Open Access. Powered by Scholars. Published by Universities.®
Physical Sciences and Mathematics Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Keyword
-
- Active learning (1)
- Bias-corrected bagging (1)
- Blockchain (1)
- Blockchain Adoption (1)
- Data analysis (1)
-
- Earthquake insurance take-up rates (1)
- Earthquake risk (1)
- Epidemiology (1)
- Exploratory analysis (1)
- Financial health (1)
- Financial literacy (1)
- Insurance (1)
- Medicine (1)
- Model (1)
- Natural (1)
- Prediction model (1)
- Q-distributions; maximum likelihood estimation; data modeling; method of moments; quadratic forms. (1)
- Supply Chain Disruption (1)
- Technology-Organization-Environment (TOE) (1)
- Texture (1)
- Threat-rigidity Theory (1)
- V2 (1)
- Variable annuity (1)
- Publication
-
- Conference on Applied Statistics in Agriculture and Natural Resources (6)
- Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity (5)
- Undergraduate Student Research Internships Conference (4)
- SDSU Data Science Symposium (3)
- Annual Symposium on Biomathematics and Ecology Education and Research (2)
- File Type
Articles 1 - 25 of 25
Full-Text Articles in Physical Sciences and Mathematics
Learning From Public Spaces In Historic Cities, Cody Josh Kucharski
Learning From Public Spaces In Historic Cities, Cody Josh Kucharski
Symposium of Student Scholars
Successful public spaces in cities are key for enhancing social cohesion and improving health and safety. Learning from historic cities involves the development of representational and analytical tools aimed at capturing their essence as places of human interaction. The research reports findings of the spatial analysis of twenty Adriatic and Ionian coastal cities, which addresses the question of how the network of public spaces calibrates different degrees of spatial enclosure necessary for creating successful social interactions. Cities in the littoral region include well-preserved historic centers that are renowned for the successful integration of urban squares into the urban fabric. For …
Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, Feridun Tasdan
Evaluation Of Circular Logistic Regression Models With Asymmetrical Link Functions, Feridun Tasdan
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, Elizabeth Amona
Incorporating Interventions To An Extended Seird Model With Vaccination: Application To Covid-19 In Qatar, Elizabeth Amona
Annual Symposium on Biomathematics and Ecology Education and Research
No abstract provided.
Bias-Corrected Bagging In Active Learning With An Actuarial Application, Yangxuan Xu
Bias-Corrected Bagging In Active Learning With An Actuarial Application, Yangxuan Xu
Undergraduate Student Research Internships Conference
The variable annuity (VA) is a modern insurance product that offers certain guaranteed protection and tax-deferred treatment. Because of the inherent complexity of guarantees’ payoff, the closed-form solution of fair market values (FMVs) is often not available. Most insurance companies depend on Monte Carlo (MC) simulation to price the FMVs of these products, which is an extremely computational intensive and time-consuming approach. The metamodeling approach can be used to circumvent the heavy computation.
In the modeling stage, the bagged tree method has proved to outperform other parametric approaches. Also, a bias-corrected (BC) bagging model was tried and showed significant improvement …
The Q-Analogue Of The Extended Generalized Gamma Distribution, Wenhao Chen
The Q-Analogue Of The Extended Generalized Gamma Distribution, Wenhao Chen
Undergraduate Student Research Internships Conference
This project introduces a flexible univariate probability model referred to as the q-analogue of the Extended Generalized Gamma (or q-EGG) distribution, which encompasses the majority of the most frequently used continuous distributions, including the gamma, Weibull, logistic, type-1 and type-2 beta, Gaussian, Cauchy, Student-t and F. Closed form representations of its moments and cumulative distribution function are provided. Additionally, computational techniques are proposed for determining estimates of its parameters. Both the method of moments and the maximum likelihood approach are utilized. The effect of each parameter is also graphically illustrated. Certain data sets are modeled with q-EGG distributions; goodness of …
Investigation Of Key Factors To Earthquake Insurance Take-Up Rates In Quebec And British Columbia Households And Prediction Model Building, Yongcheng Jiang
Investigation Of Key Factors To Earthquake Insurance Take-Up Rates In Quebec And British Columbia Households And Prediction Model Building, Yongcheng Jiang
Undergraduate Student Research Internships Conference
Maintaining an adequate level of earthquake take-up rate could protect the insurance industry from systemic failure. Past research has shown that British Columbia and Quebec have significant differences in earthquake insurance take-up rate. This report investigates key factors from the structure (default options and various types) of the insurance plan and personal characteristics along with socioeconomic/demographic profiles that affect the demand for earthquake protection in the form of insurance. The report also provides a prediction model for earthquake insurance take-up rate. The results show an importance ranking of key factors of earthquake insurance take up, the most important three are …
Financial Literacy: Self-Evaluation And Reality, Yangsijia Wang
Financial Literacy: Self-Evaluation And Reality, Yangsijia Wang
Undergraduate Student Research Internships Conference
This study is on the topic of financial literacy, with the data source containing information on clients' demographic information and self-evaluation, change in account value, and trade record, three major problems were investigated: first, whether a client's demographic traits are related to his/her self-evaluation of financial knowledge level; second, does the trading behaviour differ for clients who self-identified as in different financial knowledge groups; and third, do people who self-identified as financially knowledgeable have better investment result. Data manipulation was done using SQL and R. Exploratory analysis including multiple types of plots and proportion tables was used to derive the …
Model Averaging In Agriculture And Natural Resources: What Is It? When Is It Useful? When Is It A Distraction?, Philip M. Dixon
Model Averaging In Agriculture And Natural Resources: What Is It? When Is It Useful? When Is It A Distraction?, Philip M. Dixon
Conference on Applied Statistics in Agriculture and Natural Resources
I use two examples to illustrate three methods for model averaging: using AIC weights, using BIC weights, and fully Bayesian analyses. The first example is a capture-recapture study that estimates the population size by averaging over 4 models for capture probabilities. The second is an analysis of a study of logging impacts on Curculionid weevils using a before-after-control-impact (BACI) study design. The estimated impact is averaged over 4 ecologically relevant models.
Both examples demonstrate the sensitivity of model weights, or posterior model probabilities, to the choice of prior model probabilities and prior distributions for parameters. The model averaged estimates and …
A Robust Clustering Method Using Compositional Data Restrictions: Studying Wood Properties In The Reforestation Of Portugal, Pamela M. Chiroque-Solano, Guido A. Moreira
A Robust Clustering Method Using Compositional Data Restrictions: Studying Wood Properties In The Reforestation Of Portugal, Pamela M. Chiroque-Solano, Guido A. Moreira
Conference on Applied Statistics in Agriculture and Natural Resources
Classification of multivariate observations while preserving the data’s natural restriction is a challenge. Special properties such as identifiability, interpretability, and others need to be cared for to build a new approach. To avoid these complications, many transformation algorithms have been developed to use traditional models.In this context, the aim of this work is to propose a robust probabilistic distance algorithm to classify compositional data. Based on the probabilistic distance (PD) clustering approach, the proposal identifies clusters minimizing a joint distance function, JDF, which is part of a dissimilarity measure. This measure combines the PD clustering approach with the density of …
Random Regression For Modeling Semen Fertility In Hf Purebred And Crossbred Bulls Using A Bayesian Framework, Vrinda Ambike, R. Venkataramanan, S. M. K. Karthickeyan, K. G. Tirumurugaan, Kaustubh Bhave, M. Swaminathan
Random Regression For Modeling Semen Fertility In Hf Purebred And Crossbred Bulls Using A Bayesian Framework, Vrinda Ambike, R. Venkataramanan, S. M. K. Karthickeyan, K. G. Tirumurugaan, Kaustubh Bhave, M. Swaminathan
Conference on Applied Statistics in Agriculture and Natural Resources
Data on insemination records of Holstein Friesian (HF) purebred (n=45,497) and crossbred (n=58,497) collected from the BAIF Research Foundation were utilized. The conception rate was modeled as a binary trait, using linear repeatability models. Random regression models (RRM) were used to obtain the trajectory of variance components across age of the bulls. Legendre Polynomials up to order of fit of 4 were used for the random effects of additive genetic and permanent environmental effects. 200,000 Gibbs samples were generated with a burn-in of 20,000 and thinning interval of 50 using the THRGIBBS1F90 program. Heritability estimates were very low (0.1) in …
Rewriting The Rules For Diagnostics: Implications Of Probability And Measure Theory For Sars-Cov-2 Testing, Paul Patrone, Anthony Kearsley
Rewriting The Rules For Diagnostics: Implications Of Probability And Measure Theory For Sars-Cov-2 Testing, Paul Patrone, Anthony Kearsley
Biology and Medicine Through Mathematics Conference
No abstract provided.
Age-Dependent Ventilator-Induced Lung Injury, Quintessa Hay, Christopher Grubb, Rebecca L. Heise, Sarah Minucci, Michael S. Valentine, Jennifer Van Mullekom, Angela M. Reynolds
Age-Dependent Ventilator-Induced Lung Injury, Quintessa Hay, Christopher Grubb, Rebecca L. Heise, Sarah Minucci, Michael S. Valentine, Jennifer Van Mullekom, Angela M. Reynolds
Biology and Medicine Through Mathematics Conference
No abstract provided.
Principal Response Curve Analysis Of Arthropod Community Abundance Data With Sparse Subsets, Changjian Jiang, C. R. Brown, P. Asiimwe, Chen Meng, Adam W. Schapaugh
Principal Response Curve Analysis Of Arthropod Community Abundance Data With Sparse Subsets, Changjian Jiang, C. R. Brown, P. Asiimwe, Chen Meng, Adam W. Schapaugh
Conference on Applied Statistics in Agriculture and Natural Resources
Principal response curve (PRC) analysis was applied to an assessment of the ecological impact of the genetically-modified (GM), insect-resistant, cotton MON 88702 on predatory Hemiptera communities in the field. The field community was represented by ten taxa collected ten times across the season at six sites, in which individual taxa were not observed in at least 25% of the time (unique site x collection combinations). These complete absences and those nearly so, called sparse subsets of the data in this investigation, were the result of geoclimatic and seasonal variations, which are both independent of the treatment effect for which the …
Handling Non-Detects With Imputation In A Nested Design: A Simulation Study, Rose Adjei, John R. Stevens
Handling Non-Detects With Imputation In A Nested Design: A Simulation Study, Rose Adjei, John R. Stevens
Conference on Applied Statistics in Agriculture and Natural Resources
In this paper, a simulation study was conducted to assess whether it is ideal to address the issue of non-detects in data using a traditional substitution approach for non-detects, imputation, or a non-imputation based approach. Simulated data used were simple nested designs motivated by a real-life data in a study of bumble bee activity in a commercial cherry orchard by Kuivila et al. (2021). The simulated data were generated at different thresholds or censoring levels and at different effect sizes. For each simulated data, seven popular existing techniques to handle non-detects were applied: (i) Zero substitution, (ii) Substitution with half …
Overview Of Optimal Experimental Design And A Survey Of Its Expanse In Application To Agricultural Studies, Stephen J. Walsh
Overview Of Optimal Experimental Design And A Survey Of Its Expanse In Application To Agricultural Studies, Stephen J. Walsh
Conference on Applied Statistics in Agriculture and Natural Resources
Optimal Design of Experiments is currently recognized as the modern dominant approach to planning experiments in industrial engineering and manufacturing applications. This approach to design has gained traction among practitioners in the last two decades on two-fronts: 1) optimal designs are the result of a complicated optimization calculation and recent advances in both computing efficiency and algorithms have enabled this approach in real time for practitioners, and 2) such designs are now popular because they allow the researcher to ‘design for the experiment’ by working constraints, cost, number of experiments, and the model of the intended post-hoc data analysis into …
A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli
A Two-Layer Model Explains Higher-Order Feature Selectivity Of V2 Neurons, Timothy D. Oleskiw, Justin D. Lieber, J. Anthony Movshon, Eero P. Simoncelli
MODVIS Workshop
Neurons in cortical area V2 respond selectively to higher-order visual features, such as the quasi-periodic structure of natural texture. However, a functional account of how V2 neurons build selectivity for complex natural image features from their inputs – V1 neurons locally tuned for orientation and spatial frequency – remains elusive.
We made single-unit recordings in area V2 in two fixating rhesus macaques. We presented stimuli composed of multiple superimposed grating patches that localize contrast energy in space, orientation, and scale. V2 activity is modeled via a two-layer linear-nonlinear network, optimized to use a sparse combination of V1-like outputs to account …
To Adopt Blockchain Technology Or Not: Is The Decision-Making Process Immune To Covid-19?, Rebecca Jauch
To Adopt Blockchain Technology Or Not: Is The Decision-Making Process Immune To Covid-19?, Rebecca Jauch
Thinking Matters Symposium
Blockchain technology has been shown to have advantages in improving the effectiveness of supply chain management. We use the Technology-Organization-Environment (TOE) framework with Threat-Rigidity Theory (TRT) to determine the factors that lead U.S. businesses to adopt blockchain technology, the factors that act as barriers to adoption, and the disruptive effect of COVID-19 on the rate of blockchain adoption
A Statistical Study Of Operating Systems At Harrisburg University, Dylan Morgan, Ethan Collins, Joshua Moody, Akeisha Belgrave
A Statistical Study Of Operating Systems At Harrisburg University, Dylan Morgan, Ethan Collins, Joshua Moody, Akeisha Belgrave
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
We conducted a survey of 100 students to find out which operating system students are using for their main school laptop. (Class Project)
Percentage Of Yellow Sour Patch Kids, Easton Kratzer, Sarah Baxter
Percentage Of Yellow Sour Patch Kids, Easton Kratzer, Sarah Baxter
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
After being given the Qualitative Research Project in Introduction to Statistics, I came up with the question asking what percentage of Sour Patch Kids are yellow. This resulted in me going through an entire bag and counting the amount of every color to figure out the percentages. (Class Project)
A Statistical Study Into The Relationship Between The Student Age And Their Academic Performance, Umangkumar Patel, Akeisha Belgrave
A Statistical Study Into The Relationship Between The Student Age And Their Academic Performance, Umangkumar Patel, Akeisha Belgrave
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
This project will conduct a research in order to find out the relationship between the age of a student and their academic performance. This project will survey at least 100 students. (Class Project)
Favorite Programming Language Among Students, Anwar Jawhar, Akeisha Belgrave
Favorite Programming Language Among Students, Anwar Jawhar, Akeisha Belgrave
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
This project involves understanding the favorite programming language among students. I hypothesize that the favorite programming language will be Python. (Class Project)
Preference For Violence By Gender, Ayrton Hall, Christian Watson, Akeisha Belgrave
Preference For Violence By Gender, Ayrton Hall, Christian Watson, Akeisha Belgrave
Harrisburg University Research Symposium: Highlighting Research, Innovation, & Creativity
In our survey we asked students of HU what their favorite video games were as well as their favorite genre and most played game. We then analyzed the data to see how gender affects preference for violent games. (Class Project)
An Alpha-Based Prescreening Methodology For A Common But Unknown Source Likelihood Ratio With Different Subpopulation Structures, Dylan Borchert, Semhar Michael, Christopher Saunders, Andrew Simpson
An Alpha-Based Prescreening Methodology For A Common But Unknown Source Likelihood Ratio With Different Subpopulation Structures, Dylan Borchert, Semhar Michael, Christopher Saunders, Andrew Simpson
SDSU Data Science Symposium
Prescreening is a commonly used methodology in which the forensic examiner includes sources from the background population that meet a certain degree of similarity to the given piece of evidence. The goal of prescreening is to find the sources closest to the given piece of evidence in an alternative source population for further analysis. This paper discusses the behavior of an $\alpha-$based prescreening methodology in the form of a Hotelling $T^2$ test on the background population for a common but unknown source likelihood ratio. An extensive simulation study with synthetic and real data were conducted. We find that prescreening helps …
Identifying Subpopulations Of A Hierarchical Structured Data Using A Semi-Supervised Mixture Modeling Approach, Andrew Simpson, Semhar Michael, Christopher Saunders, Dylan Borchert
Identifying Subpopulations Of A Hierarchical Structured Data Using A Semi-Supervised Mixture Modeling Approach, Andrew Simpson, Semhar Michael, Christopher Saunders, Dylan Borchert
SDSU Data Science Symposium
The field of forensic statistics offers a unique hierarchical data structure in which a population is composed of several subpopulations of sources and a sample is collected from each source. This subpopulation structure creates a hierarchical layer. We propose using a semi-supervised mixture modeling approach to model the subpopulation structure which leverages the fact that we know the collection of samples came from the same, yet unknown, source. A simulation study based on a famous glass data was conducted and shows this method performs better than other unsupervised approaches which have been previously used in practice.
Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore
Session 5: Equipment Finance Credit Risk Modeling - A Case Study In Creative Model Development & Nimble Data Engineering, Edward Krueger, Landon Thompson, Josh Moore
SDSU Data Science Symposium
This presentation will focus first on providing an overview of Channel and the Risk Analytics team that performed this case study. Given that context, we’ll then dive into our approach for building the modeling development data set, techniques and tools used to develop and implement the model into a production environment, and some of the challenges faced upon launch. Then, the presentation will pivot to the data engineering pipeline. During this portion, we will explore the application process and what happens to the data we collect. This will include how we extract & store the data along with how it …