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Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang 2020 University of South Florida

Identification Of Patterns And Disruptions In Ambient Sensor Data From Private Homes, Yan Wang

USF Tampa Graduate Theses and Dissertations

The world’s population is rapidly aging and the increasing demand for home and health care services from this aging population brings unprecedented challenges to the economy and society. Ambient-assisted smart homes, residences equipped with ambient sensors to monitor the resident’s daily activities in a continuous and unobtrusive way, present great potential to manage the growing care service needs of this older population segment, and enable them to age-in-place.

Despite growing research, using ambient sensor data from private homes to monitor daily activities, health and wellness still faces significant challenges. To study ambient sensor data from private homes where annotated data …


A Study Of Cusum Statistics On Bitcoin Transactions, Ivan Perez 2020 CUNY Hunter College

A Study Of Cusum Statistics On Bitcoin Transactions, Ivan Perez

Theses and Dissertations

In this thesis, our objective is to study the relationship between transaction price and volume in the BTC/USD Coinbase exchange. In the second chapter, we develop a consecutive CUSUM algorithm to detect instantaneous changes in the arrival rate of market orders. We begin by estimating a baseline rate using the assumption of a local time-homogeneous Poisson process. Our observations lead us to reject the plausibility of a time-homogeneous Poisson model on a more global scale by using a chi squared test. We thus proceed to use CUSUM-based alarms to detect consecutive upward and downward changes in the arrival rate of …


A Web-Based, Positive Emotion Skills Intervention For Enhancing Posttreatment Psychological Well-Being In Young Adult Cancer Survivors (Empower): Protocol For A Single-Arm Feasibility Trial, John M. Salsman, Laurie E. McLouth, Michael Cohn, Janet A. Tooze, Mia Sorkin, Judith T. Moskowitz 2020 Wake Forest University

A Web-Based, Positive Emotion Skills Intervention For Enhancing Posttreatment Psychological Well-Being In Young Adult Cancer Survivors (Empower): Protocol For A Single-Arm Feasibility Trial, John M. Salsman, Laurie E. Mclouth, Michael Cohn, Janet A. Tooze, Mia Sorkin, Judith T. Moskowitz

Behavioral Science Faculty Publications

BACKGROUND: Adolescent and young adult cancer survivors (AYAs) experience clinically significant distress and have limited access to supportive care services. Interventions to enhance psychological well-being have improved positive affect and reduced depression in clinical and healthy populations but have not been routinely tested in AYAs.

OBJECTIVE: The aim of this protocol is to (1) test the feasibility and acceptability of a Web-based positive emotion skills intervention for posttreatment AYAs called Enhancing Management of Psychological Outcomes With Emotion Regulation (EMPOWER) and (2) examine proof of concept for reducing psychological distress and enhancing psychological well-being.

METHODS: The intervention development and testing are …


Integrated Multiple Mediation Analysis: A Robustness–Specificity Trade-Off In Causal Structure, An-Shun Tai, Sheng-Hsuan Lin 2020 Institute of Statistics, National Chiao Tung University, Hsinchu, Taiwan.

Integrated Multiple Mediation Analysis: A Robustness–Specificity Trade-Off In Causal Structure, An-Shun Tai, Sheng-Hsuan Lin

Harvard University Biostatistics Working Paper Series

Recent methodological developments in causal mediation analysis have addressed several issues regarding multiple mediators. However, these developed methods differ in their definitions of causal parameters, assumptions for identification, and interpretations of causal effects, making it unclear which method ought to be selected when investigating a given causal effect. Thus, in this study, we construct an integrated framework, which unifies all existing methodologies, as a standard for mediation analysis with multiple mediators. To clarify the relationship between existing methods, we propose four strategies for effect decomposition: two-way, partially forward, partially backward, and complete decompositions. This study reveals how the direct and …


Waiting-Time Paradox In 1922, Naoki Masuda, Takayuki Hiraoka 2020 University at Buffalo

Waiting-Time Paradox In 1922, Naoki Masuda, Takayuki Hiraoka

Northeast Journal of Complex Systems (NEJCS)

We present an English translation and discussion of an essay that a Japanese physicist, Torahiko Terada, wrote in 1922. In the essay, he described the waiting-time paradox, also called the bus paradox, which is a known mathematical phenomenon in queuing theory, stochastic processes, and modern temporal network analysis. He also observed and analyzed data on Tokyo City trams to verify the relevance of the waiting-time paradox to busy passengers in Tokyo at the time. This essay seems to be one of the earliest documentations of the waiting-time paradox in a sufficiently scientific manner.


On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix 2020 University of Calgary

On Statistical Significance Of Discriminant Function Coefficients, Tolulope T. Sajobi, Gordon H. Fick, Lisa M. Lix

Journal of Modern Applied Statistical Methods

Discriminant function coefficients are useful for describing group differences and identifying variables that distinguish between groups. Test procedures were compared based on asymptotically approximations, empirical, and exact distributions for testing hypotheses about discriminant function coefficients. These tests are useful for assessing variable importance in multivariate group designs.


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 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 …


A Decision Tree Model To Predict Marginalized Zero-Inflated Poisson Mean, Philip Amewudah 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.


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 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 …


Sensitivity Analysis For Incomplete Data And Causal Inference, Heng Chen 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.


Statistical Models And Analysis Of Univariate And Multivariate Degradation Data, Lochana Palayangoda 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 …


Evaluation Of The Utility Of Informative Priors In Bayesian Structural Equation Modeling With Small Samples, Hao Ma 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 …


Side-Channel Power Resistance For Encryption Algorithms Using Implementation Diversity, Ivan M. Bow 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 …


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 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, Lauren A. Sugden 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, Housila P. Singh, Anita Yadav 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, Zaki Anwar, Neetu Gupta, Mohd Akram Raza Khan, Qazi Azhad Jamal 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, Joel R. Levin, John M. Ferron, Boris S. Gafurov 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, Shivaji Shripati Desai, D N. Kashid 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.


American Option Pricing: From Pde Numerical Solutions To Simulation-Based Methods And Reinforcement Learning., Chenshan Hu 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 …


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