Physical Sciences and Mathematics Commons^™

Msis-Glenn: Natural Selection In Wolves Leads To Domesticated Dogs Predicted By Agent-Based Model Simulations, Alex Capaldi, David C. Elzinga

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

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

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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 …

A Course In Data Science: R And Prediction Modeling, Adam Kapelner

Open Educational Resources

This is a self-contained course in data science and machine learning using R. It covers philosophy of modeling with data, prediction via linear models, machine learning including support vector machines and random forests, probability estimation and asymmetric costs using logistic regression and probit regression, underfitting vs. overfitting, model validation, handling missingness and much more. There is formal instruction of data manipulation using dplyr and data.table, visualization using ggplot2 and statistical computing.

A Cost-Effective Method To Passively Sample Communities At The Forest Canopy-Aerosphere Interface, Michael Cunningham-Minnick, H. Patrick Roberts, Brian Kane Ph.D., Joan Milam, David I. King Ph.D.

Data and Datasets

HOBO logger data of hourly measurements at canopy-aerosphere interface from June to August above temperate forest on campus of University of Massachusetts. Weather station data (precipitation and wind speeds) from nearby weather station extracted from Mesowest.com and needed for manuscript figures. Code (R language) to recreate foundation of figures in manuscript.

Supplementary Files For "Creating A Universal Depth-To-Load Conversion Technique For The Conterminous United States Using Random Forests", Jesse Wheeler, Brennan Bean, Marc Maguire

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As part of an ongoing effort to update the ground snow load maps in the United States, this paper presents an investigation into snow densities for the purpose of predicting ground snow loads for structural engineering design with ASCE 7. Despite their importance, direct measurements of snow load are sparse when compared to measurements of snow depth. As a result, it is often necessary to estimate snow load using snow depth and other readily accessible climate variables. Existing depth-to-load conversion methods, each of varying complexity, are well suited for snow load estimation for a particular region or station network, but …

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.

How Data Is Changing The World Of Healthcare, Cameron Marous

Honors Capstone Enhancement Presentations

No abstract provided.

An Introduction To Copulas, Yifan Guo, Geng Zhang

Capstone Showcase

Copulas are the mathematical functions that connect the distribution functions of univariate random variables to form multivariate distributions. We define copulas, present some of their key properties, and provide examples of their applications.

American Bittern (Botaurus Lentiginosus), Jennifer Smetzer, Toni Lyn Morelli

Second Century Stewardship Refugia Products

No abstract provided.

Where On Ice? Algorithmically Deconstructing Nhl Shot Locations As A Method For Player Classification, Devan Becker, Douglas G. Woolford, Charmaine B. Dean

Western Research Forum

Where do hockey players shoot from? How does this vary from player to player? We present the results of a study that uses data-driven statistical methods to investigate these questions. The locations of shots by National Hockey League (NHL) players from 2011 to 2017 are analyzed using a combination of an image recognition algorithm and spatial statistical methodology. An unsupervised classifier is applied to output from a spatial point process model in order to determine which shot locations best characterize a given player. We define the number of regions a priori, but the image recognition algorithm chooses the shape …

Mapping In The Humanities: Gis Lessons For Poets, Historians, And Scientists, Emily W. Fairey

Open Educational Resources

User-friendly Geographic Information Systems (GIS) is the common thread of this collection of presentations, and activities with full lesson plans. The first section of the site contains an overview of cartography, the art of creating maps, and then looks at historical mapping platforms like Hypercities and Donald Rumsey Historical Mapping Project. In the next section Google Earth Desktop Pro is introduced, with lessons and activities on the basics of GE such as pins, paths, and kml files, as well as a more complex activity on "georeferencing" an historic map over Google Earth imagery. The final section deals with ARCGIS Online …

Comparing Methods Of Measuring Chaos In The Symbolic Dynamics Of Strange Attractors, James J. Scully

Georgia State Undergraduate Research Conference

No abstract provided.

Pglr-Sas Data, Joseph M. Hilbe

Joseph M Hilbe

SAS data files for Practical Guide to Logistic Regression

R Code For Practical Guide To Logistic Regression, Joseph M. Hilbe

Joseph M Hilbe

R code for Practical Guide to Logistic Regression

Pglr-Stata Data Files, Joseph M. Hilbe

Joseph M Hilbe

Stata data files for Practical Guide to Logistic Regression

Deciphering The Associations Between Gene Expression And Copy Number Alteration Using A Sparse Double Laplacian Shrinkage Approach, Shuangge Ma

Shuangge Ma

Both gene expression levels (GEs) and copy number alterations (CNAs) have important implications in the development of complex diseases. GEs are partly regulated by CNAs, and much effort has been devoted to understanding their relations. The expression of a gene can be regulated by multiple CNAs, and one CNA can regulate the expression of multiple genes. In addition, multiple GEs (CNAs) can be correlated with each other. The existing methods for associating GEs with CNAs have limitations in deciphering the complex data structures. In this study, we develop a sparse double Laplacian shrinkage approach. It jointly models the effects of …

A Penalized Robust Semiparametric Approach For Gene-Environment Interactions, Shuangge Ma

Shuangge Ma

In genetic and genomic studies, gene-environment (G*E) interactions have important implications. Some of the existing G$\times$E interaction methods are limited by analyzing a small number of G factors at a time, by assuming linear effects of E factors, by assuming no data contamination, and by adopting ineffective selection techniques. In this study, we propose a new approach for identifying important G*E interactions. It jointly models the effects of all E and G factors and their interactions. A partially linear varying coefficient model (PLVCM) is adopted to accommodate possible nonlinear effects of E factors. A rank-based loss function is used to …

Mcd - Stata Commands, Joseph M. Hilbe

Joseph M Hilbe

Stata commands and affiliated files for examples in book. Text file explanation of command names is included. 103 files in total

Mcd - 11 R Data Files From Book, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data: ZIP file with 11 R data files from book

Mcd - 11 Stata Data Files, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data: 11 Stata files from book

Hilbe-Mcd-Cvs-Data, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data, data files from book in CVS format

Mcd - 11 Excel Data Files, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data - 11 Excel files for use with the book

Mcd-Data-Sas, Joseph M. Hilbe

Joseph M Hilbe

Modeling Count Data, 11 SAS data files. SAS users

Demonstration Databases (Supplemental To Psychology & Health Article), Blair T. Johnson

CHIP Documents

Here is a database (in Stata, R, SAS, SPSS formats) that was used to demonstrate simple slopes analysis in meta-regression in an online supplement to the article, "Panning for the gold in health research: Incorporating studies’ methodological quality in meta-analysis," published in the journal Psychology & Health in 2014. It is an archive (zip) file that also contains the Stata syntax used in the demonstrations.

R Code To Accompany “Principal Component Analysis And Optimization: A Tutorial”, Robert Reris, J. Paul Brooks

Statistical Sciences and Operations Research Data

This data accompanies "Principal Component Analysis and Optimization: A Tutorial" by Robert Reris and J. Paul Brooks, presented at the 2015 INFORMS Computing Society Conference, Operations Research and Computing: Algorithms and Software for Analytics, Richmond, Virginia January 11-13, 2015.

The data contains R code, output, and comments that follow the examples for principal component analysis in the paper.

Sas Macro: Testing Marginal Homogeneity In Clustered Matched-Pair Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

The SAS Macro and simulated data example are used to demonstrate the application of tests for marginal homogeneity in clustered matched-pair data.

Sas Macro: Weighted Kappa Statistic For Clustered Matched-Pair Ordinal Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

This SAS macro calculate the weighted kappa statistic and its corresponding non-parametric variance estimator for the clustered matched-pair ordinal data.

Sas Macro: Kappa Statistic For Clustered Physician-Patients Polytomous Data, Zhao Yang

Zhao (Tony) Yang, Ph.D.

This SAS macro calculate the kappa statistic and its semi-parametric variance estimator for the clustered physician-patients polytomous data. The proposed method depends on the assumption of conditional independence for the clustered physician-patients data structure.

R Codes For " Hypothesis Testing For An Extended Cox Model With Time-Varying Coefficients" (Biometrics), Chongzhi Di

Chongzhi Di

No abstract provided.

Data Files To Accompany "The Support Vector Machine And Mixed Integer Linear Programming: Ramp Loss Svm With L1-Norm Regularization", Eric J. Hess, J. Paul Brooks

Statistical Sciences and Operations Research Data

These files accompany, "The Support Vector Machine and Mixed Integer Linear Programming: Ramp Loss SVM with L1-Norm Regularization" by Eric J. Hess and J. Paul Brooks, presented at the 2015 INFORMS Computing Society Conference, Operations Research and Computing: Algorithms and Software for Analytics, Richmond, Virginia January 11-13, 2015.

The files contain instances of optimization problems that are described in the paper and for which results are reported. The files are in CPLEX LP format. The naming convention of the files is as follows: ndBTj0F.lp, where is the number of samples, is the number of attributes, and refers to …