John Zobitz

Exploring Modeling with Data and Differential Equations Using R (eBook, PDF)

• Format: PDF

Produktbeschreibung

Exploring Modeling with Data and Differential Equations Using R provides a unique introduction to differential equations with applications to the biological and other natural sciences. Additionally, model parameterization and simulation of stochastic differential equations are explored, providing additional tools for model analysis and evaluation. This unified framework sits "at the intersection" of different mathematical subject areas, data science, statistics, and the natural sciences. The text throughout emphasizes data science workflows using the R statistical software program and the tidyverse constellation of packages. Only knowledge of calculus is needed; the text's integrated framework is a stepping stone for further advanced study in mathematics or as a comprehensive introduction to modeling for quantitative natural scientists.

The text will introduce you to:

• modeling with systems of differential equations and developing analytical, computational, and visual solution techniques.
• the R programming language, the tidyverse syntax, and developing data science workflows.
• qualitative techniques to analyze a system of differential equations.
• data assimilation techniques (simple linear regression, likelihood or cost functions, and Markov Chain, Monte Carlo Parameter Estimation) to parameterize models from data.
• simulating and evaluating outputs for stochastic differential equation models.

An associated R package provides a framework for computation and visualization of results. It can be found here: https://cran.r-project.org/web/packages/demodelr/index.html.

---

Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.

Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 378
• Erscheinungstermin: 29. November 2022
• Englisch
• ISBN-13: 9781000776744
• Artikelnr.: 66305935

Autorenporträt

John Zobitz is a Professor of Mathematics and Data Science at Augsburg University in Minneapolis, Minnesota. His scholarship in environmental data science includes ecosystem models parameterized with datasets from environmental observation networks. He is a member of the Mathematical Association of America (MAA) and previous president of the North Central Section of the MAA. He has served on the editorial board of MAA Notes. He was a recipient of the Fulbright-Saastamoinen Foundation Grant in Health and Environmental Sciences at the University of Eastern Finland in Kuopio, Finland. In addition, he is an affiliated member of the Ecological Forecasting Network and regularly taught at Fluxcourse, an annual summer course for measurements and modeling of ecosystem biogeochemical fluxes.

Inhaltsangabe

1. Models of rates with data 2. Introduction to R 3. Modeling With Rates of
Change 4. Euler's Method 5. Phase lines and equilibrium solutions 6.
Coupled Systems of Equations 7. Exact Solutions to Differential Equations
8. Linear Regression and Curve Fitting 9. Probability and Likelihood
Functions 10. Cost Functions & Bayes' Rule 11. Sampling Distributions and
the Bootstrap Method 12. The Metropolis-Hastings Algorithm 13. Markov Chain
Monte Carlo Parameter Estimation 14. Information Criteria 15. Systems of
linear differential equations 16. Systems of nonlinear equations 17. Local
Linearization and the Jacobian 18. What are eigenvalues? 19. Qualitative
Stability Analysis 20. Bifurcation 21. Stochastic Biological Systems 22.
Simulating and Visualizing Randomness 23. Random Walks 24. Diffusion and
Brownian Motion 25. Simulating Stochastic Differential Equations 26.
Statistics of a Stochastic Differential Equation 27. Solutions to
Stochastic Differential Equations