Physical Sciences and Mathematics Commons^™

Dynamic Neuromechanical Sets For Locomotion, Aravind Sundararajan

Doctoral Dissertations

Most biological systems employ multiple redundant actuators, which is a complicated problem of controls and analysis. Unless assumptions about how the brain and body work together, and assumptions about how the body prioritizes tasks are applied, it is not possible to find the actuator controls. The purpose of this research is to develop computational tools for the analysis of arbitrary musculoskeletal models that employ redundant actuators. Instead of relying primarily on optimization frameworks and numerical methods or task prioritization schemes used typically in biomechanics to find a singular solution for actuator controls, tools for feasible sets analysis are instead developed …

Analysis Of Map/Ph/1 Queueing Model With Breakdown, Instantaneous Feedback And Server Vacation, G. Ayyappan, K. Thilagavathy

Applications and Applied Mathematics: An International Journal (AAM)

In this article, we analyze a single server queueing model with feedback, a single vacation under Bernoulli schedule, breakdown and repair. The arriving customers follow the Markovian Arrival Process (MAP) and service follow the phase-type distribution. When the server returns from vacation, if there is no one present in the system, the server will wait until the customer’s arrival. When the service completion epoch if the customer is not satisfied then that customer will get the service immediately. Under the steady-state probability vector that the total number of customers are present in the system is probed by the Matrix-analytic method. …

On A New Class Of Bivariate Survival Distributions Based On The Model Of Dependent Lives And Its Generalization, Shirin Shoaee

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, a new class of survival distributions based on the model of dependent lives and proportional hazard rate family is introduced. This new family of bivariate survival models contains several bivariate lifetime models and is more flexible. The main purpose of this paper is to generalize this family of bivariate survival distributions of dependent lives so that more flexible models can be achieved. These new families of distributions are called the bivariate proportional hazard rate (BPHR) and the bivariate proportional hazard rate-geometric (BPHRG) families, respectively. It is also observed that, if θ = 1, then the BPHR family …

Nonparametric M-Regression With Scale Parameter For Functional Dependent Data, Mebsout Mokhtaria, Attouch M. Kadi, Fetitah Omar

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, we study the equivariant nonparametric robust regression estimation relationship between a functional dependent random covariable and a scalar response. We consider a new robust regression estimator when the scale parameter is unknown. The consistency result of the proposed estimator is studied, namely the uniform almost complete convergence (with rate). Thus, suitable topological considerations are needed, implying changes in the convergence rates, which are quantified by entropy considerations. The benefits of considering robust estimators are illustrated on two real data sets where the robust fit reveals the presence of influential outliers.

The Linear Combination Of Kernels In The Estimation Of Cumulative Distribution Functions, Abdel-Razzaq Mugdadi, Rugayyah Sani

Applications and Applied Mathematics: An International Journal (AAM)

The kernel distribution function estimator method is the most popular nonparametric method to estimate the cumulative distribution function F(x). In this investigation, we propose a new estimator for F(x) based on a linear combination of kernels. The mean integrated squared error, asymptotic mean integrated squared error and the asymptotically optimal bandwidth for the new estimator are derived. Also, based on the plug-in technique in density estimation, we propose a data based method to select the bandwidth for the new estimator. In addition, we evaluate the new estimator using simulations and real life data.

Uganda As A Role Model For Pandemic Containment In Africa, Ahmed M. Sarki, Alex Ezeh, Saverio Stranges

Epidemiology and Biostatistics Publications

No abstract provided.

Random Search Plus: A More Effective Random Search For Machine Learning Hyperparameters Optimization, Bohan Li

Masters Theses

Machine learning hyperparameter optimization has always been the key to improve model performance. There are many methods of hyperparameter optimization. The popular methods include grid search, random search, manual search, Bayesian optimization, population-based optimization, etc. Random search occupies less computations than the grid search, but at the same time there is a penalty for accuracy. However, this paper proposes a more effective random search method based on the traditional random search and hyperparameter space separation. This method is named random search plus. This thesis empirically proves that random search plus is more effective than random search. There are some case …

Participatory Video As A Novel Recovery-Oriented Intervention In Early Psychosis: A Pilot Study., Arlene G Macdougall, Sahana Kukan, Elizabeth Price, Sarah Glen, Richelle Bird, Laura Powe, Joshua C. Wiener, Paul H Lysaker, Kelly K Anderson, Ross Mg Norman

Epidemiology and Biostatistics Publications

BACKGROUND: Personal narrative plays an important role in the process of recovery from psychotic illnesses. Participatory video is a novel, active intervention that can be used as a tool for fostering narrative development among people with psychosis.

AIM: To assess the feasibility, acceptability and potential clinical utility of participatory video as an innovative tool for promoting recovery in early psychosis.

METHODS: Ten outpatients of an early psychosis intervention programme were recruited to participate in 13 biweekly workshops to plan, film and produce documentary-style videos of their experiences. Feasibility was measured through recruitment and retention. Acceptability was measured through workshop attendance …

Delta Hedging Of Financial Options Using Reinforcement Learning And An Impossibility Hypothesis, Ronak Tali

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

In this thesis we take a fresh perspective on delta hedging of financial options as undertaken by market makers. The current industry standard of delta hedging relies on the famous Black Scholes formulation that prescribes continuous time hedging in a way that allows the market maker to remain risk neutral at all times. But the Black Scholes formulation is a deterministic model that comes with several strict assumptions such as zero transaction costs, log normal distribution of the underlying stock prices, etc. In this paper we employ Reinforcement Learning to redesign the delta hedging problem in way that allows us …

Comparative Evaluation Of Statistical Dependence Measures, Eman Abdel Rahman Ibrahim

Graduate Theses and Dissertations

Measuring and testing dependence between random variables is of great importance in many scientific fields. In the case of linearly correlated variables, Pearson’s correlation coefficient is a commonly used measure of the correlation strength. In the case of nonlinear correlation, several innovative measures have been proposed, such as distance-based correlation, rank-based correlations, and information theory-based correlation. This thesis focuses on the statistical comparison of several important correlations, including Spearman’s correlation, mutual information, maximal information coefficient, biweight midcorrelation, distance correlation, and copula correlation, under various simulation settings such as correlative patterns and the level of random noise. Furthermore, we apply those …

Gene Set Testing By Distance Correlation, Sho-Hsien Su

Graduate Theses and Dissertations

Pathways are the functional building blocks of complex diseases such as cancers. Pathway-level studies may provide insights on some important biological processes. Gene set test is an important tool to study the differential expression of a gene set between two groups, e.g., cancer vs normal. The differential expression of a gene set could be due to the difference in mean, variability, or both. However, most existing gene set tests only target the mean difference but overlook other types of differential expression. In this thesis, we propose to use the recently developed distance correlation for gene set testing. To assess the …

The Impact Of The Diabetes Management Incentive On Diabetes-Related Services: Evidence From Ontario, Canada., Thaksha Thavam, Rose Anne Devlin, Amardeep Thind, Gregory S Zaric, Sisira Sarma

Epidemiology and Biostatistics Publications

Financial incentives have been introduced in several countries to improve diabetes management. In Ontario, the most populous province in Canada, a Diabetes Management Incentive (DMI) was introduced to family physicians practicing in patient enrollment models in 2006. This paper examines the impact of the DMI on diabetes-related services provided to individuals with diabetes in Ontario. Longitudinal health administrative data were obtained for adults diagnosed with diabetes and their family physicians. The study population consisted of two groups: DMI group (patients enrolled with a family physician exposed to DMI for 3 years), and comparison group (patients affiliated with a family physician …

Development Of An Effect Size To Classify The Magnitude Of Dif In Dichotomous And Polytomous Items, James D. Weese

Graduate Theses and Dissertations

A standardized effect size for the SIBTEST/POLYSIBTEST procedure is proposed, allowing for Differential Item Functioning (DIF) to be classified with a single set of DIF heuristics regardless of whether data are dichotomous or polytomous. This proposed standardized effect size accounts for both variability in responses and whether participants are included in the SIBTEST/POLYSIBTEST calculations. First, a new set of unstandardized effect size heuristics are established for dichotomous data that are more aligned with Educational Testing Service (ETS) standards using two and three parameter logistic (2PL and 3PL) models. Second, a standardized effect size is proposed and compared to other DIF …

Gardasil Vaccine Trends Within Nevada, California, And The U.S.: A Comparative Study, Karen S. Gutierrez

UNLV Theses, Dissertations, Professional Papers, and Capstones

Despite decreasing incidence in cervical cancer in the U.S., there continues to be an increase in public health concern for cervical cancer worldwide. Recent studies report that individuals are disproportionately affected based on region, sex, and race. Additionally, the human papillomavirus (HPV) attributable cancers may be reduced between 70% and 90% through the universal use of HPV-vaccines. In order to expand current knowledge and implement intervention programs in Nevada, it is critical to examine the associations among the Gardasil vaccine, cervical cancer screening, and adverse events following immunization as well as to understand the different socio-demographic subgroups affected. To our …

Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das

Electronic Theses and Dissertations

Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …

Modified-Half-Normal Distribution And Different Methods To Estimate Average Treatment Effect., Jingchao Sun

Electronic Theses and Dissertations

This dissertation consists of three projects related to Modified-Half-Normal distribution and causal inference. In my first project, a new distribution called Modified-Half-Normal distribution was introduced. I explored a few of its distributional properties, the procedures for generating random samples based on Bayesian approaches, and the parameter estimation based on the method of moments. The second project deals with the problem of selection bias of average treatment effect (ATE) if we use the observational data. I combined the propensity score based inverse probability of treatment weighting (IPTW) method and the directed acyclic graph (DAG) to solve this problem. The third project …

Aspects Of Causal Inference., John A. Craycroft

Electronic Theses and Dissertations

Observational studies differ from experimental studies in that assignment of subjects to treatments is not randomized but rather occurs due to natural mechanisms, which are usually hidden from researchers. Yet objectives of the two studies are frequently the same: identify the causal – rather than merely associational – relationship between some treatment or exposure and an outcome. The statistical issues that arise in properly analyzing observational data for this goal are numerous and fascinating, and these issues are encompassed in the domain of causal inference. The research presented in this dissertation explores several distinct aspects of causal inference. This dissertation …

Developing A Tourism Opportunity Index Regarding The Prospective Of Overtourism In Nepal, Susan Phuyal

MSU Graduate Theses

This research explores Nepal's overtourism scenario based on the capacity of a locality to manage sustainable tourism practices. Environmental degradation, local infrastructure degradation, negative tourist experience and local resident responses regarding visitors are the four main variables used in this study to analyze overtourism. In order to analyze the case study of overtourism, we select the three top touristic cities of Nepal, Kathmandu, Pokhara, and Chitwan based on the number of annual visitors. Nepal's case analysis of overtourism conditions reviews the overall threat of over-tourism and establishes a metric by which tourism can be viewed as potentially detrimental to sustainability. …

A Management Strategy Evaluation Of The Impacts Of Interspecific Competition And Recreational Fishery Dynamics On Vermilion Snapper (Rhomboplites Aurorubens) In The Gulf Of Mexico, Megumi C. Oshima

Dissertations

In the Gulf of Mexico (GOM), Vermilion Snapper (Rhomboplites auroruben), are believed to compete with Red Snapper directly for prey and habitat. The two species share similar diets and have significant spatial overlap in the Gulf. Red Snapper are thought to be the dominate competitor, forcing Vermilion Snapper to feed on less nutritious prey when local resources are depleted. In addition to ecological pressures, GOM Vermilion Snapper support substantial commercial and recreational fisheries. Over the past decade, recreational landings have steadily increased, reaching a historical high in 2018. One cause may be stricter regulations for similar target species such as …

Impatient Customers In An Markovian Queue With Bernoulli Schedule Working Vacation Interruption And Setup Time, P. Manoharan, T. Jeeva

Applications and Applied Mathematics: An International Journal (AAM)

In this paper, using probability generating function method, Impatient customers in an Markovian queue with Bernoulli schedule working vacation interruption and setup time is discussed. Customers impatience is due to the servers vacation. During the working vacation period, if there are customers in the queue, the vacation can be interrupted at a service completion instant and the server begins a regular service period with probability (1 - b) or continues the vacation with probability b. We obtain the probability generating functions of the stationary state probabilities, performance measures, sojourn time of a customer and stochastic decomposition of the queue length, …

On A Multiserver Queueing System With Customers’ Impatience Until The End Of Service Under Single And Multiple Vacation Policies, Mokhtar Kadi, Amina A. Bouchentouf, Lahcene Yahiaoui

Applications and Applied Mathematics: An International Journal (AAM)

This paper deals with a multiserver queueing system with Bernoulli feedback and impatient customers (balking and reneging) under synchronous multiple and single vacation policies. Reneged customers may be retained in the system. Using probability generating functions (PGFs) technique, we formally obtain the steady-state solution of the proposed queueing system. Further, important performance measures and cost model are derived. Finally, numerical examples are presented.

Statistics Of Branched Populations Split Into Different Types, Thierry E. Huillet

Applications and Applied Mathematics: An International Journal (AAM)

Some population is made of n individuals that can be of P possible species (or types) at equilibrium. How are individuals scattered among types? We study two random scenarios of such species abundance distributions. In the first one, each species grows from independent founders according to a Galton-Watson branching process. When the number of founders P is either fixed or random (either Poisson or geometrically-distributed), a question raised is: given a population of n individuals as a whole, how does it split into the species types? This model is one pertaining to forests of Galton-Watson trees. A second scenario that …

Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek

Graduate Theses and Dissertations

Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear models, …

Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, Shanshan Zhang

Graduate Theses and Dissertations

Over the past years, efforts have been devoted to the genome-wide analysis of genetic and epigenetic profiles to better understand the underlying biological mechanisms of complex diseases such as cancer. It is of great importance to unravel the complex dependence structure between biological factors, and many conditional dependence tests have been developed to meet this need. The traditional partial correlation method can only capture the linear partial correlation, but not the nonlinear correlation. To overcome this limitation, we propose to use the innovative conditional distance correlation (CDC), which measures the conditional dependence between random vectors and detect nonlinear relations. In …

On Simes’S Second Conjecture: An Extended Single-Step Simes Test Procedure For Multiple Testing, Matthew G. Hudson

Dissertations

One of the major concerns with multiple tests of significance is controlling the family wise error rate. Various methods have been developed to ensure that the false positive rate be maintained at some prespecified level. One of the most well know being the Bonferroni procedure. Simes presented an improved Bonferroni procedure for testing the global hypothesis that is more powerful and less conservative, especially with positively correlated tests. While Simes’s procedure is more powerful, it does not allow for making inferences on the individual hypotheses. However, the Simes procedure has since become the foundation of many p-value based multiple testing …

Bayesian Variable Selection Methods For Genome-Wide Association Studies With Categorical Phenotypes, Benazir Rowe

UNLV Theses, Dissertations, Professional Papers, and Capstones

Genome-wide association studies (GWAS) attempt to find the associations between genetic markers and studied traits (phenotypes). The problem of GWAS is complex and various methods have been developed to approach it. One of such methods is Bayesian variable selection (BVS). We describe the BVS methods in detail and demonstrate the ability of BVS method Posterior Inference via Model Averaging and Subset Selection (piMASS) to improve the power of detecting phenotype-associated genetic loci, potentially leading to new discoveries from existing data without increasing the sample size.

We present several ways to improve and extend the applicability of piMASS for GWAS. The …

Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman

Master's Theses

Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …

Inference And Estimation In Change Point Models For Censored Data, Kristine Gierz

Mathematics & Statistics Theses & Dissertations

In general, the change point problem considers inference of a change in distribution for a set of time-ordered observations. This has applications in a large variety of fields and can also apply to survival data. With improvements to medical diagnoses and treatments, incidences and mortality rates have changed. However, the most commonly used analysis methods do not account for such distributional changes. In survival analysis, change point problems can concern a shift in a distribution for a set of time-ordered observations, potentially under censoring or truncation.

In this dissertation, we first propose a sequential testing approach for detecting multiple change …

Development Of A Statistical Model To Predict Materials’ Unit Prices For Future Maintenance And Rehabilitation In Highway Life Cycle Cost Analysis, Changmo Kim, Ghazan Khan, Brent Nguyen, Emily L. Hoang

Mineta Transportation Institute

The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were …

Statistical Methods With A Focus On Joint Outcome Modeling And On Methods For Fire Science, Da Zhong Xi

Electronic Thesis and Dissertation Repository

Understanding the dynamics of wildfires contributes significantly to the development of fire science. Challenges in the analysis of historical fire data include defining fire dynamics within existing statistical frameworks, modeling the duration and size of fires as joint outcomes, identifying the how fires are grouped into clusters of subpopulations, and assessing the effect of environmental variables in different modeling frameworks. We develop novel statistical methods to consider outcomes related to fire science jointly. These methods address these challenges by linking univariate models for separate outcomes through shared random effects, an approach referred to as joint modeling. Comparisons with existing …