Effect Of Predictor Dependence On Variable Selection For Linear And Log-Linear Regression,
2020
University of Arkansas, Fayetteville
Effect Of Predictor Dependence On Variable Selection For Linear And Log-Linear Regression, Apu Chandra Das
Graduate Theses and Dissertations
We propose a Bayesian approach to the Dirichlet-Multinomial (DM) regression model, which uses horseshoe, Laplace, and horseshoe plus priors for shrinkage and selection. The Dirichlet-Multinomial model can be used to find the significant association between a set of available covariates and taxa for a microbiome sample. We incorporate the covariates in a log-linear regression framework. We design a simulation study to make a comparison among the performance of the three shrinkage priors in terms of estimation accuracy and the ability to detect true signals. Our results have clearly separated the performance of the three priors and indicated that the horseshoe …
Performance Analysis Of An M/M/1 Queue With N-Policy Interrupted Closedown Preventive Maintenance Balking And Feedback,
2020
Anna University
Performance Analysis Of An M/M/1 Queue With N-Policy Interrupted Closedown Preventive Maintenance Balking And Feedback, A. Azhagappan, T. Deepa
Applications and Applied Mathematics: An International Journal (AAM)
This paper investigates the transient and stationary behavior of a M/M/1 queueing model with N-policy, interrupted closedown, balking, feedback and preventive maintenance. The server stays dormant (off state) until N customers accumulate in the queue and then starts an exhaustive service (on state). After the service, each customer may either leave the system or get immediate feedback. When the system becomes empty, the server resumes closedown. If any arrival occurs before the completion of closedown time, the closedown work of the server is interrupted and starts the busy period in an exhaustive manner. If no arrival occurs during the …
On Arnold–Villasenor Conjectures For Characterizaing Exponential Distribution Based On Sample Of Size Three,
2020
The University of Texas Rio Grande Valley
On Arnold–Villasenor Conjectures For Characterizaing Exponential Distribution Based On Sample Of Size Three, George Yanev
School of Mathematical & Statistical Sciences Faculty Publications
Arnold and Villasenor [4] obtain a series of characterizations of the exponential distribution based on random samples of size two. These results were already applied in constructing goodness-of-fit tests. Extending the techniques from [4], we prove some of Arnold and Villasenor’s conjectures for samples of size three. An example with simulated data is discussed.
Life And Death: Quantifying The Risk Of Heart Disease With Machine Learning,
2020
University of Northern Iowa
Life And Death: Quantifying The Risk Of Heart Disease With Machine Learning, Jack Scott Glienke
Honors Program Theses
Coronary heart disease has long been a key area of focus in the discussion of public health. As such, numerous studies have been conducted throughout history with the sole intention of identifying risk factors leading to the onset of cardiovascular conditions. A plethora of statistical procedures can be used to identify an individual’s risk of developing heart disease, yet regression models tend to be the default tool used by researchers. Using the data obtained from the most influential cardiovascular study to date, the Framingham Heart Study, this analysis uses machine learning techniques to generate and test the predictive power of …
Personal Foul: How Head Trauma And The Insurance Industry Are Threatening Sports,
2020
Liberty University
Personal Foul: How Head Trauma And The Insurance Industry Are Threatening Sports, Zachary Cooler
Senior Honors Theses
This thesis will investigate the growing problem of head trauma in contact sports like football, hockey, and soccer through medical studies, implications to the insurance industry, and ongoing litigation. The thesis will investigate medical studies that are finding more evidence to support the claim that contact sports players are more likely to receive head trauma symptoms such as memory loss, mood swings, and even Lou Gehrig’s disease in extreme cases. The thesis will also demonstrate that these medical symptoms and monetary losses from medical claims are convincing insurance companies to withdraw insurance coverage for sports leagues, which they are justifying …
Dynamic Control Of Probabilistic Simple Temporal Networks,
2020
Harvey Mudd College
Dynamic Control Of Probabilistic Simple Temporal Networks, James C. Boerkoel Jr., Michael Gao, Lindsay Popowski
All HMC Faculty Publications and Research
The controllability of a temporal network is defined as an agent’s ability to navigate around the uncertainty in its schedule and is well-studied for certain networks of temporal constraints. However, many interesting real-world problems can be better represented as Probabilistic Simple Temporal Networks (PSTNs) in which the uncertain durations are represented using potentially-unbounded probability density functions. This can make it inherently impossible to control for all eventualities. In this paper, we propose two new dynamic controllability algorithms that attempt to maximize the likelihood of successfully executing a schedule within a PSTN. The first approach, which we call MIN-LOSS DC, finds …
D-Vine Copula Model For Dependent Binary Data,
2020
Old Dominion University
D-Vine Copula Model For Dependent Binary Data, Huihui Lin, N. Rao Chaganty
College of Sciences Posters
High-dimensional dependent binary data are prevalent in a wide range of scientific disciplines. A popular method for analyzing such data is the Multivariate Probit (MP) model. But the MP model sometimes fails even within a feasible range of binary correlations, because the underlying correlation matrix of the latent variables may not be positive definite. In this research, we proposed pair copula models, assuming the dependence between the binary variables is first order autoregressive (AR(1))or equicorrelated structure. Also, when Archimediean copula is used, most paper converted Kendall Tau to corresponding copula parameter, there is no explicit function of Pearson’s correlation coefficient …
Dice Questions Answered,
2020
Civil Engineering
Dice Questions Answered, Warren Campbell, William P. Dolan
SEAS Faculty Publications
Superstitious discussion of fair and unfair dice has pervaded the tabletop gaming industry since its inception. Many of these are not based on any quantitative data or studies. Consequently, misconceptions have been spread widely. One dice float test video on Youtube currently has 925,000 views (Fisher, 2015a). To combat the flood of misconceptions we investigated the following questions: 1) Are dice cursed? 2) Are D20s (20-sided dice) less fair than D6s (6-sided dice)? 3) Do float tests tell anything about the fairness of dice? 4) Are some dice systems inherently fairer than others? 5) Are density differences or dimensions more …
Some New Results On Stochastic Comparisons Of Coherent Systems Using Signatures,
2020
Bu-Ali Sina University
Some New Results On Stochastic Comparisons Of Coherent Systems Using Signatures, Ebrahim Amini-Seresht, Baha-Eldin Khaledi, Subhash C. Kochar
Mathematics and Statistics Faculty Publications and Presentations
We consider coherent systems with independent and identically distributed components. While it is clear that the system’s life will be stochastically larger when the components are replaced with stochastically better components, we show that, in general, similar results may not hold for hazard rate, reverse hazard rate, and likelihood ratio orderings. We find sufficient conditions on the signature vector for these results to hold. These results are combined with other well-known results in the literature to get more general results for comparing two systems of the same size with different signature vectors and possibly with different independent and identically distributed …
Next-Generation Air Force Weather Metrics Via Bayes Cost Analysis,
2020
Air Force Institute of Technology
Next-Generation Air Force Weather Metrics Via Bayes Cost Analysis, Brandon M. Bailey
Theses and Dissertations
This research proposes a new methodology for U.S. Air Force weather forecast metrics. Military weather forecasters are essentially statistical classifiers. They categorize future conditions into an operationally relevant category based on current data, much like an Artificial Neural Net or Logistic Regression model. There is extensive literature on statistically-based metrics for these types of classifiers. Additionally, in the U.S. Air Force, forecast errors (errors in classification) have quantifiable operational costs and benefits associated with incorrect or correct classification decisions. There is a methodology in the literature, Bayes Cost, which provides a structure for creating statistically rigorous metrics for classification decisions …
Inferences For Weibull-Gamma Distribution In Presence Of Partially Accelerated Life Test,
2020
Al-Azhar University - Egypt
Inferences For Weibull-Gamma Distribution In Presence Of Partially Accelerated Life Test, Mahmoud Mansour, M A W Mahmoud Prof., Rashad El-Sagheer
Basic Science Engineering
In this paper, the point at issue is to deliberate point and interval estimations for the parameters of Weibull-Gamma distribution (WGD) using progressively Type-II censored (PROG-II-C) sample under step stress partially accelerated life test (SSPALT) model. The maximum likelihood (ML), Bayes, and four parametric bootstrap methods are used to obtain the point estimations for the distribution parameters and the acceleration factor. Furthermore, the approximate confidence intervals (ACIs), four bootstrap confidence intervals and credible intervals of the estimators have been gotten. The results of Bayes estimators are computed under the squared error loss (SEL) function using Markov Chain Monte Carlo (MCMC) …
Teaching A University Course On The Mathematics Of Gambling,
2020
University of Utah
Teaching A University Course On The Mathematics Of Gambling, Stewart N. Ethier, Fred M. Hoppe
UNLV Gaming Research & Review Journal
Courses on the mathematics of gambling have been offered by a number of colleges and universities, and for a number of reasons. In the past 15 years, at least seven potential textbooks for such a course have been published. In this article we objectively compare these books for their probability content, their gambling content, and their mathematical level, to see which ones might be most suitable, depending on student interests and abilities. This is not a book review (e.g., none of the books is recommended over others) but rather an essay offering advice about which topics to include in a …
Predicting Diabetes Diagnoses,
2020
Misericordia University
Predicting Diabetes Diagnoses, Sarah Netchert
Student Research Poster Presentations 2020
This study explored the traits and health state of African Americans in central Virginia in order to determine what traits put people at a higher probability of being diagnosed with diabetes. We also want to know which traits will generate the highest probability a person will be diagnosed with diabetes. Traits that were included and used in this study were cholesterol, stabilized glucose, high density lipoprotein levels, age(years), gender, height(inches), weight(pounds), systolic blood pressure, diastolic blood pressure, waist size(inches), and hip size(inches). There were 403 individuals included in study since they were only ones screened for diabetes out of 1,046 …
Shrinkage Priors For Isotonic Probability Vectors And Binary Data Modeling,
2020
The University Of Michigan
Shrinkage Priors For Isotonic Probability Vectors And Binary Data Modeling, Philip S. Boonstra, Daniel R. Owen, Jian Kang
The University of Michigan Department of Biostatistics Working Paper Series
This paper outlines a new class of shrinkage priors for Bayesian isotonic regression modeling a binary outcome against a predictor, where the probability of the outcome is assumed to be monotonically non-decreasing with the predictor. The predictor is categorized into a large number of groups, and the set of differences between outcome probabilities in consecutive categories is equipped with a multivariate prior having support over the set of simplexes. The Dirichlet distribution, which can be derived from a normalized cumulative sum of gamma-distributed random variables, is a natural choice of prior, but using mathematical and simulation-based arguments, we show that …
How Machine Learning And Probability Concepts Can Improve Nba Player Evaluation,
2020
Claremont Colleges
How Machine Learning And Probability Concepts Can Improve Nba Player Evaluation, Harrison Miller
CMC Senior Theses
In this paper I will be breaking down a scholarly article, written by Sameer K. Deshpande and Shane T. Jensen, that proposed a new method to evaluate NBA players. The NBA is the highest level professional basketball league in America and stands for the National Basketball Association. They proposed to build a model that would result in how NBA players impact their teams chances of winning a game, using machine learning and probability concepts. I preface that by diving into these concepts and their mathematical backgrounds. These concepts include building a linear model using ordinary least squares method, the bias …
Evaluating An Ordinal Output Using Data Modeling, Algorithmic Modeling, And Numerical Analysis,
2020
Murray State University
Evaluating An Ordinal Output Using Data Modeling, Algorithmic Modeling, And Numerical Analysis, Martin Keagan Wynne Brown
Murray State Theses and Dissertations
Data and algorithmic modeling are two different approaches used in predictive analytics. The models discussed from these two approaches include the proportional odds logit model (POLR), the vector generalized linear model (VGLM), the classification and regression tree model (CART), and the random forests model (RF). Patterns in the data were analyzed using trigonometric polynomial approximations and Fast Fourier Transforms. Predictive modeling is used frequently in statistics and data science to find the relationship between the explanatory (input) variables and a response (output) variable. Both approaches prove advantageous in different cases depending on the data set. In our case, the data …
Elucidating The Properties And Mechanism For Cellulose Dissolution In Tetrabutylphosphonium-Based Ionic Liquids Using High Concentrations Of Water,
2020
West Virginia University
Elucidating The Properties And Mechanism For Cellulose Dissolution In Tetrabutylphosphonium-Based Ionic Liquids Using High Concentrations Of Water, Brad Crawford
Graduate Theses, Dissertations, and Problem Reports (ETD)
The structural, transport, and thermodynamic properties related to cellulose dissolution by tetrabutylphosphonium chloride (TBPCl) and tetrabutylphosphonium hydroxide (TBPH)-water mixtures have been calculated via molecular dynamics simulations. For both ionic liquid (IL)-water solutions, water veins begin to form between the TBPs interlocking arms at 80 mol % water, opening a pathway for the diffusion of the anions, cations, and water. The water veins allow for a diffusion regime shift in the concentration region from 80 to 92.5 mol % water, providing a higher probability of solvent interaction with the dissolving cellulose strand. The hydrogen bonding was compared between small and large …
V-Slam And Sensor Fusion For Ground Robots,
2020
CUNY City College
V-Slam And Sensor Fusion For Ground Robots, Ejup Hoxha
Dissertations and Theses
In underground, underwater and indoor environments, a robot has to rely solely on its on-board sensors to sense and understand its surroundings. This is the main reason why SLAM gained the popularity it has today. In recent years, we have seen excellent improvement on accuracy of localization using cameras and combinations of different sensors, especially camera-IMU (VIO) fusion. Incorporating more sensors leads to improvement of accuracy,but also robustness of SLAM. However, while testing SLAM in our ground robots, we have seen a decrease in performance quality when using the same algorithms on flying vehicles.We have an additional sensor for ground …
Time-Dependent Reliability Framework For Durability Design Of Frp Composites,
2020
West Virginia University
Time-Dependent Reliability Framework For Durability Design Of Frp Composites, Rajneesh Kumar Bharil
Graduate Theses, Dissertations, and Problem Reports (ETD)
The life-cycle performance, durability, and aging characteristics of Fiber Reinforced Polymer (FRP or Structural Composites) have been of keen interest to the engineers engaged in the FRP design, construction, and manufacturing. Unlike conventional construction materials such as steel and concrete, the design guidelines to account for the aging of FRP are somewhat scattered or not available in an approved or consistent format. Loss of strength over time or aging of any structural material should be of concern to engineers as the in-service lifespan of many engineering structures is expected to exceed 100 years. Use of durability strength-reduction factors or factors …
Statistical Inference For Networks Of High-Dimensional Point Processes,
2019
University of Washington - Seattle Campus
Statistical Inference For Networks Of High-Dimensional Point Processes, Xu Wang, Mladen Kolar, Ali Shojaie
UW Biostatistics Working Paper Series
Fueled in part by recent applications in neuroscience, high-dimensional Hawkes process have become a popular tool for modeling the network of interactions among multivariate point process data. While evaluating the uncertainty of the network estimates is critical in scientific applications, existing methodological and theoretical work have only focused on estimation. To bridge this gap, this paper proposes a high-dimensional statistical inference procedure with theoretical guarantees for multivariate Hawkes process. Key to this inference procedure is a new concentration inequality on the first- and second-order statistics for integrated stochastic processes, which summarizes the entire history of the process. We apply this …
