Simulate kits ordered and kits distributed for a set number of regions and time-points.
The kits ordered simulation is a simple square-term multiplied by region_coeffs.
For example if region_coeffs = c(1,2) then the number of kits ordered at
month 12 are c(1,2) * 12^2 = c(144,288).
The probability of kit use in time is assumed to increase linearly in inverse
logit space at a constant rate 0.1.
The probability of reporting for each month and region is iid distributed
\(logit^{-1}(p) \sim N(2,5)\) which produces a mean reporting rate
of approximately 88%
generate_model_data(
N_t = 24,
region_coeffs = c(5, 0.5),
c_region = c(-1, 2),
reporting_freq = NULL
)
Kit orders per time and region
Numeric index indicating region of orders and distributions
Number of kits reported as used
Number of kits reported as distributed
Probability that a kit was used
Probability that a distributed kit was reported
Index for time
String index for the region
number of time-points
vector of coefficients for regions determining kit orders
logit probability of kit use per region
The frequency that distribution data is provided.
If NULL distribution frequency matches orders frequency
Other data generation:
model_random_walk_data()