Stan model
functions{
real zeta(real s);
/*TODO: implement rng for prior and posterior predictive checks*/
}
data{
int<lower=0> K; // number of unique values
int values[K];
int<lower=0> frequencies[K];
library(deSolve) | |
sir <- function(time, state, parameters) { ## this is the ODE system | |
with(as.list(c(state, parameters)), { | |
dS <- -beta * S * I | |
dI <- beta * S * I - gamma * I | |
dR <- gamma * I | |
return(list(c(dS, dI, dR))) | |
}) | |
} |
Stan model
functions{
real zeta(real s);
/*TODO: implement rng for prior and posterior predictive checks*/
}
data{
int<lower=0> K; // number of unique values
int values[K];
int<lower=0> frequencies[K];