ICI3D R tutorials and labs

Tutorials

Tutorial 0: Introduction to R Studio - provides an introduction to the user interface (required)
Tutorial 1: Introduction to R and its quirks (required)
Tutorial 2: More on Vectors, Data Frames, and Functions (required)
Tutorial 3: Probability Distributions and Control Structures (required)
Tutorial 4: Visualizing Infectious Disease Data in R (recommended)
Tutorial 5: Data cleaning and management in R (recommended)

Labs

Lab 1: ODE models in R (required)
Lab 2: Consequences of heterogeneity (required)
- Download data file
Lab 3: Study Design in Epidemiology lab (required for Track A)
Lab 4: Study Design for Clinical Trials (recommended for Track A)
- Download data file
Lab 5: Introduction to Likelihood (required)
Lab 6: MLE fitting of a dynamic model (required)
Lab 7: MCMC fitting of a binomial distribution (required)
Lab 8: MCMC fitting of a dynamic model (optional)
- Note: Download this file to avoid having to wait for long MCMC chains to be sampled.

Exercises and Examples

Exercise 1: Basic stochastic simulation models - Stochastic spillover (required for Track B)
Exercise 2: Basic stochastic simulation models - Demographic stochasticity (recommended for Track B)
Stochastic SIR Example - Gillespie Algorithm
Stochastic SIR Example - Chain Binomial

Participatory Coding Archive