Statistics and Probability Commons^™

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 …

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 …

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 …

Natural Language Processing For Disaster Tweets, Akinyemi D. Apampa, Nan Li

Publications and Research

Our goal is to establish an automatic model that identifies which tweets are about natural disasters based on the content of the tweets. Our method is to construct a decision tree based on keyword searching. We will construct the model using 7,645 tweets and test our model on 3,465 tweets as an assessment of the performance.

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 …

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 Challenges And Methods For Missing And Imbalanced Data, Rose Adjei

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Missing data remains a prevalent issue in every area of research. The impact of missing data, if not carefully handled, can be detrimental to any statistical analysis. Some statistical challenges associated with missing data include, loss of information, reduced statistical power and non-generalizability of findings in a study. It is therefore crucial that researchers pay close and particular attention when dealing with missing data. This multi-paper dissertation provides insight into missing data across different fields of study and addresses some of the above mentioned challenges of missing data through simulation studies and application to real datasets. The first paper of …

Learning From Public Spaces In Historic Cities, Cody Josh Kucharski

Symposium of Student Scholars

Successful public spaces in cities are key for enhancing social cohesion and improving health and safety. Learning from historic cities involves the development of representational and analytical tools aimed at capturing their essence as places of human interaction. The research reports findings of the spatial analysis of twenty Adriatic and Ionian coastal cities, which addresses the question of how the network of public spaces calibrates different degrees of spatial enclosure necessary for creating successful social interactions. Cities in the littoral region include well-preserved historic centers that are renowned for the successful integration of urban squares into the urban fabric. For …

The Potential Of Private Health Insurance Ownership Based On The 2018-2020 National Socioeconomic Survey Data, Arief Rosyid Hasan, Adang Bachtiar, Cicilya Candi

Kesmas

In 2014, the Indonesian Government introduced a social security program in the health sector. However, Indonesia’s out-of-pocket expenses remain high due to a lack of public interest in National Health Insurance services. Financing expensive health services with high out-of-pocket expenses has the potential to cause poverty. Private health insurance is considered a solution to this problem. This study aimed to determine the socioeconomic factors of private health insurance ownership and its potential in Indonesia. This study used secondary data from the 2018, 2019, and 2020 National Socioeconomic Surveys. Logistic regression analysis showed that the variables related to private health insurance …

A Bootstrap Method For A Multiple-Imputation Variance Estimator In Survey Sampling, Lili Yu, Yichuan Zhao

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Rubin’s variance estimator of the multiple imputation estimator for a domain mean is not asymptotically unbiased. Kim et al. derived the closed-form bias for Rubin’s variance estimator. In addition, they proposed an asymptotically unbiased variance estimator for the multiple imputation estimator when the imputed values can be written as a linear function of the observed values. However, this needs the assumption that the covariance of the imputed values in the same imputed dataset is twice that in the different imputed datasets. In this study, we proposed a bootstrap variance estimator that does not need this assumption. Both theoretical argument and …

Pandemic Fatigue Impedes Mitigation Of Covid-19 In Hong Kong, Zhanwei Du, Lin Wang, Songwei Shan, Dickson Lam, Tim K. Tsang, Jingyi Xiao, Huizhi Gao, Bingyi Yang, Sheikh Taslim Ali, Sen Pei, Isaac Chun-Hai Fung, Eric H. Y. Lau, Qiuyan Liao, Peng Wu, Lauren Ancel Meyers, Gabriel M. Leung, Benjamin Cowling

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Hong Kong has implemented stringent public health and social measures (PHSMs) to curb each of the four COVID-19 epidemic waves since January 2020. The third wave between July and September 2020 was brought under control within 2 m, while the fourth wave starting from the end of October 2020 has taken longer to bring under control and lasted at least 5 mo. Here, we report the pandemic fatigue as one of the potential reasons for the reduced impact of PHSMs on transmission in the fourth wave. We contacted either 500 or 1,000 local residents through weekly random-digit dialing of landlines …

Association Between The Health Belief Model, Exercise, And Nutrition Behaviors During The Covid-19 Pandemic, Keagan Kiely, Bill Mase, Andrew R. Hansen, Jessica S. Schwind

Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications

Introduction: The COVID-19 pandemic has affected our nation’s health further than the infection it causes. Physical activity levels and dietary intake have suffered while individuals grapple with the changes in behavior to reduce viral transmission. With unique nuances regarding the access to physical activity and nutrition during the pandemic, the constructs of Health Belief Model (HBM) may present themselves differently in nutrition and exercise behaviors compared to precautions implemented to reduce viral transmission studied in previous research. The purpose of this study was to investigate the extent of exercise and nutritional behavior change during the COVID-19 pandemic and explain the …

Laboratory Evaluation And Field Feasibility Of Micro-Encapsulated Insecticide Effect On Rhodnius Prolixus And Triatoma Dimidiata Mortality In Rural Households In Boyaca, Colombia, Lidia Gual-Gonzalez, Manuel Medina, Cesar Valverde-Castro, Virgilio Beltran, Rodrigo Caro, Omar Triana-Chavez, Melissa Nolan Ph.D., Mph, Omar Cantillo-Barraza

Faculty Publications

Chagas disease is a neglected vector-borne zoonosis caused by the parasite Trypanosoma cruzi that is primarily transmitted by insects of the subfamily Triatominae. Although control efforts targeting domestic infestations of Rhodnius prolixus have been largely successful, with several regions in Boyacá department certified free of T. cruzi transmission by intradomicile R. prolixus, novel native species are emerging, increasing the risk of disease. Triatoma dimidiata is the second most important species in Colombia, and conventional control methods seem to be less effective. In this study we evaluated the efficacy and usefulness of micro-encapsulated insecticide paints in laboratory conditions and its …

Convexity Of Regularized Optimal Transport Dissimilarity Measures For Signed Signals, Christian P. Fowler

Mathematics & Statistics ETDs

Debiased Sinkhorn divergence (DS divergence) is a distance function of

regularized optimal transport that measures the dissimilarity between two

probability measures of optimal transport. This thesis analyzes the advantages of

using DS divergence when compared to the more computationally expensive

Wasserstein distance as well as the classical Euclidean norm. Specifically, theory

and numerical experiments are used to show that Debiased Sinkhorn divergence

has geometrically desirable properties such as maintained convexity after data

normalization. Data normalization is often needed to calculate Sinkhorn

divergence as well as Wasserstein distance, as these formulas only accept

probability distributions as inputs and do not directly …

Statistical Methods For Differential Gene Expression Analysis Under The Case-Cohort Design, Lidong Wang

Mathematics & Statistics ETDs

Differential gene expression analysis has the potential to discover candidate biomarkers, therapeutic targets, and gene signatures. How to save money when using an unaffordable sample is a practical question. The case-cohort (CCH) study design can blend the economy of case-control studies with the advantages of cohort studies. But it has not been seen in the medical research literature where high-throughput genomic data were involved.

A score test does not need to fit the Cox PH model iteratively; hence, it can save computing time and avoid potential convergence issues. We developed a score test under the CCH design to identify DEGs …

Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, Feridun Tasdan

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, Elizabeth Amona

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Estimating R0 For Dengue Emergence In Central Argentina Using Statistical Models, Sahil Chindal

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Functional Data Analysis Of Covid-19, Nichole L. Fluke

Mathematics & Statistics ETDs

This thesis deals with Functional Data Analysis (FDA) on COVID data. The Data involves counts for new COVID cases, hospitalized COVID patients, and new COVID deaths. The data used is for all the states and regions in the United States. The data starts in March 1^st, 2020 and goes through March 31^st, 2021. The FDA smooths the data and looks to see if there are similarities or differences between the states and regions in the data. The data also shows which states and regions stand out from the others and which ones are similar. Also shown …

The Dietary Inflammatory Index Is Associated With Subclinical Mastitis In Lactating European Women, Myriam C. Afeiche, Alison Iroz, Frank Thielecke, Antoino C. De Castro, Gregory Lefebvre, Colleen F. Draper, Cecilia Martiínez-Costa, Maria Jose Costeira, Mireille Vanpee, Claude Billeaud, Jean-Charles Picaud, Daryl Lim Kah Hian, Guimei Liu, Nitin Shivappa Mbbs, Mph, Ph.D., James Hébert Scd, Tinu M. Samuel

Faculty Publications

Subclinical mastitis (SCM) is an inflammatory state of the lactating mammary gland, which is asymptomatic and may have negative consequences for child growth. The objectives of this study were to: (1) test the association between the dietary inflammatory index (DII®) and SCM and (2) assess the differences in nutrient intakes between women without SCM and those with SCM. One hundred and seventy-seven women with available data on human milk (HM) sodium potassium ratio (Na:K) and dietary intake data were included for analysis. Multivariable logistic regression was used to examine the association between nutrient intake and the DII score in relation …

Statistical Methods For Reliability Test Planning And Data Analysis, Oluwaseun Elizabeth Otunuga

USF Tampa Graduate Theses and Dissertations

This dissertation develops several statistical methods to advance the techniques and applications in the fields of reliability test planning and data analysis as well as statistical modeling and analysis in survival analysis.

The first project focuses on developing new demonstration test plans for lifetime data based on considering multiple objectives. Reliability demonstration tests have been broadly used for assuring reliability performance at the desired confidence level. We consider lifetime data that follows a Weibull distribution which has been broadly used for modeling a variety of shapes of lifetime distributions. When planning a demonstration test, there are often multiple aspects to …

Music Genre Classification By Convolutional Neural Networks, Usame Suud

Mathematics & Statistics ETDs

In today’s world, deep learning models are widely used in a variety of fields. Audio

applications include speech recognition, audio classification, and music information

retrieval. In this paper, we will focus on the classification of music genres using an

artificial neural network. The development of audio machine learning techniques has

created an independence from traditional, more time-consuming signal processing

techniques. Starting with raw audio data, we will gain an understanding of what

audio is and its digital representation. Then, the focus will be on obtaining frequency

information from audio signals through the use of spectrograms. Transforming the

spectrograms into the …