Statistical Models Commons^™

Quantifying The Simultaneous Effect Of Socio-Economic Predictors And Build Environment On Spatial Crime Trends, Alfieri Daniel Ek

Graduate Theses and Dissertations

Proper allocation of law enforcement agencies falls under the umbrella of risk terrainmodeling (Caplan et al., 2011, 2015; Drawve, 2016) that primarily focuses on crime prediction and prevention by spatially aggregating response and predictor variables of interest. Although mental health incidents demand resource allocation from law enforcement agencies and the city, relatively less emphasis has been placed on building spatial models for mental health incidents events. Analyzing spatial mental health events in Little Rock, AR over 2015 to 2018, we found evidence of spatial heterogeneity via Moran’s I statistic. A spatial modeling framework is then built using generalized linear models, …

Development Of A Statistical Model To Predict Materials’ Unit Prices For Future Maintenance And Rehabilitation In Highway Life Cycle Cost Analysis, Changmo Kim, Ghazan Khan, Brent Nguyen, Emily L. Hoang

Mineta Transportation Institute

The main objectives of this study are to investigate the trends in primary pavement materials’ unit price over time and to develop statistical models and guidelines for using predictive unit prices of pavement materials instead of uniform unit prices in life cycle cost analysis (LCCA) for future maintenance and rehabilitation (M&R) projects. Various socio-economic data were collected for the past 20 years (1997–2018) in California, including oil price, population, government expenditure in transportation, vehicle registration, and other key variables, in order to identify factors affecting pavement materials’ unit price. Additionally, the unit price records of the popular pavement materials were …

Incorporating Shear Resistance Into Debris Flow Triggering Model Statistics, Noah J. Lyman

Master's Theses

Several regions of the Western United States utilize statistical binary classification models to predict and manage debris flow initiation probability after wildfires. As the occurrence of wildfires and large intensity rainfall events increase, so has the frequency in which development occurs in the steep and mountainous terrain where these events arise. This resulting intersection brings with it an increasing need to derive improved results from existing models, or develop new models, to reduce the economic and human impacts that debris flows may bring. Any development or change to these models could also theoretically increase the ease of collection, processing, and …

Stochastic Analysis And Statistical Inference For Seir Models Of Infectious Diseases, Andrés Ríos-Gutiérrez, Viswanathan Arunachalam, Anuj Mubayi

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Stochastic Modeling Of Ovarian Follicle Growth In Adult Female Rats, Zhaozhi Li

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Interval Estimation Of Proportion Of Second-Level Variance In Multi-Level Modeling, Steven Svoboda

The Nebraska Educator: A Student-Led Journal

Physical, behavioral and psychological research questions often relate to hierarchical data systems. Examples of hierarchical data systems include repeated measures of students nested within classrooms, nested within schools and employees nested within supervisors, nested within organizations. Applied researchers studying hierarchical data structures should have an estimate of the intraclass correlation coefficient (ICC) for every nested level in their analyses because ignoring even relatively small amounts of interdependence is known to inflate Type I error rate in single-level models. Traditionally, researchers rely upon the ICC as a point estimate of the amount of interdependency in their data. Recent methods utilizing an …

Cost Estimating Using A New Learning Curve Theory For Non-Constant Production Rates, Dakotah Hogan, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru, Shawn M. Valentine

Faculty Publications

Traditional learning curve theory assumes a constant learning rate regardless of the number of units produced. However, a collection of theoretical and empirical evidence indicates that learning rates decrease as more units are produced in some cases. These diminishing learning rates cause traditional learning curves to underestimate required resources, potentially resulting in cost overruns. A diminishing learning rate model, namely Boone’s learning curve, was recently developed to model this phenomenon. This research confirms that Boone’s learning curve systematically reduced error in modeling observed learning curves using production data from 169 Department of Defense end-items. However, high amounts of variability in …

A Differential Geometry-Based Machine Learning Algorithm For The Brain Age Problem, Justin Asher, Khoa Tan Dang, Maxwell Masters

The Journal of Purdue Undergraduate Research

No abstract provided.

Predicting Postoperative Delirium Risk For Intracranial Surgery: A Statistical Machine Learning Approach, Juliet Aygun, Alaina Bartfeld, Sahana Rayan

The Journal of Purdue Undergraduate Research

No abstract provided.

Machine Learning Approaches For Improving Prediction Performance Of Structure-Activity Relationship Models, Gabriel Idakwo

Dissertations

In silico bioactivity prediction studies are designed to complement in vivo and in vitro efforts to assess the activity and properties of small molecules. In silico methods such as Quantitative Structure-Activity/Property Relationship (QSAR) are used to correlate the structure of a molecule to its biological property in drug design and toxicological studies. In this body of work, I started with two in-depth reviews into the application of machine learning based approaches and feature reduction methods to QSAR, and then investigated solutions to three common challenges faced in machine learning based QSAR studies.

First, to improve the prediction accuracy of learning …

A Geochemical And Statistical Investigation Of The Big Four Springs Region In Southern Missouri, Jordan Jasso Vega

Graduate Theses/Dissertations

The Big Four Springs region hosts four major first-order magnitude springs in southern Missouri and northern Arkansas. These springs are Big Spring (Carter County, MO), Greer Spring (Oregon County, MO), Mammoth Spring (Fulton County, AR), and Hodgson Mill Spring (Ozark County, MO). Based on historic dye traces and hydrogeological investigations, these springs drain an area of approximately 1500 square miles and collectively discharge an average of 780 million gallons of water per day. The rocks from youngest to oldest that are found in Big Four Springs region are the Cotter and Jefferson City Dolomite (Ordovician), Roubidoux Formation (Ordovician), Gasconade Dolomite …

Data Mining For Structural Damage Identification Using Hybrid Artificial Neural Network Based Algorithm For Beam And Slab Girder, Gordan Meisam

Student Works (2020-2029)

One of the approaches for structural health monitoring (SHM) consists of two major components, i.e. a network of sensors to collect the response data and an extraction method to obtain information on the structural health condition. Data mining (DM) is a novel data extraction technology which can employ for development of inverse analysis. Implementation of DM techniques in different areas of civil engineering has recently given very good results. However, application of DM in SHM is not used as much as expected, thus, many challenges are still ahead. Therefore, it is necessary to develop the applicability of DM in SHM. …

D-Vine Pair-Copula Models For Longitudinal Binary Data, Huihui Lin

Mathematics & Statistics Theses & Dissertations

Dependent longitudinal binary data are prevalent in a wide range of scientific disciplines, including healthcare and medicine. A popular method for analyzing such data is the multivariate probit (MP) model. The motivation for this dissertation stems from the fact that the MP model fails even the binary correlations are within the feasible range. The reason being the underlying correlation matrix of the latent variables in the MP model may not be positive definite. In this dissertation, we study alternatives that are based on D-vine pair-copula models. We consider both the serial dependence modeled by the first order autoregressive (AR(1)) and …

Lectures On Mathematical Computing With Python, Jay Gopalakrishnan

PDXOpen: Open Educational Resources

This open resource is a collection of class activities for use in undergraduate courses aimed at teaching mathematical computing, and computational thinking in general, using the python programming language. It was developed for a second-year course (MTH 271) revamped for a new undergraduate program in data science at Portland State University. The activities are designed to guide students' use of python modules effectively for scientific computation, data analysis, and visualization.

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Statistical Methodology To Establish A Benchmark For Evaluating Antimicrobial Resistance Genes Through Real Time Pcr Assay, Enakshy Dutta

Department of Statistics: Dissertations, Theses, and Student Research

Novel diagnostic tests are usually compared with gold standard tests for evaluating diagnostic accuracy. For assessing antimicrobial resistance (AMR) to bovine respiratory disease (BRD) pathogens, phenotypic broth microdilution method is used as gold standard (GS). The objective of the thesis is to evaluate the optimal cycle threshold (Ct) generated by real-time polymerase chain reaction (rtPCR) to genes that confer resistance that will translate to the phenotypic classification of AMR. Data from two different methodologies are assessed to identify Ct that will discriminate between resistance (R) and susceptibility (S). First, the receiver operating characteristic (ROC) curve was used to determine the …

Italian Sociologists: A Community Of Disconnected Groups, Aliakbar Akbaritabar, Vincent Traag, Alberto Caimo, Flaminio Squazzoni

Articles

Examining coauthorship networks is key to study scientific collaboration patterns and structural characteristics of scientific communities. Here, we studied coauthorship networks of sociologists in Italy, using temporal and multi-level quantitative analysis. By looking at publications indexed in Scopus, we detected research communities among Italian sociologists. We found that Italian sociologists are fractured in many disconnected groups. The giant connected component of the Italian sociology could be split into five main groups with a mixture of three main disciplinary topics: sociology of culture and communication (present in two groups), economic sociology (present in three groups) and general sociology (present in three …

Working Children On Java Island 2017, Yuniarti

International Programs

Children's wellbeing has currently become a global concern as many of them are engaged in the labor force. A small area estimation (SAE) technique, EBLUP under Fey Herriot model, is employed to reveal their number in regencies of Java Island. Statistics have been disaggregated by geographical location (urban/rural) and gender. These statistics are required by the government as the basis for policy making.

Mathematical Modeling: Instructor And Student Resources, Marnie Phipps, Patty Wagner

Mathematics Ancillary Materials

This collection of student and instructor materials for Mathematical Modeling contains lesson plans, lecture slides, homework, learning goals, and student notes for the following major topics:

• Linear Functions
• Quadratic Functions
• Exponential Functions
• Logarithmic Functions

This is a materials update for a collection of materials created for a Round Nine ALG Textbook Transformation Grant.

Structural Analysis Of The Multifunctional Spoiie Regulatory Protein Of Clostridioides Difficile., Blythe Emily Bunkers

Graduate Theses and Dissertations

Clostridioides (formally Clostridium) difficile is a medically relevant pathogen pertinent to infectious disease research. C. difficile is distinctly known for its ability to produce two toxins, enterotoxin A and cytotoxin B, and the propensity to colonize the mammalian gastrointestinal tract. It is known that metabolism is tightly correlated with sporulation in endospore producers such as C. difficile, but an interesting and novel regulatory relationship found by the Ivey lab has yet to be understood. The relationship explored in this study is observed between the sporulation factor, SpoIIE, which represses expression of an ABC peptide transporter, app. In this study, two …

Constitutive Model Of Lateral Unloading Creep Of Soft Soil Under Excess Pore Water Pressure, Wei Huang, Kejun Wen, Xiaojia Deng, Junjie Li, Zhijian Jiang, Yang Li, Lin Li, Farshad Amini

Civil and Architectural Engineering Faculty Research

Presented in this paper is a study on the lateral unloading creep tests under different excess pore water pressures. The marine sedimentary soft soil in Shenzhen, China, was selected in this study. The results show that the excess pore water pressure plays a significant role in enhancing the unloading creep of soft soil. Higher excess pore water pressure brings more obvious creep deformation of soft soil and lower ultimate failure load. Meanwhile, the viscoelastic and the viscoplastic modulus of soft soil were found to exponentially decline with creep time. A modified merchant model and a combined model of the modified …