A multivariate synthetic infection-count dataset generated from three independent stochastic epidemic processes simulated using the Doob–Gillespie algorithm. Each time series has a different transmission rate, resulting in distinct change point structures.
data(epi_synthetic_multi)A \(3 \times 200\) numeric matrix. Each row represents one synthetic epidemic time series and each column corresponds to a discrete time point.
The simulation follows the stochastic framework described in: Anderson, D. F. and Kurtz, T. G. (2015). Stochastic Analysis of Biochemical Systems. Springer International Publishing.
All three epidemic processes use:
S0 = 100000, I0 = 20
max_time = 200
xi_0 = 1/8
The three beta vectors differ in their change-point locations and
values:
Series 1: 0.211 → 0.55 at time 120
Series 2: 0.215 → 0.52 at time 120
Series 3: 0.193 → 0.53 at time 30