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Articles 91 - 120 of 131
Full-Text Articles in Applied Statistics
Building A Better Risk Prevention Model, Steven Hornyak
Building A Better Risk Prevention Model, Steven Hornyak
National Youth Advocacy & Resilience Conference
This presentation chronicles the work of Houston County Schools in developing a risk prevention model built on more than ten years of longitudinal student data. In its second year of implementation, Houston At-Risk Profiles (HARP), has proven effective in identifying those students most in need of support and linking them to interventions and supports that lead to improved outcomes and significantly reduces the risk of failure.
Density Estimation Of Spatio-Temporal Point Patterns Using Moran’S Statistics, Jennifer L. Lorio, Norou Diawara, Lance A. Waller
Density Estimation Of Spatio-Temporal Point Patterns Using Moran’S Statistics, Jennifer L. Lorio, Norou Diawara, Lance A. Waller
Mathematics & Statistics Faculty Publications
Moran’s Index is a statistic that measures spatial autocorrelation, quantifying the degree of dispersion (or spread) of objects in space. When investigating data in an area, a single Moran statistic may not give a sufficient summary of the autocorrelation spread. However, by partitioning the area and taking the Moran statistic of each subarea, we discover patterns of the local neighbors not otherwise apparent. In this paper, we consider the model of the spread of an infectious disease, incorporate time factor, and simulate a multilevel Poisson process where the dependence among the levels is captured by the rate of increase of …
Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram
Effect Of Anthropometric Variability On Middle-Market Aircraft Seating, Tara C. Sriram
International Journal of Aviation, Aeronautics, and Aerospace
A middle-of-market aircraft, or MoMA, is defined as an aircraft capable of flying 180-250 passengers without refueling for 2,300-5,800 miles(~2,000-5,000 nautical miles). As the name suggests, middle-of-market aircraft are positioned in between the market segments served by narrow body (single-aisle) and wide body (twin-aisle) aircraft. This paper presents the findings of a study on the effect of anthropomorphic variability on economy class seating on middle-market aircraft currently in service. The study found that among 130 middle-market LOPAs, the mean seat pitch was greater for US airlines than for Asian airlines. Furthermore, the sampled Asian airlines had a higher preference …
Monte Carlo Simulations Of Three-Dimensional Electromagnetic Gaussian Schell-Model Sources, Milo W. Hyde Iv, Santasri Bose-Pillai, Olga Korotkova
Monte Carlo Simulations Of Three-Dimensional Electromagnetic Gaussian Schell-Model Sources, Milo W. Hyde Iv, Santasri Bose-Pillai, Olga Korotkova
Faculty Publications
This article presents a method to simulate a three-dimensional (3D) electromagnetic Gaussian-Schell model (EGSM) source with desired characteristics. Using the complex screen method, originally developed for the synthesis of two-dimensional stochastic electromagnetic fields, a set of equations is derived which relate the desired 3D source characteristics to those of the statistics of the random complex screen. From these equations and the 3D EGSM source realizability conditions, a single criterion is derived, which when satisfied guarantees both the realizability and simulatability of the desired 3D EGSM source. Lastly, a 3D EGSM source, with specified properties, is simulated; the Monte Carlo simulation …
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
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 …
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
Predicting The Next Us President By Simulating The Electoral College, Boyan Kostadinov
Publications and Research
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 …
Burden Of Rheumatoid Arthritis Among Us Medicare Population: Co-Morbidities, Health-Care Resource Utilization And Costs, Chieh-I Chen, Li Wang, Wenhui Wei, Huseyin Yuce, Kristine Phillips
Burden Of Rheumatoid Arthritis Among Us Medicare Population: Co-Morbidities, Health-Care Resource Utilization And Costs, Chieh-I Chen, Li Wang, Wenhui Wei, Huseyin Yuce, Kristine Phillips
Publications and Research
Objectives. The study aimed to assess the burden of RA among the US Medicare population (aged 65 years) by comparing co-morbidities, health-care resource utilization (HCRU) and costs against matched non-RA Medicare patients.
Methods. Data were obtained from the Medicare fee-for-service claims database from 2010 to 2013. RA Medicare patients were identically matched with Medicare patients without RA (controls) based on demographics. Bivariate analyses were conducted to examine differences between cohorts for comorbidities, HCRU and costs. A generalized linear model was used to test relationships between patient-level characteristics, HCRU and costs.
Results. The study population included 115 867 RA patients and …
Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz
Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John M. Zobitz
Spora: A Journal of Biomathematics
We analyze a process-based temperature model for the length distribution and population over time of mayfly nymphs. Model parameters are estimated using a Markov Chain Monte Carlo parameter estimation method utilizing length distribution data at five different stream sites. Two different models (a standard exponential model and a modified Weibull model) of mayfly mortality are evaluated, where in both cases mayfly length growth is a function of stream temperature. Based on model-data comparisons to the modeled length distribution and the Bayesian Information Criterion, we found that approaches that length distribution data can reliably estimate 2–3 model parameters. Future model development …
Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John Zobitz
Modeling Mayfly Nymph Length Distribution And Population Dynamics Across A Gradient Of Stream Temperatures And Stream Types, Jeremy Anthony, Jennifer Baccam, Imanuel Bier, Emily Gregg, Leif Halverson, Ryan Mulcahy, Emmanuel Okanla, Samira A. Osman, Adam R. Pancoast, Kevin C. Schultz, Alex Sushko, Jennifer Vorarath, Yia Vue, Austin Wagner, Emily Gaenzle Schilling, John Zobitz
Faculty Authored Articles
We analyze a process-based temperature model for the length distribution and population over time of mayfly nymphs. Model parameters are estimated using a Markov Chain Monte Carlo parameter estimation method utilizing length distribution data at five different stream sites. Two different models (a standard exponential model and a modified Weibull model) of mayfly mortality are evaluated, where in both cases mayfly length growth is a function of stream temperature. Based on model-data comparisons to the modeled length distribution and the Bayesian Information Criterion, we found that approaches that length distribution data can reliably estimate 2–3 model parameters. Future model development …
A Preliminary Study Of Smithport Plain Bottle Morphology In The Southern Caddo Area, Robert Z. Selden Jr.
A Preliminary Study Of Smithport Plain Bottle Morphology In The Southern Caddo Area, Robert Z. Selden Jr.
CRHR: Archaeology
This study expands upon a previous analysis of the Clarence H. Webb collection, which resulted in the identification of two discrete shapes used in the manufacture of the base and body of Smithport Plain bottles. The sample includes the Smithport Plain bottles from the Webb collection, and four new bottles: two previously repatriated specimens in the Pohler Collection, and two from the Mitchell site (41BW4) to test whether those specimens align morphologically with the Belcher Mound or Smithport Landing specimens. Results indicate significant allometry and a significant difference in Smithport Plain body and base shapes for bottles produced at the …
X-Ray Spectroscopy Of Nio And Nanodiamond At Ssrl, Jackson Earl
X-Ray Spectroscopy Of Nio And Nanodiamond At Ssrl, Jackson Earl
STAR Program Research Presentations
The first aspect of this research project focuses on investigating the surface chemistry of high pressure high temperature (HPHT) nanodiamond by using X-ray spectroscopy techniques at the Stanford Synchrotron Radiation Lightsource (SSRL). HPHT nanodiamond is being examined as a biosensing tool for electric field detection based on the fluorescent nitrogen vacancy center hosted within diamond. With use of the transition edge spectrometer (TES), a state-of-the-art X-ray fluorescence detector, we are able to probe the surface and bulk properties of diamond. Preliminary work using density functional theory (DFT) has been done, offering insight into ground state energies and electronic structure. DFT …
Gene × Environment Interaction: What Exactly Are We Talking About?, David S. Moore
Gene × Environment Interaction: What Exactly Are We Talking About?, David S. Moore
Pitzer Faculty Publications and Research
An ambiguity exists in how psychological scientists use the word “interaction.” This word can refer to physical interactions between components that constitute the mechanisms in complex systems, but it can also refer to statistical interactions revealed by General Linear Statistical Models (e.g., Analyses of Variance). Statistical interactions indicate that the nature of the relationship between two variables depends on a third variable, but the discovery of such interactions does not constitute evidence of physical interactions between components in a system. Studies conducted using traditional behavioral genetics methods sometimes reveal statistical interactions between genes and environments, but the presence or absence …
A Proposed Taxonomy For The Systems Statistical Engineering Body Of Knowledge, Teddy Steven Cotter
A Proposed Taxonomy For The Systems Statistical Engineering Body Of Knowledge, Teddy Steven Cotter
Engineering Management & Systems Engineering Faculty Publications
In the ASEM-IAC 2012, Cotter (2012) identified the gaps in knowledge that statistical engineering needs to address, explored additional gaps in knowledge not addressed in the prior works, and set forth a working definition of and body of knowledge for statistical engineering. In the ASEM-IAC 2015, Cotter (2015) proposed a systemic causal Bayesian hierarchical model that addressed the knowledge gap needed to integrate deterministic mathematical engineering causal models within a stochastic framework. Missing, however, is the framework for specifying the hierarchical qualitative systems structures necessary and sufficient for specifying systemic causal Bayesian hierarchical models. In the ASEM-IAC 2016, Cotter (2016) …
Providing Access To Confidential Research Data Through Synthesis And Verification: An Application To Data On Employees Of The U.S. Federal Government, Andrés F. Barrientos, Alexander Bolton, Tom Balmat, Jerome P. Reiter, John M. De Figueiredo, Ashwin Machanavajjhala, Yan Chen, Charley Kneifel, Mark Delong
Providing Access To Confidential Research Data Through Synthesis And Verification: An Application To Data On Employees Of The U.S. Federal Government, Andrés F. Barrientos, Alexander Bolton, Tom Balmat, Jerome P. Reiter, John M. De Figueiredo, Ashwin Machanavajjhala, Yan Chen, Charley Kneifel, Mark Delong
Faculty Scholarship
Data stewards seeking to provide access to large-scale social science data face a difficult challenge. They have to share data in ways that protect privacy and confidentiality, are informative for many analyses and purposes, and are relatively straightforward to use by data analysts. One approach suggested in the literature is that data stewards generate and release synthetic data, that is, data simulated from statistical models, while also providing users access to a verification server that allows them to assess the quality of inferences from the synthetic data. We present an application of the synthetic data plus verification server approach to …
Borrowing Capacity, Financial Instability, And Contagion: Case Study Of The U.S. Subprime Mortgage Crisis, Youngna Choi
Borrowing Capacity, Financial Instability, And Contagion: Case Study Of The U.S. Subprime Mortgage Crisis, Youngna Choi
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
We use the case of the 2007 United States subprime mortgage crisis to investigate the impact of borrowing capacity limitations on financial instability and contagion. We divide an economy into agents that interact via flow of funds and express the financial instability level of each agent as a function of time derivatives of its wealth, cash inflows, and borrowing capacity. We show that among these factors, the borrowing capacity, which is determined by other economic constraints, has the largest impact on financial instability. It is suggested that borrowing capacity limitations could even cause contagion through feedback loop formed by flow …
The Impact Of Truncating Data On The Predictive Ability For Single-Step Genomic Best Linear Unbiased Prediction, Jeremy T. Howard, Thomas A. Rathje, Caitlyn E. Bruns, Danielle F. Wilson-Wells, Stephen D. Kachman, Matthew L. Spangler
The Impact Of Truncating Data On The Predictive Ability For Single-Step Genomic Best Linear Unbiased Prediction, Jeremy T. Howard, Thomas A. Rathje, Caitlyn E. Bruns, Danielle F. Wilson-Wells, Stephen D. Kachman, Matthew L. Spangler
Department of Animal Science: Faculty Publications
Simulated and swine industry data sets were utilized to assess the impact of removing older data on the predictive ability of selection candidate estimated breeding values (EBV) when using single-step genomic best linear unbiased prediction (ssGBLUP). Simulated data included thirty replicates designed to mimic the structure of swine data sets. For the simulated data, varying amounts of data were truncated based on the number of ancestral generations back from the selection candidates. The swine data sets consisted of phenotypic and genotypic records for three traits across two breeds on animals born from 2003 to 2017. Phenotypes and genotypes were iteratively …
Psychometric Properties Of A Working Memory Span Task, Juan M. Alzate Vanegas
Psychometric Properties Of A Working Memory Span Task, Juan M. Alzate Vanegas
Honors Undergraduate Theses
The intent of this thesis is to examine the psychometric properties of a complex span task (CST) developed to measure working memory capacity (WMC) using measurements obtained from a sample of 68 undergraduate students at the University of Central Florida. The Grocery List Task (GLT) promises several design improvements over traditional CSTs in a prior study about individual differences in WMC and distraction effects on driving performance, and it offers potential benefits for studying WMC as well as the serial-position effect. Currently, the working memory system is composed of domain-general memorial storage processes and information-processing, which involves the use of …
Analysis Of Residential And Auto Break-In Records In Taipei City, Afnan Althoupety, Aishwarya Joy, Juchun Cheng, Priyanka Patil, Tejas Deshpande
Analysis Of Residential And Auto Break-In Records In Taipei City, Afnan Althoupety, Aishwarya Joy, Juchun Cheng, Priyanka Patil, Tejas Deshpande
Engineering and Technology Management Student Projects
Taipei City is the capital of Taiwan. It has population of 2.7 million living in the city area of 271 km2 (104 mi2). There are totally 12 administrative districts in this city. To maintain the safety of the city, Taipei City Police Bureau has arranged regular patrol routes with focus on the high-risk area where residential and auto break-in occurs. Due to limited police resource, resident neighborhood also organized volunteered patrol teams to enhance the security in residential area. Based on past file record history, the Bureau would like to understand the high-risk districts and time schedule to improve their …
Improved Methods And Selecting Classification Types For Time-Dependent Covariates In The Marginal Analysis Of Longitudinal Data, I-Chen Chen
Theses and Dissertations--Epidemiology and Biostatistics
Generalized estimating equations (GEE) are popularly utilized for the marginal analysis of longitudinal data. In order to obtain consistent regression parameter estimates, these estimating equations must be unbiased. However, when certain types of time-dependent covariates are presented, these equations can be biased unless an independence working correlation structure is employed. Moreover, in this case regression parameter estimation can be very inefficient because not all valid moment conditions are incorporated within the corresponding estimating equations. Therefore, approaches using the generalized method of moments or quadratic inference functions have been proposed for utilizing all valid moment conditions. However, we have found that …
Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz
Automated Tree-Level Forest Quantification Using Airborne Lidar, Hamid Hamraz
Theses and Dissertations--Computer Science
Traditional forest management relies on a small field sample and interpretation of aerial photography that not only are costly to execute but also yield inaccurate estimates of the entire forest in question. Airborne light detection and ranging (LiDAR) is a remote sensing technology that records point clouds representing the 3D structure of a forest canopy and the terrain underneath. We present a method for segmenting individual trees from the LiDAR point clouds without making prior assumptions about tree crown shapes and sizes. We then present a method that vertically stratifies the point cloud to an overstory and multiple understory tree …
Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger
Modeling And Mapping Location-Dependent Human Appearance, Zachary Bessinger
Theses and Dissertations--Computer Science
Human appearance is highly variable and depends on individual preferences, such as fashion, facial expression, and makeup. These preferences depend on many factors including a person's sense of style, what they are doing, and the weather. These factors, in turn, are dependent upon geographic location and time. In our work, we build computational models to learn the relationship between human appearance, geographic location, and time. The primary contributions are a framework for collecting and processing geotagged imagery of people, a large dataset collected by our framework, and several generative and discriminative models that use our dataset to learn the relationship …
Occurrence And Attributes Of Two Echinoderm-Bearing Faunas From The Upper Mississippian (Chesterian; Lower Serpukhovian) Ramey Creek Member, Slade Formation, Eastern Kentucky, U.S.A., Ann Well Harris
Theses and Dissertations--Earth and Environmental Sciences
Well-preserved echinoderm faunas are rare in the fossil record, and when uncovered, understanding their occurrence can be useful in interpreting other faunas. In this study, two such faunas of the same age from separate localities in the shallow-marine Ramey Creek Member of the Slade Formation in the Upper Mississippian (Chesterian) rocks of eastern Kentucky are examined. Of the more than 5,000 fossil specimens from both localities, only 9–34 percent were echinoderms from 3–5 classes. Nine non-echinoderm (8 invertebrate and one vertebrate) classes occurred at both localities, but of these, bryozoans, brachiopods and sponges dominated. To understand the attributes of both …
Accounting For Matching Uncertainty In Photographic Identification Studies Of Wild Animals, Amanda R. Ellis
Accounting For Matching Uncertainty In Photographic Identification Studies Of Wild Animals, Amanda R. Ellis
Theses and Dissertations--Statistics
I consider statistical modelling of data gathered by photographic identification in mark-recapture studies and propose a new method that incorporates the inherent uncertainty of photographic identification in the estimation of abundance, survival and recruitment. A hierarchical model is proposed which accepts scores assigned to pairs of photographs by pattern recognition algorithms as data and allows for uncertainty in matching photographs based on these scores. The new models incorporate latent capture histories that are treated as unknown random variables informed by the data, contrasting past models having the capture histories being fixed. The methods properly account for uncertainty in the matching …
The Family Of Conditional Penalized Methods With Their Application In Sufficient Variable Selection, Jin Xie
The Family Of Conditional Penalized Methods With Their Application In Sufficient Variable Selection, Jin Xie
Theses and Dissertations--Statistics
When scientists know in advance that some features (variables) are important in modeling a data, then these important features should be kept in the model. How can we utilize this prior information to effectively find other important features? This dissertation is to provide a solution, using such prior information. We propose the Conditional Adaptive Lasso (CAL) estimates to exploit this knowledge. By choosing a meaningful conditioning set, namely the prior information, CAL shows better performance in both variable selection and model estimation. We also propose Sufficient Conditional Adaptive Lasso Variable Screening (SCAL-VS) and Conditioning Set Sufficient Conditional Adaptive Lasso Variable …
Mixtures-Of-Regressions With Measurement Error, Xiaoqiong Fang
Mixtures-Of-Regressions With Measurement Error, Xiaoqiong Fang
Theses and Dissertations--Statistics
Finite Mixture model has been studied for a long time, however, traditional methods assume that the variables are measured without error. Mixtures-of-regression model with measurement error imposes challenges to the statisticians, since both the mixture structure and the existence of measurement error can lead to inconsistent estimate for the regression coefficients. In order to solve the inconsistency, We propose series of methods to estimate the mixture likelihood of the mixtures-of-regressions model when there is measurement error, both in the responses and predictors. Different estimators of the parameters are derived and compared with respect to their relative efficiencies. The simulation results …
Improved Standard Error Estimation For Maintaining The Validities Of Inference In Small-Sample Cluster Randomized Trials And Longitudinal Studies, Whitney Ford Tanner
Improved Standard Error Estimation For Maintaining The Validities Of Inference In Small-Sample Cluster Randomized Trials And Longitudinal Studies, Whitney Ford Tanner
Theses and Dissertations--Epidemiology and Biostatistics
Data arising from Cluster Randomized Trials (CRTs) and longitudinal studies are correlated and generalized estimating equations (GEE) are a popular analysis method for correlated data. Previous research has shown that analyses using GEE could result in liberal inference due to the use of the empirical sandwich covariance matrix estimator, which can yield negatively biased standard error estimates when the number of clusters or subjects is not large. Many techniques have been presented to correct this negative bias; However, use of these corrections can still result in biased standard error estimates and thus test sizes that are not consistently at their …
Old English Character Recognition Using Neural Networks, Sattajit Sutradhar
Old English Character Recognition Using Neural Networks, Sattajit Sutradhar
College of Graduate Studies: Theses & Dissertations
Character recognition has been capturing the interest of researchers since the beginning of the twentieth century. While the Optical Character Recognition for printed material is very robust and widespread nowadays, the recognition of handwritten materials lags behind. In our digital era more and more historical, handwritten documents are digitized and made available to the general public. However, these digital copies of handwritten materials lack the automatic content recognition feature of their printed materials counterparts. We are proposing a practical, accurate, and computationally efficient method for Old English character recognition from manuscript images. Our method relies on a modern machine learning …
A Primer On Noise-Induced Transitions In Applied Dynamical Systems, Eric Forgoston, Richard O. Moore
A Primer On Noise-Induced Transitions In Applied Dynamical Systems, Eric Forgoston, Richard O. Moore
Department of Applied Mathematics and Statistics Faculty Scholarship and Creative Works
Noise plays a fundamental role in a wide variety of physical and biological dynamical systems. It can arise from an external forcing or due to random dynamics internal to the system. It is well established that even weak noise can result in large behavioral changes such as transitions between or escapes from quasi-stable states. These transitions can correspond to critical events such as failures or extinctions that make them essential phenomena to understand and quantify, despite the fact that their occurrence is rare. This article will provide an overview of the theory underlying the dynamics of rare events for stochastic …
A Probability Model For Strategic Bidding On The Price Is Right, Paul H. Kvam
A Probability Model For Strategic Bidding On The Price Is Right, Paul H. Kvam
Department of Math & Statistics Faculty Publications
The TV game show “The Price is Right” features a bidding auction called “Contestants’ Row” that rewards the player (out of 4) who bids closest to an item’s value, without overbidding. This paper considers ways in which players can maximize a winning probability based on the player's bidding order. We consider marginal strategies in which players assume opponents are bidding individually perceived values of the merchandise. Based on preceding bids of others, players have information available to create strategies. We consider conditional strategies in which players adjust bids knowing other players are using strategies. The last bidder has a large …
A Model To Predict Concentrations And Uncertainty For Mercury Species In Lakes, Ashley Hendricks
A Model To Predict Concentrations And Uncertainty For Mercury Species In Lakes, Ashley Hendricks
Dissertations, Master's Theses and Master's Reports
To increase understanding of mercury cycling, a seasonal mass balance model was developed to predict mercury concentrations in lakes and fish. Results indicate that seasonality in mercury cycling is significant and is important for a northern latitude lake. Models, when validated, have the potential to be used as an alternative to measurements; models are relatively inexpensive and are not as time intensive. Previously published mercury models have neglected to perform a thorough validation. Model validation allows for regulators to be able to make more informed, confident decisions when using models in water quality management. It is critical to quantify uncertainty; …