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 …

Green On The Map - The Influence Of Conservation Easements On The Naturalness Of Landscapes In The United States, Nakisha Fouch

All Dissertations

Large protected areas have long been the cornerstone of conservation biology, however, in an era branded by the human dominance of ecosystems, regional landscape structure and function are often a consequence of accumulated land-use decisions that may or may not include a nod to conservation planning. With underrepresentation of habitats in publicly protected areas, attention has focused on the function of alternative land conservation mechanisms. Private conservation easements (CEs) have proliferated in the United States, yet assessing landscape-level function is confounded by holder and donor intent, national and regional policy, regional landscape contexts, varying extents, resolution, and temporal scale. Over …

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 …