A Decision Tree Model To Predict Marginalized Zero-Inflated Poisson Mean,
2020
University of New Orleans
A Decision Tree Model To Predict Marginalized Zero-Inflated Poisson Mean, Philip Amewudah
LSU New Orleans Theses and Dissertations
No abstract provided.
A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages,
2020
RAND Corporation
A Call For Consistency In The Official Naming Of The Disease Caused By Severe Acute Respiratory Syndrome Coronavirus 2 In Non-English Languages, Lu Dong, Zhe Li, Isaac Fung
Biostatistics, Epidemiology & Environmental Health Sciences: Faculty Publications
We investigated the adoption of World Health Organization (WHO) naming of COVID-19 into the respective languages among the Group of Twenty (G20) countries, and the variation of COVID-19 naming in the Chinese language across different health authorities. On May 7, 2020, we identified the websites of the national health authorities of the G20 countries to identify naming of COVID-19 in their respective languages, and the websites of the health authorities in mainland China, Hong Kong, Macau, Taiwan and Singapore and identify their Chinese name for COVID-19. Among the G20 nations, Argentina, China, Italy, Japan, Mexico, Saudi Arabia and Turkey do …
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons,
2020
University of Kentucky
Brain Structure Changes Over Time In Normal And Mildly Impaired Aged Persons, Charles D. Smith, Linda J. Van Eldik, Gregory A. Jicha, Frederick A. Schmitt, Peter T. Nelson, Erin L. Abner, Richard J. Kryscio, Richard R. Murphy, Anders H. Andersen
Neurology Faculty Publications
Structural brain changes in aging are known to occur even in the absence of dementia, but the magnitudes and regions involved vary between studies. To further characterize these changes, we analyzed paired MRI images acquired with identical protocols and scanner over a median 5.8-year interval. The normal study group comprised 78 elders (25M 53F, baseline age range 70-78 years) who underwent an annual standardized expert assessment of cognition and health and who maintained normal cognition for the duration of the study. We found a longitudinal grey matter (GM) loss rate of 2.56 ± 0.07 ml/year (0.20 ± 0.04%/year) and a …
Side-Channel Power Resistance For Encryption Algorithms Using Implementation Diversity,
2020
University of New Mexico
Side-Channel Power Resistance For Encryption Algorithms Using Implementation Diversity, Ivan M. Bow
Electrical and Computer Engineering ETDs
This thesis paper investigates countermeasures to hardware side-channel attacks and proposes a new solution to this ever growing threat against data integrity and security. The side-channel attack methods, differential power analysis and correlation power analysis, are both very powerful techniques and are used to gain access to secrets inside of a field programmable gate array that are otherwise inaccessible, in particular the cryptographic key for the Advanced Encryption Standard algorithm. To counter these attacks, we propose a method of changing the internal hardware configuration of the field programmable gate array using dynamic partial reconfiguration. Using this method, we change the …
Sensitivity Analysis For Incomplete Data And Causal Inference,
2020
Southern Methodist University
Sensitivity Analysis For Incomplete Data And Causal Inference, Heng Chen
Statistical Science Theses and Dissertations
In this dissertation, we explore sensitivity analyses under three different types of incomplete data problems, including missing outcomes, missing outcomes and missing predictors, potential outcomes in \emph{Rubin causal model (RCM)}. The first sensitivity analysis is conducted for the \emph{missing completely at random (MCAR)} assumption in frequentist inference; the second one is conducted for the \emph{missing at random (MAR)} assumption in likelihood inference; the third one is conducted for one novel assumption, the ``sixth assumption'' proposed for the robustness of instrumental variable estimand in causal inference.
Evaluation Of The Utility Of Informative Priors In Bayesian Structural Equation Modeling With Small Samples,
2020
Southern Methodist University
Evaluation Of The Utility Of Informative Priors In Bayesian Structural Equation Modeling With Small Samples, Hao Ma
Education Policy and Leadership Theses and Dissertations
The estimation of parameters in structural equation modeling (SEM) has been primarily based on the maximum likelihood estimator (MLE) and relies on large sample asymptotic theory. Consequently, the results of the SEM analyses with small samples may not be as satisfactory as expected. In contrast, informative priors typically do not require a large sample, and they may be helpful for improving the quality of estimates in the SEM models with small samples. However, the role of informative priors in the Bayesian SEM has not been thoroughly studied to date. Given the limited body of evidence, specifying effective informative priors remains …
Statistical Models And Analysis Of Univariate And Multivariate Degradation Data,
2020
Southern Methodist University
Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda
Statistical Science Theses and Dissertations
For degradation data in reliability analysis, estimation of the first-passage time (FPT) distribution to a threshold provides valuable information on reliability characteristics. Recently, Balakrishnan and Qin (2019; Applied Stochastic Models in Business and Industry, 35:571-590) studied a nonparametric method to approximate the FPT distribution of such degradation processes if the underlying process type is unknown. In this thesis, we propose improved techniques based on saddlepoint approximation, which enhance upon their suggested methods. Numerical examples and Monte Carlo simulation studies are used to illustrate the advantages of the proposed techniques. Limitations of the improved techniques are discussed and some possible solutions …
Co-Authorship Visualization Of Research On Covid-19 From Web Of Science Data Using Bibliometric Analysis,
2020
Department of Informatics Engineering, STMIK AKBA, Makassar, Indonesia
Co-Authorship Visualization Of Research On Covid-19 From Web Of Science Data Using Bibliometric Analysis, Akbar Iskandar, Firman Azis, Riskha Dora Candra Dewi, R. Rusli, Ansari Saleh Ahmar
Library Philosophy and Practice (e-journal)
Bibliometric analysis is one of the research approaches that utilizes quantitative and mathematical data to address problems posed in the context of visualization to see patterns in the field of science. In fact, bibliometric analysis may also include a wider overview of the names of the most influential writers in the area of science. This data analysis would discuss the co-authorship of COVID-19 research covering author productivity and author collaboration. The data was collected on 11th May 2020 of Web of Science (WoS) Core Collection database. The literature review was conducted using the keyword: TOPIC: ("covid") AND YEAR PUBLISHED: (2020). …
Statistical Inference Of Adaptation At Multiple Genomic Scales Using Supervised Classification And A Hidden Markov Model,
2020
Duquesne University
Statistical Inference Of Adaptation At Multiple Genomic Scales Using Supervised Classification And A Hidden Markov Model, Lauren A. Sugden
Biology and Medicine Through Mathematics Conference
No abstract provided.
A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters,
2020
Vikram University, Ujjain, India
A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters, Housila P. Singh, Anita Yadav
Journal of Modern Applied Statistical Methods
Classes of ratio-type estimators t (say) and ratio-type exponential estimators te (say) of the population mean are proposed, and their biases and mean squared errors under large sample approximation are presented. It is the class of ratio-type exponential estimators te provides estimators more efficient than the ratio-type estimators.
Recurrence Relations For Marginal And Joint Moment Generating Functions Of Topp-Leone Generated Exponential Distribution Based On Record Values And Its Characterization,
2020
Aligarh Muslim University
Recurrence Relations For Marginal And Joint Moment Generating Functions Of Topp-Leone Generated Exponential Distribution Based On Record Values And Its Characterization, Zaki Anwar, Neetu Gupta, Mohd Akram Raza Khan, Qazi Azhad Jamal
Journal of Modern Applied Statistical Methods
The exact expressions and some recurrence relations are derived for marginal and joint moment generating functions of kth lower record values from Topp-Leone Generated (TLG) Exponential distribution. This distribution is characterized by using the recurrence relation of the marginal moment generating function of kth lower record values.
An Improved Two Independent-Samples Randomization Test For Single-Case Ab-Type Intervention Designs: A 20-Year Journey,
2020
University of Arizona
An Improved Two Independent-Samples Randomization Test For Single-Case Ab-Type Intervention Designs: A 20-Year Journey, Joel R. Levin, John M. Ferron, Boris S. Gafurov
Journal of Modern Applied Statistical Methods
Detailed is a 20-year arduous journey to develop a statistically viable two-phase (AB) single-case two independent-samples randomization test procedure. The test is designed to compare the effectiveness of two different interventions that are randomly assigned to cases. In contrast to the unsatisfactory simulation results produced by an earlier proposed randomization test, the present test consistently exhibited acceptable Type I error control under various design and effect-type configurations, while at the same time possessing adequate power to detect moderately sized intervention-difference effects. Selected issues, applications, and a multiple-baseline extension of the two-sample test are discussed.
Support Vector Machine-Based Modified Sp Statistic For Subset Selection With Non-Normal Error Terms,
2020
Department of Statistics, Gopal Krishna Gokhale College, Kolhapur (MS), India.
Support Vector Machine-Based Modified Sp Statistic For Subset Selection With Non-Normal Error Terms, Shivaji Shripati Desai, D N. Kashid
Journal of Modern Applied Statistical Methods
Support vector machine (SVM) is used for estimation of regression parameters to modify the sum of cross products (Sp). It works well for some nonnormal error distributions. The performance of existing robust methods and the modified Sp is evaluated through simulated and real data. The results show the performance of the modified Sp is good.
Multilevel Asymptotic Parallel-In-Time Techniques For Temporally Oscillatory Pdes,
2020
University of New Mexico - Main Campus
Multilevel Asymptotic Parallel-In-Time Techniques For Temporally Oscillatory Pdes, Nicholas Abel
Mathematics & Statistics ETDs
As the clock speeds of individual processors level off and the amount of parallel resources continue to increase rapidly, further exploitation of parallelism is necessary to improve compute times. For time-dependent differential equations, the serial computation of time-stepping presents a bottleneck, but parallel-in-time integration methods offer a way to compute the solution in parallel along the time domain. Parallel-in-time methods have been successful in achieving speedup when computing solutions for parabolic problems; however, for problems with large hyperbolic terms and no strong diffusivity, parallel-in-time methods have traditionally struggled to offer speedup. While work has been done to understand why parallel-in-time …
Flexible Box-Cox Transformation Model For Analyzing Energy Usage At Uconn,
2020
University of Connecticut
Flexible Box-Cox Transformation Model For Analyzing Energy Usage At Uconn, Yutong Chen
Honors Scholar Theses
The Box-Cox transformation is a way to transform non-normal data into more normally distributed data. However, when we fit linear regression models to transformed data, we cannot use the Akaike Information Criterion (AIC) directly to compare different models since the transformed data are no longer on the same scale. In this study, the Jacobian adjusted AIC is proposed to compare regression models on transformed data and to select an “optimal” value of the transformation parameter. Instead of using a single for the whole data, which is commonly used in the literature and in practice, we formulate a linear regression pattern …
American Option Pricing: From Pde Numerical Solutions To Simulation-Based Methods And Reinforcement Learning.,
2020
Washington University in St. Louis
American Option Pricing: From Pde Numerical Solutions To Simulation-Based Methods And Reinforcement Learning., Chenshan Hu
Arts & Sciences Graduate Student Theses and Dissertations
An American call (put) option is a contract that gives the holder the right, but not the obligation, to buy (sell) one unit of an asset (typically, stock) at a prespecified price (called strike price) at any desired time before a preset expiration time of the contract. The associated option pricing problem plays an important role in modern financial markets and one way to solve this is by searching for the optimal exercise policy, i.e., find the optimal time to exercise so that maximal reward is achieved. In this thesis, we shall discuss the modern Least Square Policy Iteration Method …
Bayesian Variable Selection And Post-Selection Inference,
2020
Washington University in St. Louis
Bayesian Variable Selection And Post-Selection Inference, Qiyiwen Zhang
Arts & Sciences Graduate Student Theses and Dissertations
In this dissertation, we first develop a novel perspective to compare Bayesian variable selection procedures in terms of their selection criteria as well as their finite-sample properties. Secondly, we investigate Bayesian post-selection inference in two types of selection problems: linear regression and population selection. We will demonstrate that both inference problems are susceptible to selection effects since the selection procedure is data-dependent. Before comparing Bayesian variable selection procedures, we first classify the current Bayesian variable selection procedures into two classes: those with selection criteria defined on the space of candidate models, and those with selection criteria not explicitly formulated on …
“The Prediction Of Fantasy Football”,
2020
Louisiana Tech University
“The Prediction Of Fantasy Football”, Chelsea Robinson
Mathematics Senior Capstone Papers
In this paper, we consider the game fantasy football, which allows people to simulate being a National Football League team owner. Imaginary owners select from the best players in the NFL and compete on weekly basis based upon player performances on the field. Fantasy football has become popular over the years. In 2011, according to the Fantasy Sports Trade Association there were 35 million people that played fantasy sports online in the United States and Canada. The most major companies that use fantasy football are Yahoo, ESPN, and NFL, even though there are more platforms. Many people use these platforms …
The Primary Volatile Composition Of Comet C/2015 Er61 (Panstarrs),
2020
University of Missouri-St. Louis
The Primary Volatile Composition Of Comet C/2015 Er61 (Panstarrs), Aaron Butler
Theses
In the outer edges of the solar system exist two regions: the Kuiper belt and Oort cloud. These two regions have a high amount of icy bodies (comets) orbiting the Sun. Comets located within the Oort cloud and Kuiper belt contain an ancient codex to the solar systems contents, before the formation of our solar system. Presented are near-infrared, high-resolution (λ/Δλ ~40000) data obtained from the immersion-grating echelle spectrograph iSHELL at the 3m NASA Infrared Telescope Facility (IRTF) in Maunakea, Hawaii of the Oort cloud comet C/2015 ER61 (PANSTARRS). Observations took place on April 15 and 17 in 2017 while …
Mentoring Undergraduate Research In Statistics: Reaping The Benefits And Overcoming The Barriers,
2020
Northern Kentucky University
Mentoring Undergraduate Research In Statistics: Reaping The Benefits And Overcoming The Barriers, Joseph R. Nolan, Kelly S. Mcconville, Vittorio Addona, Nathan L. Tintle, Dennis K. Pearl
Faculty Work Comprehensive List
Undergraduate research experiences (UREs), whether within the context of a mentor-mentee experience or a classroom framework, represent an excellent opportunity to expose students to the independent scholarship model. The high impact of undergraduate research has received recent attention in the context of STEM disciplines. Reflecting a 2017 survey of statistics faculty, this article examines the perceived benefits of UREs, as well as barriers to the incorporation of UREs, specifically within the field of statistics. Viewpoints of students, faculty mentors, and institutions are investigated. Further, the article offers several strategies for leveraging characteristics unique to the field of statistics to overcome …
