Supplementary Files For "Adaptive Mapping Of Design Ground Snow Loads In The Conterminous United States",
2023
University of Utah
Supplementary Files For "Adaptive Mapping Of Design Ground Snow Loads In The Conterminous United States", Jadon Wagstaff, Jesse Wheeler, Brennan Bean, Marc Maguire, Yan Sun
Browse all Datasets
Recent amendments to design ground snow load requirements in ASCE 7-22 have reduced the size of case study regions by 91% from what they were in ASCE 7-16, primarily in western states. This reduction is made possible through the development of highly accurate regional generalized additive regression models (RGAMs), stitched together with a novel smoothing scheme implemented in the R software package remap, to produce the continental- scale maps of reliability-targeted design ground snow loads available in ASCE 7-22. This approach allows for better characterizations of the changing relationship between temperature, elevation, and ground snow loads across the Conterminous United …
On Partially Observed Tensor Regression,
2023
University of Windsor
On Partially Observed Tensor Regression, Dinara Miftyakhetdinova
Major Papers
Tensor data is widely used in modern data science. The interest lies in identifying and characterizing the relationship between tensor datasets and external covariates. These datasets, though, are often incomplete. An efficient nonconvex alternating updating algorithm proposed by J. Zhou et al. in the paper "Partially Observed Dynamic Tensor Response Regression" provides a novel approach. The algorithm handles the problem of unobserved entries by solving an optimization problem of a loss function under the low-rankness, sparsity, and fusion constraints. This analysis aims to understand in detail the proposed algorithms and their theoretical proofs with, potentially, dropping some of the assumptions …
Informative Hypothesis For Group Means Comparison,
2023
National University of Singapore
Informative Hypothesis For Group Means Comparison, Dr. Teck Kiang Tan
Practical Assessment, Research, and Evaluation
Researchers often have hypotheses concerning the state of affairs in the population from which they sampled their data to compare group means. The classical frequentist approach provides one way of carrying out hypothesis testing using ANOVA to state the null hypothesis that there is no difference in the means and proceed with multiple comparisons if the null hypothesis is rejected. As this approach is not able to incorporate order, inequality, and direction into hypothesis testing, and neither does it able to specify multiple hypotheses, this paper introduces the informative hypothesis that allows more flexibility in stating hypothesis testing and is …
Uniformity Test Based On The Empirical Bernstein Distribution,
2023
University of Windsor
Uniformity Test Based On The Empirical Bernstein Distribution, Ran Sun
Major Papers
In this paper, we firstly review the origin of Bernstein polynomial and the various application of it. Then we review the importance of goodness-of-fit test, especially the uniformity test, and we examine lots of different test statistics proposed by far. After that we suggest two new statistics for testing the uniformity. These two statistics are based on Komogorov-Smirnov test type and Cramér-Von Mises test type, respectively. Also we embed Bernstein polynomial into those test type and take advantage of great approximation performance of this polynomial. Finally, we run a Monte-Carlo simulation to compare the performance of our statistics to those …
Optimal Speed Of A Machine In An Assembly Line Using The Continuous Time Markov Chain Rate Matrix,
2023
University of Windsor
Optimal Speed Of A Machine In An Assembly Line Using The Continuous Time Markov Chain Rate Matrix, Chandi Darshani Rupasinghe
Major Papers
The optimal speed of a machine in an assembly line is determined using a Markov decision process type model. We develop the rate matrix that represents the inter-event time of a machine, either repair time or time to breakdown, as a function of speed. We consider the rate of time to breakdown with a variety of functions of speed. We find limiting probabilities and express profit in terms of these probabilities. We then find the optimal speed to maximize profit. Further, we assume an underlying function of speed and simulate data using R. From the simulated data, we estimate the …
Statistical Models For Decision-Making In Professional Soccer,
2023
Wilfrid Laurier University
Statistical Models For Decision-Making In Professional Soccer, Sean Hellingman
Theses and Dissertations (Comprehensive)
As soccer is widely regarded as the most popular sport in the world there is high interest in methods of improving team performances. There are many ways teams and individual athletes can influence their own performances during competition. This thesis focuses on developing statistical methodologies for improving competition-based decision-making for soccer so as to allow professional soccer teams to make better informed decisions regarding player selection and in-game decision-making.
To properly capture the dynamic actions of professional soccer, Markov chains with increasing complexity are proposed. These models allow for the inclusion of potential changes in the process caused by goals …
Medical Racism: Comparing Prenatal Care Across Races In The United States,
2022
DePauw University
Medical Racism: Comparing Prenatal Care Across Races In The United States, Rubina Cheema
Student Research
Prenatal care describes any care a woman receives during her pregnancy. It is intended to keep both the mother and the child healthy and also to reduce the risk of complications during and after birth. This care is especially important for women with high-risk factors so that doctors and nurses are able to monitor their health and the health of their baby during the duration of their pregnancy. For prenatal care to be most effective, it is imperative to begin prenatal care within the first trimester of a woman's pregnancy. However, in the United States, medical racism creates a major …
Study On Innovation Networks And Its Spillover Effect Of China’S New Energy Automobile Industry,
2022
Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Study On Innovation Networks And Its Spillover Effect Of China’S New Energy Automobile Industry, Zhifei Xiong, Wenzhong Zhang
Bulletin of Chinese Academy of Sciences (Chinese Version)
The network spillover effect of knowledge has been playing an increasingly significant role in the development of industrial innovation. The urban cooperation matrix of China’s new energy automobile industry is built based on new energy automobile patent data, and the structure and evolution process of China’s new energy automobile industry are depicted. On this basis, the spatial Dubin model (SDM) is used to calculate the network spillover effect, and its results are compared with the results of spillover effect based on the relationship of spatial contiguity and distance of cities. The results show that the innovation activities of China’s new …
Regression Modeling Of Complex Survival Data Based On Pseudo-Observations,
2022
Southern Methodist University
Regression Modeling Of Complex Survival Data Based On Pseudo-Observations, Rong Rong
Statistical Science Theses and Dissertations
The restricted mean survival time (RMST) is a clinically meaningful summary measure in studies with survival outcomes. Statistical methods have been developed for regression analysis of RMST to investigate impacts of covariates on RMST, which is a useful alternative to the Cox regression analysis. However, existing methods for regression modeling of RMST are not applicable to left-truncated right-censored data that arise frequently in prevalent cohort studies, for which the sampling bias due to left truncation and informative censoring induced by the prevalent sampling scheme must be properly addressed. Meanwhile, statistical methods have been developed for regression modeling of the cumulative …
Kernel Estimation Of Spot Volatility And Its Application In Volatility Functional Estimation,
2022
Washington University in St. Louis
Kernel Estimation Of Spot Volatility And Its Application In Volatility Functional Estimation, Bei Wu
Arts & Sciences Electronic Theses and Dissertations
It\^o semimartingale models for the dynamics of asset returns have been widely studied in financial econometrics. A key component of the model, spot volatility, plays a crucial role in option pricing, portfolio management, and financial risk assessment. In this dissertation, we consider three problems related to the estimation of spot volatility using high-frequency asset returns. We first revisit the problem of estimating the spot volatility of an It\^o semimartingale using a kernel estimator. We prove a Central Limit Theorem with an optimal convergence rate for a general two-sided kernel under quite mild assumptions, which includes leverage effects and jumps of …
Contribution To Data Science: Time Series, Uncertainty Quantification And Applications,
2022
Washington University in St. Louis
Contribution To Data Science: Time Series, Uncertainty Quantification And Applications, Dhrubajyoti Ghosh
Arts & Sciences Electronic Theses and Dissertations
Time series analysis is an essential tool in modern world statistical analysis, with a myriad of real data problems having temporal components that need to be studied to gain a better understanding of the temporal dependence structure in the data. For example, in the stock market, it is of significant importance to identify the ups and downs of the stock prices, for which time series analysis is crucial. Most of the existing literature on time series deals with linear time series, or with Gaussianity assumption. However, there are multiple instances where the time series shows nonlinear trends, or when the …
Dealing With Dimensionality: Problems And Techniques In High-Dimensional Statistics,
2022
Washington University in St. Louis
Dealing With Dimensionality: Problems And Techniques In High-Dimensional Statistics, Cezareo Rodriguez
Arts & Sciences Electronic Theses and Dissertations
In modern data analysis, problems involving high dimensional data with more variables than subjects is increasingly common. Two such cases are mediation analysis and distributed optimization. In Chapter 2 we start with an overview of high dimensional statistics and mediation analysis. In Chapter 3 we motivate and prove properties for a new marginal screening procedure for performing high dimensional mediation analysis. This screening procedure is shown via simulation to perform better than benchmark approaches and is applied to a DNA methylation study. In Chapter 4 we construct a cryptosystem that accurately performs distributed penalized quantile regression in the high-dimensional setting …
Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach,
2022
Sacred Heart University
Predictors Of Covid-19 Vaccination Rate In Usa: A Machine Learning Approach, Syed M. I. Osman, Ahmed Sabit
WCBT Faculty Publications
In this study, we examine state-level features and policies that are most important in achieving a threshold level vaccination rate to curve the effects of the COVID-19 pandemic. We employ CHAID, a decision tree algorithm, on three different model specifications to answer this question based on a dataset that includes all the states in the United States. Workplace travel emerges as the most important predictor; however, the governors’ political affiliation (PA) replaces it in a more conservative feature set that includes economic features and the growth rate of COVID-19 cases. We also employ several alternative algorithms as a robustness check. …
Examining The Impact Of Covid-19 On The Education And Development Of American Students,
2022
DePauw University
Examining The Impact Of Covid-19 On The Education And Development Of American Students, Riley Fortin '25
Student Research
After the COVID-19 pandemic, the vast majority of American children have fallen behind on core subjects due to the ultimate ineffectiveness of remote learning. This study attempts to discover the degree to which children have fallen behind through the trends in the National Association of Educational Procurement’s two most recent testing years. A database accessed from Google has been analyzed, filtered by state and visualized in tables in order to indicate any possible trends as a result of remote learning brought on by the pandemic. By looking at data in seven different states across the country, there is a notable …
Sexual And Reproductive Health Disparities For Lgbtq+ Patients,
2022
DePauw University
Sexual And Reproductive Health Disparities For Lgbtq+ Patients, Lauren Del Rosario
Student Research
As of 2022, 7.1% of Americans identify as LGBTQ. Members of the LGBTQ+ community in the United States experience greater health disparities than their heterosexual counterparts due to structural inequity: in addition to having minority status within the United States, there is a lack of education and research about LGBTQ+ health-related issues as well as restrictive policies that limit access to health care and other health benefits. As a result, the LGBTQ+ community is more prone to developing certain conditions, have less access to health care, and have worse health outcomes. However, LGBTQ+ visibility has increased dramatically within the last …
Polarization, Media Bias, And General Opinion,
2022
DePauw University
Polarization, Media Bias, And General Opinion, Knole Ihle '25
Student Research
This article researches the relationship between three different spheres of influence: party identification, issue selection process in media, and the following changes in public opinion. This relationship was examined through a random sample of news organizations based on a specific issue. The number of articles was then documented for each newspaper and measured against the articles produced apropos to that issue in the previous year. The discrepancy in articles produced is then compared to the succeeding policy shift to determine whether or not there is a correlation between these two relationships. Regarding the relationship between Ukraine-Russia War media and proceeding …
Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits,
2022
Nova Southeastern University
Examining The Relationship Between Stomiiform Fish Morphology And Their Ecological Traits, Mikayla L. Twiss
All HCAS Student Capstones, Theses, and Dissertations
Trait-based ecology characterizes individuals’ functional attributes to better understand and predict their interactions with other species and their environments. Utilizing morphological traits to describe functional groups has helped group species with similar ecological niches that are not necessarily taxonomically related. Within the deep-pelagic fishes, the Order Stomiiformes exhibits high morphological and species diversity, and many species undertake diel vertical migration (DVM). While the morphology and behavior of stomiiform fishes have been extensively studied and described through taxonomic assessments, the connection between their form and function regarding their DVM types, morphotypes, and daytime depth distributions is not well known. Here, three …
Evidence-Based Study: The Effect Of The Covid-19 Pandemic On Post-Secondary Enrollment And Chosen Fields Of Study,
2022
DePauw University
Evidence-Based Study: The Effect Of The Covid-19 Pandemic On Post-Secondary Enrollment And Chosen Fields Of Study, Hannah Fields '25
Student Research
The onset of the COVID-19 pandemic in the United States in March of 2020 derailed educational systems at all levels. Specifically, at the post-secondary level, the pandemic sent many students online or forced them to take a fifth year to complete their degrees. As a result, post-secondary enrollment rates are likely to have dropped to reflect these changing post-COVID views surrounding education. Additionally, changing viewpoints about the essentiality of certain jobs and roles changed the chosen fields of study of these same students. Data for this study was collected by way of a short-scale meta-analysis, and enrollment rates were split …
Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things,
2022
Army Cyber Institute, U.S. Military Academy
Context-Aware Collaborative Neuro-Symbolic Inference In Internet Of Battlefield Things, Tarek Abdelzaher, Nathaniel D. Bastian, Susmit Jha, Lance Kaplan, Mani Srivastava, Venugopal Veeravalli
ACI Journal Articles
IoBTs must feature collaborative, context-aware, multi-modal fusion for real-time, robust decision-making in adversarial environments. The integration of machine learning (ML) models into IoBTs has been successful at solving these problems at a small scale (e.g., AiTR), but state-of-the-art ML models grow exponentially with increasing temporal and spatial scale of modeled phenomena, and can thus become brittle, untrustworthy, and vulnerable when interpreting large-scale tactical edge data. To address this challenge, we need to develop principles and methodologies for uncertainty-quantified neuro-symbolic ML, where learning and inference exploit symbolic knowledge and reasoning, in addition to, multi-modal and multi-vantage sensor data. The approach features …
(R1971) Analysis Of Feedback Queueing Model With Differentiated Vacations Under Classical Retrial Policy,
2022
Hindu Girls College, Sonipat (India)
(R1971) Analysis Of Feedback Queueing Model With Differentiated Vacations Under Classical Retrial Policy, Poonam Gupta, Naveen Kumar, Rajni Gupta
Applications and Applied Mathematics: An International Journal (AAM)
This paper analyzes an M/M/1 retrial queue under differentiated vacations and Bernoulli feedback policy. On receiving the service, if the customer is not satisfied, then he may join the retrial group again with some probability and demand for service or may leave the system with the complementary probability. Using the probability generating functions technique, the steady-state solutions of the system are obtained. Furthermore, we have obtained some of the important performance measures such as expected orbit length, expected length of the system, sojourn times and probability of server being in different states. Using MATLAB software, we have represented the graphical …