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Stochastic Averaging For Multiple Cooperative And Antagonistic Molecular Motors, Joe Klobusicky 2018 Rensselaer Polytechnic Institute

Stochastic Averaging For Multiple Cooperative And Antagonistic Molecular Motors, Joe Klobusicky

Biology and Medicine Through Mathematics Conference

No abstract provided.


Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares 2018 University of Richmond

Quantitative Electroencephalography For Detecting Concussions, Sara Krehbiel, Kathy Hoke, Joanna Wares

Biology and Medicine Through Mathematics Conference

No abstract provided.


Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn 2018 Melbourne Business School

Inversion Copulas From Nonlinear State Space Models With An Application To Inflation Forecasting, Michael S. Smith, Worapree Ole Maneesoonthorn

Michael Stanley Smith

We propose the construction of copulas through the inversion of nonlinear state space models. These copulas allow for new time series models that have the same serial dependence structure as a state space model, but with an arbitrary marginal distribution, and flexible density forecasts. We examine the time series properties of the copulas, outline serial dependence measures, and estimate the models using likelihood-based methods. Copulas constructed from three example state space models are considered: a stochastic volatility model with an unobserved component, a Markov switching autoregression, and a Gaussian linear unobserved component model. We show that all three inversion copulas ...


Algorithmic Trading With Prior Information, Xinyi Cai 2018 Washington University in St. Louis

Algorithmic Trading With Prior Information, Xinyi Cai

Arts & Sciences Electronic Theses and Dissertations

Traders utilize strategies by using a mix of market and limit orders to generate profits. There are different types of traders in the market, some have prior information and can learn from changes in prices to tweak her trading strategy continuously(Informed Traders), some have no prior information but can learn(Uninformed Learners), and some have no prior information and cannot learn(Uninformed Traders). In this thesis. Alvaro C, Sebastian J and Damir K \cite{AL} proposed a model for algorithmic traders to access the impact of dynamic learning in profit and loss in 2014. The traders can employ the ...


The Properties Of Partial Trace And Block Trace Operators Of Partitioned Matrices, Katarzyna Filipiak, Daniel Klein, Erika Vojtková 2018 Poznań University Of Technology

The Properties Of Partial Trace And Block Trace Operators Of Partitioned Matrices, Katarzyna Filipiak, Daniel Klein, Erika Vojtková

Electronic Journal of Linear Algebra

The aim of this paper is to give the properties of two linear operators defined on non-square partitioned matrix: the partial trace operator and the block trace operator. The conditions for symmetry, nonnegativity, and positive-definiteness are given, as well as the relations between partial trace and block trace operators with standard trace, vectorizing and the Kronecker product operators. Both partial trace as well as block trace operators can be widely used in statistics, for example in the estimation of unknown parameters under the multi-level multivariate models or in the theory of experiments for the determination of an optimal designs under ...


Preface: International Conference On Matrix Analysis And Its Applications -- Mattriad 2017, Oskar Maria Baksalary, Natalia Bebiano, Heike Fassbender, Simo Puntanen 2018 University of Tampere

Preface: International Conference On Matrix Analysis And Its Applications -- Mattriad 2017, Oskar Maria Baksalary, Natalia Bebiano, Heike Fassbender, Simo Puntanen

Electronic Journal of Linear Algebra

No abstract provided.


Consistent Saliency Benchmarking: How One Model Can Win On All Metrics, Matthias Kümmerer, Thomas S.A. Wallis, Matthias Bethge 2018 Centre for Integrative Neuroscience, Tübingen

Consistent Saliency Benchmarking: How One Model Can Win On All Metrics, Matthias Kümmerer, Thomas S.A. Wallis, Matthias Bethge

MODVIS Workshop

No abstract provided.


Re-Evaluating Performance Measurement: New Mathematical Methods To Address Common Performance Measurement Challenges, Jordan David Benis 2018 Duquesne University

Re-Evaluating Performance Measurement: New Mathematical Methods To Address Common Performance Measurement Challenges, Jordan David Benis

Electronic Theses and Dissertations

Performance Measurement is an essential discipline for any business. Robust and reliable performance metrics for people, processes, and technologies enable a business to identify and address deficiencies to improve performance and profitability. The complexity of modern operating environments presents real challenges to developing equitable and accurate performance metrics. This thesis explores and develops two new methods to address common challenges encountered in businesses across the world. The first method addresses the challenge of estimating the relative complexity of various tasks by utilizing the Pearson Correlation Coefficient to identify potentially over weighted and under weighted tasks. The second method addresses the ...


Model Misspecification And Assumption Violations With The Linear Mixed Model: A Meta-Analysis, Brandon LeBeau, Yoon Ah Song, Wei Cheng Liu 2018 University of Iowa

Model Misspecification And Assumption Violations With The Linear Mixed Model: A Meta-Analysis, Brandon Lebeau, Yoon Ah Song, Wei Cheng Liu

Department of Psychological and Quantitative Foundations Publications

This meta analysis attempts to synthesize the Monte Carlo literature for the linear mixed model under a longitudinal framework. The empirical type I error rate will serve as the effect size and Monte Carlo simulation conditions will be coded to serve as moderator variables. The type I error rate for the fixed and random effects will be explored as the primary dependent variable. Effect sizes were coded from 13 studies, resulting in a total of 4,002 and 621 effect sizes for fixed and random effects. Meta-regression and proportional odds models were used to explore variation in the empirical type ...


Discrete Ranked Set Sampling, Heng Cui 2018 Southern Methodist University

Discrete Ranked Set Sampling, Heng Cui

Statistical Science Theses and Dissertations

Ranked set sampling (RSS) is an efficient data collection framework compared to simple random sampling (SRS). It is widely used in various application areas such as agriculture, environment, sociology, and medicine, especially in situations where measurement is expensive but ranking is less costly. Most past research in RSS focused on situations where the underlying distribution is continuous. However, it is not unusual to have a discrete data generation mechanism. Estimating statistical functionals are challenging as ties may truly exist in discrete RSS. In this thesis, we started with estimating the cumulative distribution function (CDF) in discrete RSS. We proposed two ...


Golden Arm: A Probabilistic Study Of Dice Control In Craps, Donald R. Smith, Robert Scott III 2018 Monmouth University

Golden Arm: A Probabilistic Study Of Dice Control In Craps, Donald R. Smith, Robert Scott Iii

UNLV Gaming Research & Review Journal

This paper calculates how much control a craps shooter must possess on dice outcomes to eliminate the house advantage. A golden arm is someone who has dice control (or a rhythm roller or dice influencer). There are various strategies for dice control in craps. We discuss several possibilities of dice control that would result in several different mathematical models of control. We do not assert whether dice control is possible or not (there is a lack of published evidence). However, after studying casino-legal methods described by dice-control advocates, we can see only one realistic mathematical model that describes the resulting ...


Simple Approximations To The Renewal Function, Antonio G. Campbell 2018 University of Nebraska at Omaha

Simple Approximations To The Renewal Function, Antonio G. Campbell

Theses/Capstones/Creative Projects

In reliability theory, a renewal process is a stochastic model for arrival times or events occurring in a certain system. For a renewal process, it is of interest to be able to estimate the number of events that will occur in the time interval (0, t]. The renewal function, M(t), is the expected value of renewals to occur within the system from (0,t]. It is a solution of the renewal equation. Since closed-form solutions of the renewal equation are mostly non-existent, approximation methods are used. Simpler approximation methods than those currently available are presented and are applied to ...


Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, ian d. campbell 2018 Lynchburg College

Analysis Of 2016-17 Major League Soccer Season Data Using Poisson Regression With R, Ian D. Campbell

Undergraduate Theses and Capstone Projects

To the outside observer, soccer is chaotic with no given pattern or scheme to follow, a random conglomeration of passes and shots that go on for 90 minutes. Yet, what if there was a pattern to the chaos, or a way to describe the events that occur in the game quantifiably. Sports statistics is a critical part of baseball and a variety of other of today’s sports, but we see very little statistics and data analysis done on soccer. Of this research, there has been looks into the effect of possession time on the outcome of a game, the ...


Evaluation Of Using The Bootstrap Procedure To Estimate The Population Variance, Nghia Trong Nguyen 2018 Stephen F Austin State University

Evaluation Of Using The Bootstrap Procedure To Estimate The Population Variance, Nghia Trong Nguyen

Electronic Theses and Dissertations

The bootstrap procedure is widely used in nonparametric statistics to generate an empirical sampling distribution from a given sample data set for a statistic of interest. Generally, the results are good for location parameters such as population mean, median, and even for estimating a population correlation. However, the results for a population variance, which is a spread parameter, are not as good due to the resampling nature of the bootstrap method. Bootstrap samples are constructed using sampling with replacement; consequently, groups of observations with zero variance manifest in these samples. As a result, a bootstrap variance estimator will carry a ...


Physical Applications Of The Geometric Minimum Action Method, George L. Poppe Jr. 2018 The Graduate Center, City University of New York

Physical Applications Of The Geometric Minimum Action Method, George L. Poppe Jr.

All Dissertations, Theses, and Capstone Projects

This thesis extends the landscape of rare events problems solved on stochastic systems by means of the \textit{geometric minimum action method} (gMAM). These include partial differential equations (PDEs) such as the real Ginzburg-Landau equation (RGLE), the linear Schroedinger equation, along with various forms of the nonlinear Schroedinger equation (NLSE) including an application towards an ultra-short pulse mode-locked laser system (MLL).

Additionally we develop analytical tools that can be used alongside numerics to validate those solutions. This includes the use of instanton methods in deriving state transitions for the linear Schroedinger equation and the cubic diffusive NLSE.

These analytical solutions ...


Standard And Anomalous Wave Transport Inside Random Media, Xujun Ma 2018 The Graduate Center, City University of New York

Standard And Anomalous Wave Transport Inside Random Media, Xujun Ma

All Dissertations, Theses, and Capstone Projects

This thesis is a study of wave transport inside random media using random matrix theory. Anderson localization plays a central role in wave transport in random media. As a consequence of destructive interference in multiple scattering, the wave function decays exponentially inside random systems. Anderson localization is a wave effect that applies to both classical waves and quantum waves. Random matrix theory has been successfully applied to study the statistical properties of transport and localization of waves. Particularly, the solution of the Dorokhov-Mello-Pereyra-Kumar (DMPK) equation gives the distribution of transmission.

For wave transport in standard one dimensional random systems in ...


Allocating Interventions Based On Counterfactual Predictions: A Case Study On Homelessness Services, Amanda R. Kube 2018 Washington University in St. Louis

Allocating Interventions Based On Counterfactual Predictions: A Case Study On Homelessness Services, Amanda R. Kube

Engineering and Applied Science Theses & Dissertations

Modern statistical and machine learning methods are increasingly capable of modeling individual or personalized treatment effects by predicting counterfactual outcomes. These counterfactual predictions could be used to allocate different interventions across populations based on individual characteristics. In many domains, like social services, the availability of possible interventions can be severely resource limited. This thesis considers possible improvements to the allocation of such services in the context of homelessness service provision in a major metropolitan area. Using data from the homeless system, I show potential for substantial predicted benefits in terms of reducing the number of families who experience repeat episodes ...


The Ethics In Synthetics: Statistics In The Service Of Ethics And Law In Health-Related Research In Big Data From Multiple Sources, Sharon Bassan Ph.D., Ofer Harel Ph.D. 2018 Princeton University

The Ethics In Synthetics: Statistics In The Service Of Ethics And Law In Health-Related Research In Big Data From Multiple Sources, Sharon Bassan Ph.D., Ofer Harel Ph.D.

Journal of Law and Health

An ethical advancement of scientific knowledge demands a delicate equilibrium between benefits and harms, in particular in health-related research. When applying and advancing scientific knowledge or technologies, Article 4 of UNESCO’s Universal Declaration on Bioethics and Human Rights, ethically justifiable research requires maximizing direct and indirect benefits and minimizing possible harms. The National Institution of Health [NIH] Data Sharing Policy and Implementation Guidance similarly states that data necessary for drawing valid conclusions and advancing medical research should be made as widely and freely available as possible (in order to share the benefits) while safeguarding the privacy of participants from ...


Ultra-High Dimensional Statistical Learning, Yanxin Xu 2018 College of William and Mary

Ultra-High Dimensional Statistical Learning, Yanxin Xu

Undergraduate Honors Theses

Advancements in information technology have enabled scientists to collect data of unprecedented size as well as complexity. Nowadays, high-dimensional data commonly arise in diverse fields as biology, engineering, health sciences, and economics. In this project, we consider both linear and non-parametric models with variable selection in the high-dimensional setting by assuming that only a small number of index coefficients influence the conditional mean of the response variable. Both the numerical results and the real data application demonstrate that the proposed approach selects the correct model with a high frequency and estimates the model coefficients accurately even for moderate sample size ...


Analysis Of Patient Recruitment Methods For Clinical Trials Of Different Heart And Lung Diseases, Oghenevovwero Vovwe Sido 2018 University of North Texas Health Science Center at Fort Worth

Analysis Of Patient Recruitment Methods For Clinical Trials Of Different Heart And Lung Diseases, Oghenevovwero Vovwe Sido

Theses and Dissertations

Patient recruitment is key to the success of any clinical trial, as clinical trials cannot be conducted without the willful participation of subjects. However, clinical trial recruitment has always been a great challenge in clinical studies. This practicum project conducted over an eight-month period, compares three different methods of subject recruitment into 2 clinical research studies conducted at the Heart & Lung Transplant and Pulmonary Research Department of Baylor Scott & White Research Institute, Dallas. The three recruitment methods are: Physician Referral, EHR Screening and Online Portals. We hypothesize that Physician referral is a more successful method for enrolling patients into clinical ...


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