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Mathematical Models, Patty Wagner, Marnie Phipps 2018 University of North Georgia

Mathematical Models, Patty Wagner, Marnie Phipps

Mathematics Grants Collections

This Grants Collection for Mathematical Models was created under a Round Nine ALG Textbook Transformation Grant.

Affordable Learning Georgia Grants Collections are intended to provide faculty with the frameworks to quickly implement or revise the same materials as a Textbook Transformation Grants team, along with the aims and lessons learned from project teams during the implementation process.

Documents are in .pdf format, with a separate .docx (Word) version available for download. Each collection contains the following materials:

  • Linked Syllabus
  • Initial Proposal
  • Final Report


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 ...


Variable Selection Via Lasso With High-Dimensional Proteomic Data, Hongxuan Zhai 2018 Washington University in St. Louis

Variable Selection Via Lasso With High-Dimensional Proteomic Data, Hongxuan Zhai

Arts & Sciences Electronic Theses and Dissertations

Multiclass classification with high-dimensional data is an applied topic both in statistics and machine learning. The classification procedure could be done in various ways. In this thesis, we review the theory of the Lasso procedure which provides a parameter estimator while simultaneously achieving dimension reduction due to a property of the L1 norm. Lasso with elastic net penalty and sparse group lasso are also reviewed. Our data is high-dimensional proteomic data (iTRAQ ratios) of breast cancer patients with four subtypes of breast cancer. We use the multinomial logistic regression to train our classifier and use the false classification rates obtained ...


Deep Learning Analysis Of Limit Order Book, xin xu 2018 Washington University in St. Louis

Deep Learning Analysis Of Limit Order Book, Xin Xu

Arts & Sciences Electronic Theses and Dissertations

In this paper, we build a deep neural network for modeling spatial structure in limit order book and make prediction for future best ask or best bid price based on ideas of (Sirignano 2016). We propose an intuitive data processing method to approximate the data is non-available for us based only on level I data that is more widely available. The model is based on the idea that there is local dependence for best ask or best bid price and sizes of related orders. First we use logistic regression to prove that this approach is reasonable. To show the advantages ...


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.


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 ...


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 ...


Nonparametric Estimation Of Time Series Volatility Model Estimation, Teng Tu 2018 Washington University in St. Louis

Nonparametric Estimation Of Time Series Volatility Model Estimation, Teng Tu

Arts & Sciences Electronic Theses and Dissertations

In this article we consider two estimation methods of a non-parametric volatility model with autoregressive error of order two. The first estimation method based on the two- lag difference. To get a better result, we consider the second approach based on the general quadratic forms. For illustration, we provided several data sets from different simulation models to support the procedures of both two methods, and prove that the second approach can make a better estimation.


Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas 2018 Southern Methodist University

Cognitive Virtual Admissions Counselor, Kumar Raja Guvindan Raju, Cory Adams, Raghuram Srinivas

SMU Data Science Review

Abstract. In this paper, we present a cognitive virtual admissions counselor for the Master of Science in Data Science program at Southern Methodist University. The virtual admissions counselor is a system capable of providing potential students accurate information at the time that they want to know it. After the evaluation of multiple technologies, Amazon’s LEX was selected to serve as the core technology for the virtual counselor chatbot. Student surveys were leveraged to collect and generate training data to deploy the natural language capability. The cognitive virtual admissions counselor platform is currently capable of providing an end-to-end conversational dialog ...


Statistical Applications In Healthcare Systems, Maryam Mojalal 2018 The University of Western Ontario

Statistical Applications In Healthcare Systems, Maryam Mojalal

Electronic Thesis and Dissertation Repository

This thesis consists of three contributing manuscripts related to waiting times with possible applications in health care. The first manuscript is inspired by a practical problem related to decision making in an emergency department (ED). As short-run predictions of ED censuses are particularly important for efficient allocation and management of ED resources we model ED changes and present estimations for short term (hourly) ED censuses at each time point. We present a Markov-chain based algorithm to make census predictions in near future.

Considering the variation in arrival pattern and service requirements, we apply and compare three models which best describe ...


Developing Methods Of Processing And Analyzing Genetic Data To Examine Tiger Salamander Population Structure, Dennis Dongmin Kim 2018 University of Minnesota, Morris

Developing Methods Of Processing And Analyzing Genetic Data To Examine Tiger Salamander Population Structure, Dennis Dongmin Kim

Undergraduate Research Symposium 2018

Professor Heather Waye and her colleagues conducted a pilot study in 2014 to measure genetic diversity and dispersal pattern in a population of tiger salamanders in west-central Minnesota. The ultimate goal of this research was to analyze the genetic differences between tiger salamander larvae captured in breeding ponds within Pepperton Waterfowl Production Area to understand the population structure and movement patterns. They expected that ponds closer to each other would have more similar genetic information, and that genetic differences between ponds would increase with geographic distance. However, the initial analysis using standard techniques failed to uncover useful patterns in the ...


A Systems Modeling Approach To Forecast Corn Economic Optimum Nitrogen Rate, Laila A. Puntel, John E. Sawyer, Daniel W. Barker, Peter J. Thorburn, Michael J. Castellano, Kenneth J. Moore, Andy VanLoocke, Emily A. Heaton, Sotirios V. Archontoulis 2018 Iowa State University

A Systems Modeling Approach To Forecast Corn Economic Optimum Nitrogen Rate, Laila A. Puntel, John E. Sawyer, Daniel W. Barker, Peter J. Thorburn, Michael J. Castellano, Kenneth J. Moore, Andy Vanloocke, Emily A. Heaton, Sotirios V. Archontoulis

Agronomy Publications

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the ...


The Devil You Don’T Know: A Spatial Analysis Of Crime At Newark’S Prudential Center On Hockey Game Days, Justin Kurland, Eric Piza 2018 Institute for Security and Crime Science - University of Waikato

The Devil You Don’T Know: A Spatial Analysis Of Crime At Newark’S Prudential Center On Hockey Game Days, Justin Kurland, Eric Piza

Journal of Sport Safety and Security

Inspired by empirical research on spatial crime patterns in and around sports venues in the United Kingdom, this paper sought to measure the criminogenic extent of 216 hockey games that took place at the Prudential Center in Newark, NJ between 2007-2016. Do games generate patterns of crime in the areas beyond the arena, and if so, for what type of crime and how far? Police-recorded data for Newark are examined using a variety of exploratory methods and non-parametric permutation tests to visualize differences in crime patterns between game and non-game days across all of Newark and the downtown area. Change ...


Developing Statistical Methods For Data From Platforms Measuring Gene Expression, Gaoxiang Jia 2018 Southern Methodist University

Developing Statistical Methods For Data From Platforms Measuring Gene Expression, Gaoxiang Jia

Statistical Science Theses and Dissertations

This research contains two topics: (1) PBNPA: a permutation-based non-parametric analysis of CRISPR screen data; (2) RCRnorm: an integrated system of random-coefficient hierarchical regression models for normalizing NanoString nCounter data from FFPE samples.

Clustered regularly-interspaced short palindromic repeats (CRISPR) screens are usually implemented in cultured cells to identify genes with critical functions. Although several methods have been developed or adapted to analyze CRISPR screening data, no single spe- cific algorithm has gained popularity. Thus, rigorous procedures are needed to overcome the shortcomings of existing algorithms. We developed a Permutation-Based Non-Parametric Analysis (PBNPA) algorithm, which computes p-values at the gene level ...


Life-History Characteristics And Fishery Dynamics Of Red Drum (Sciaenops Ocellatus), In The North-Central Gulf Of Mexico, Corbin Bennetts 2018 The University of Southern Mississippi

Life-History Characteristics And Fishery Dynamics Of Red Drum (Sciaenops Ocellatus), In The North-Central Gulf Of Mexico, Corbin Bennetts

Master's Theses

Red Drum (Sciaenops ocellatus) are highly targeted recreationally in the Gulf of Mexico, and support a small commercial fishery in Mississippi. Despite their popularity, the stock is assessed using data limited approaches that necessitate accurate life history information. I estimated the year-specific and year-aggregated escapement rates for the Mississippi stock (years 2004 to 2015), which were sensitive to mortality estimation methods; year-aggregated estimates were 6.9 to 28.2 % depending on the method, but temporal patterns were consistent. I then addressed concerns with previously estimated life-history characteristics by describing the sex-specific growth and reproductive dynamics. The three-parameter von Bertalanffy growth ...


Default Priors For The Intercept Parameter In Logistic Regressions, Philip S. Boonstra, Ryan P. Barbaro, Ananda Sen 2018 The University Of Michigan

Default Priors For The Intercept Parameter In Logistic Regressions, Philip S. Boonstra, Ryan P. Barbaro, Ananda Sen

The University of Michigan Department of Biostatistics Working Paper Series

In logistic regression, separation refers to the situation in which a linear combination of predictors perfectly discriminates the binary outcome. Because finite-valued maximum likelihood parameter estimates do not exist under separation, Bayesian regressions with informative shrinkage of the regression coefficients offer a suitable alternative. Little focus has been given on whether and how to shrink the intercept parameter. Based upon classical studies of separation, we argue that efficiency in estimating regression coefficients may vary with the intercept prior. We adapt alternative prior distributions for the intercept that downweight implausibly extreme regions of the parameter space rendering less sensitivity to separation ...


Incorporating Historical Models With Adaptive Bayesian Updates, Philip S. Boonstra, Ryan P. Barbaro 2018 The University Of Michigan

Incorporating Historical Models With Adaptive Bayesian Updates, Philip S. Boonstra, Ryan P. Barbaro

The University of Michigan Department of Biostatistics Working Paper Series

This paper considers Bayesian approaches for incorporating information from a historical model into a current analysis when the historical model includes only a subset of covariates currently of interest. The statistical challenge is two-fold. First, the parameters in the nested historical model are not generally equal to their counterparts in the larger current model, neither in value nor interpretation. Second, because the historical information will not be equally informative for all parameters in the current analysis, additional regularization may be required beyond that provided by the historical information. We propose several novel extensions of the so-called power prior that adaptively ...


Essentials Of Structural Equation Modeling, Mustafa Emre Civelek 2018 Istanbul Commerce University

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling ...


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