8 research outputs found
Agent-Based Modeling for the Neophyte: An Application of NetLogo
Agent-based modeling has found applications in a wide range of fields including economics, sociology, ecology, epidemiology, transportation planning, and more. Its versatility allows researchers to investigate various “what-if” scenarios, test the effects of different policies or interventions, and gain insights into the underlying mechanisms driving complex systems. This article is intended for the curious student or researcher who is unfamiliar with agent based modeling, and is looking for a quick but reasonably informative exposure to the field
Compartmental Modeling for the Neophyte: An Application of Berkeley Madonna
Compartmental modeling serves as a necessary framework in many fields, especially biomathematics and ecology. This article introduces readers to a user-friendly approach to constructing compartmental models and solving the resulting systems of differential equations to simulate real-world applications. The platform used is Berkeley Madonna, a software package that has an intuitive graphical interface which empowers users—even those with limited mathematical and programming backgrounds—to focus on modeling concepts rather than mathematical or programming intricacies. This makes Berkeley Madonna an ideal platform for students, educators, and researchers
Clustering for the Neophyte: An R Shiny App for Self-Organizing Maps
This article provides an outline of clustering, key stages in creating self-organizing maps for purposes of clustering, instructions on how to use a free online R Shiny app that constructs self-organizing maps for data provided by users, and interpretations of the graphics produced
An R companion to linear statistical models
Focusing on user-developed programming, An R Companion to Linear Statistical Models serves two audiences: those who are familiar with the theory and applications of linear statistical models and wish to learn or enhance their skills in R; and those who are enrolled in an R-based course on regression and analysis of variance. For those who have never used R, the book begins with a self-contained introduction to R that lays the foundation for later chapters.This book includes extensive and carefully explained examples of how to write programs using the R programming language. These examples cov