1. Introduction to the R language Mathew Plucinski University of Cambridge / UC Berkeley

2. What is it A free version of S+ Statistical programming Used extensively in computational biology, to a lesser extent in applied statistics, financial mathematics Interpretive language

3. Outline 1.Introduction to R Console 2.Basic arithmetic, working with vectors, and simple statistics 3.A more serious example – Gillespie Algorithm

4. Stochastic, Discrete SIR model SIR λIλIµ

5. S t,I t,R t

6. Stochastic, Discrete SIR model S t,I t,R t Infection Recovery

7. Stochastic, Discrete SIR model S t,I t,R t Infection Recovery

8. Stochastic, Discrete SIR model S t,I t,R t S t -1,I t +1,R t Infection

9. Stochastic, Discrete SIR model S t,I t,R t S t -1,I t +1,R t Infection Recovery

10. Stochastic, Discrete SIR model S t,I t,R t S t -1,I t +1,R t S t,I t -1,R t +1 Infection Recovery

11. Stochastic, Discrete SIR model Rate: λS t I t S t,I t,R t S t -1,I t +1,R t S t,I t -1,R t +1 Rate: µI t

12. Stochastic, Discrete SIR model p=λS t I t /(λS t I t + µI t ) S t,I t,R t S t -1,I t +1,R t S t,I t -1,R t +1 p= µI t /(λS t I t + µI t )