R for modellers

These small snapshots (“vignettes”) illustrate techniques in R. This information is mainly geared towards mathematical modellers but may be useful to others.

If you are registered in one of the courses I teach at the University of Manitoba in which I require R coding, e.g., Mathematics of Data Science (MATH 2740), some of the vignettes are required material.

Slides are produced using Quarto and, for a few, using Sweave. Slide sources and all the code used are available on the GitHub repo. Feel free to use any material; if you find this useful, I will be happy to know, that’s all.

Material here is inherently work in progress. I will be updating the vignettes from time to time to reflect a better understanding of the material, new packages, etc. The vignettes and videos vary greatly in length. Their order is not relevant and somewhat random.

When present, the YouTube logo points to the video of the vignette. Those vignettes for which a video is available are more complete than those without.

• Vignette 00 - About these "vignettes"
• Vignette 01 - Introduction to and installation of R
• Vignette 02 - RStudio and friends
• Vignette 03 - Installing and loading packages
• Vignette 04 - Data types and simple operations
• Vignette 05 - Flow control
• Vignette 06 - apply, lapply and friends
• Vignette 07 - parLapply and friends
• Vignette 08 - Acquiring data
• Vignette 09 - Data wrangling
• Vignette 10 - Solving ODE in R
• Vignette 11 - Solving DDE in R
• Vignette 12 - Fitting an ODE
• Vignette 13 - RStudio
• Vignette 14 - RStudio server
• Vignette 15 - RMarkdown
• Vignette 16 - Sweave
• Vignette 17 - Quarto
• Vignette 18 - Shiny
• Vignette 19 - Shiny-server
• Vignette 20 - Discrete Time Markov Chains (DTMC) in R
• Vignette 21 - Continuous Time Markov Chains (CTMC) in R
• Vignette 22 - Stochastic Differential Equations (SDE) in R
• Vignette 23 - Sensitivity analysis in R
• Vignette 24 - R from the command line

Transversal lectures

I have started preparing some lectures that take a transversal approach, digging into one topic in detail using a variety of techniques illustrated in the vignettes above. For the time being, there is a single such lecture here, but I aim to make others. (If you have a request for a topic, feel free to get in touch.)

• Basic computational analysis of a model. Note that this is work in progress.

Note pour les étudiants francophones

Je prévois de traduire les vignettes en français, mais cela prendra du temps. En attendant, si vous avez des questions, n’hésitez pas à me contacter.