University of Nebraska at Lincoln
Florida International University
Minnesota State University, Mankato
Western Kentucky University
University of Connecticut
Bryant University
Worcester Polytechnic Institute
The University of Western Ontario
Deep Learning Analysis Of Limit Order Book,
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 ...
Golden Arm: A Probabilistic Study Of Dice Control In Craps,
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 ...
Evaluation Of Using The Bootstrap Procedure To Estimate The Population Variance,
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 ...
On Passing The Buck,
2018
Cedarville University
On Passing The Buck, Adam J. Hammett, Anna Joy Yang
Adam J. Hammett, Ph.D.
Imagine there are n>1 people seated around a table, and person S starts with a fair coin they will flip to decide whom to hand the coin next -- if "heads" they pass right, and if "tails" they pass left. This process continues until all people at the table have "touched" the coin. Curiously, it turns out that all people seated at the table other than S have the same probability 1/(n-1) of being last to touch the coin. In fact, Lovasz and Winkler ("A note on the last new vertex visited by a random walk," J. Graph Theory ...
On Passing The Buck,
2018
Cedarville University
On Passing The Buck, Adam J. Hammett, Anna Joy Yang
The Research and Scholarship Symposium
Imagine there are n>1 people seated around a table, and person S starts with a fair coin they will flip to decide whom to hand the coin next -- if "heads" they pass right, and if "tails" they pass left. This process continues until all people at the table have "touched" the coin. Curiously, it turns out that all people seated at the table other than S have the same probability 1/(n-1) of being last to touch the coin. In fact, Lovasz and Winkler ("A note on the last new vertex visited by a random walk," J. Graph Theory ...
The Devil You Don’T Know: A Spatial Analysis Of Crime At Newark’S Prudential Center On Hockey Game Days,
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 ...
Score Test And Likelihood Ratio Test For Zero-Inflated Binomial Distribution And Geometric Distribution,
2018
Western Kentucky University
Score Test And Likelihood Ratio Test For Zero-Inflated Binomial Distribution And Geometric Distribution, Xiaogang Dai
Masters Theses & Specialist Projects
The main purpose of this thesis is to compare the performance of the score test and the likelihood ratio test by computing type I errors and type II errors when the tests are applied to the geometric distribution and inflated binomial distribution. We first derive test statistics of the score test and the likelihood ratio test for both distributions. We then use the software package R to perform a simulation to study the behavior of the two tests. We derive the R codes to calculate the two types of error for each distribution. We create lots of samples to approximate ...
Network Structure Sampling In Bayesian Networks Via Perfect Sampling From Linear Extensions,
2018
University of Colorado, Boulder
Network Structure Sampling In Bayesian Networks Via Perfect Sampling From Linear Extensions, Evan Sidrow
Applied Mathematics Graduate Theses & Dissertations
Bayesian networks are widely considered as powerful tools for modeling risk assessment, uncertainty, and decision making. They have been extensively employed to develop decision support systems in a variety of domains including medical diagnosis, risk assessment and management, human cognition, industrial process and procurement, pavement and bridge management, and system reliability. Bayesian networks are convenient graphical expressions for high dimensional probability distributions which are used to represent complex relationships between a large number of random variables. A Bayesian network is a directed acyclic graph consisting of nodes which represent random variables and arrows which correspond to probabilistic dependencies between them ...
General Stochastic Integral And Itô Formula With Application To Stochastic Differential Equations And Mathematical Finance,
2018
Louisiana State University and Agricultural and Mechanical College
General Stochastic Integral And Itô Formula With Application To Stochastic Differential Equations And Mathematical Finance, Jiayu Zhai
LSU Doctoral Dissertations
A general stochastic integration theory for adapted and instantly independent stochastic processes arises when we consider anticipative stochastic differential equations. In Part I of this thesis, we conduct a deeper research on the general stochastic integral introduced by W. Ayed and H.-H. Kuo in 2008. We provide a rigorous mathematical framework for the integral in Chapter 2, and prove that the integral is well-defined. Then a general Itô formula is given. In Chapter 3, we present an intrinsic property, near-martingale property, of the general stochastic integral, and Doob-Meyer's decomposition for near-submartigales. We apply the new stochastic integration theory ...
Predicting The Next Us President By Simulating The Electoral College,
2018
New York City College of Technology, CUNY
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
Journal of Humanistic Mathematics
We develop a simulation model for predicting the outcome of the US Presidential election based on simulating the distribution of the Electoral College. The simulation model has two parts: (a) estimating the probabilities for a given candidate to win each state and DC, based on state polls, and (b) estimating the probability that a given candidate will win at least 270 electoral votes, and thus win the White House. All simulations are coded using the high-level, open-source programming language R. One of the goals of this paper is to promote computational thinking in any STEM field by illustrating how probabilistic ...
Some Applications Of Sophisticated Mathematics To Randomized Computing,
2018
Selected Works
Some Applications Of Sophisticated Mathematics To Randomized Computing, Ronald I. Greenberg
Ronald Greenberg
No abstract provided.
Educational Magic Tricks Based On Error-Detection Schemes,
2018
Loyola University Chicago
Educational Magic Tricks Based On Error-Detection Schemes, Ronald I. Greenberg
Ronald Greenberg
Magic tricks based on computer science concepts help grab student attention and can motivate them to delve more deeply. Error detection ideas long used by computer scientists provide a rich basis for working magic; probably the most well known trick of this type is one included in the CS Unplugged activities. This paper shows that much more powerful variations of the trick can be performed, some in an unplugged environment and some with computer assistance. Some of the tricks also show off additional concepts in computer science and discrete mathematics.
Comparing Various Machine Learning Statistical Methods Using Variable Differentials To Predict College Basketball,
2018
The University of Akron
Comparing Various Machine Learning Statistical Methods Using Variable Differentials To Predict College Basketball, Nicholas Bennett
Honors Research Projects
The purpose of this Senior Honors Project is to research, study, and demonstrate newfound knowledge of various machine learning statistical techniques that are not covered in the University of Akron’s statistics major curriculum. This report will be an overview of three machine-learning methods that were used to predict NCAA Basketball results, specifically, the March Madness tournament. The variables used for these methods, models, and tests will include numerous variables kept throughout the season for each team, along with a couple variables that are used by the selection committee when tournament teams are being picked. The end goal is to ...
A Review Of The Utility Of Bayesian Network Models,
2018
The University of Akron
A Review Of The Utility Of Bayesian Network Models, Luke Magyar
Honors Research Projects
Bayesian Networks are probabilistic models built from conditional probability tables that relate two observable instances to one another in parent-child fashion. The networks’ strength lies in their ability to use inferential logic to make likelihood assessments about a parent node based on an observation of its child. Additionally, they make it very easy to combine quantitative data with qualitative knowledge from industry experts. These abilities make them very attractive for use as formulation tools in the paint and rubber industries. Paint and rubber formulation has long proven to be a challenging task because companies have a difficult time compiling the ...
Particle Filters For State Estimation Of Confined Aquifers,
2018
University of North Florida
Particle Filters For State Estimation Of Confined Aquifers, Graeme Field
UNF Graduate Theses and Dissertations
Mathematical models are used in engineering and the sciences to estimate properties of systems of interest, increasing our understanding of the surrounding world and driving technological innovation. Unfortunately, as the systems of interest grow in complexity, so to do the models necessary to accurately describe them. Analytic solutions for problems with such models are provably intractable, motivating the use of approximate yet still accurate estimation techniques. Particle filtering methods have emerged as a popular tool in the presence of such models, spreading from its origins in signal processing to a diverse set of fields throughout engineering and the sciences including ...
Can An Influence Graph Driven By Outage Data Determine Transmission Line Upgrades That Mitigate Cascading Blackouts?,
2018
Iowa State University
Can An Influence Graph Driven By Outage Data Determine Transmission Line Upgrades That Mitigate Cascading Blackouts?, Kai Zhou, Ian Dobson, Paul D.H. Hines, Zhaoyu Wang
Electrical and Computer Engineering Conference Papers, Posters and Presentations
We transform historically observed line outages in a power transmission network into an influence graph that statistically describes how cascades propagate in the power grid. The influence graph can predict the critical lines that are historically most involved in cascading propagation. After upgrading these critical lines, simulating the influence graph suggests that these upgrades could mitigate large blackouts by reducing the probability of large cascades.
Mechanism Design, Matching Theory And The Stable Roommates Problem,
2018
Colby College
Mechanism Design, Matching Theory And The Stable Roommates Problem, Yashaswi Mohanty
Honors Theses
This thesis consists of two independent albeit related chapters. The first chapter introduces concepts from mechanism design and matching theory, and discusses potential applications of this theory, particularly in relation to dorm allocations in colleges. The second chapter investigates a subset of the dorm allocation problem, namely that of matching roommates. In particular, the paper looks at the probability of solvability of random instances of the stable roommates game under the condition that preferences are not completely random and exogenous but endogenously determined through a dependence on room choice. These probabilities are estimated using Monte-Carlo simulations and then compared with ...
Effects Of Grain Boundary Disorder On Yield Strength,
2018
Iowa State University and Ames Laboratory
Effects Of Grain Boundary Disorder On Yield Strength, Valery Borovikov, Mikhail I. Mendelev, Alexander H. King
Materials Science and Engineering Publications
It was recently reported that segregation of Zr to grain boundaries (GB) in nanocrystalline Cu can lead to the formation of disordered intergranular films [1,2]. In this study we employ atomistic computer simulations to study how the formation of these films affects the dislocation nucleation from the GBs. We found that full disorder of the grain boundary structure leads to the suppression of dislocation emission and significant increase of the yield stress. Depending on the solute concentration and heat-treatment, however, a partial disorder may also occur and this aids dislocation nucleation rather than suppressing it, resulting in elimination of ...
Making Models With Bayes,
2017
California State University, San Bernardino
Making Models With Bayes, Pilar Olid
Electronic Theses, Projects, and Dissertations
Bayesian statistics is an important approach to modern statistical analyses. It allows us to use our prior knowledge of the unknown parameters to construct a model for our data set. The foundation of Bayesian analysis is Bayes' Rule, which in its proportional form indicates that the posterior is proportional to the prior times the likelihood. We will demonstrate how we can apply Bayesian statistical techniques to fit a linear regression model and a hierarchical linear regression model to a data set. We will show how to apply different distributions to Bayesian analyses and how the use of a prior affects ...
Statistical Modelling, Optimal Strategies And Decisions In Two-Period Economies,
2017
The University of Western Ontario
Statistical Modelling, Optimal Strategies And Decisions In Two-Period Economies, Jiang Wu
Electronic Thesis and Dissertation Repository
Motivated by some real problems, our thesis puts forward two general two-period pricing models and explore optimal buying and selling strategies in two states of the two-period decision, when buyer/seller's decisions in the two periods are uncertain: commodity valuations may or may not be independent, may or may not follow the same distribution, be heavily or just lightly influenced by exogenous economic conditions, and so on. For both the example of buying laptops and the example of selling houses, the connections between each example and the two-envelope paradox encourage us to explore optimal strategies based on the works ...
