generate model data for testing purposes

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
)

Arguments

N_t: number of time-points
region_coeffs: vector of coefficients for regions determining kit orders
c_region: logit probability of kit use per region
reporting_freq: The frequency that distribution data is provided. If NULL distribution frequency matches orders frequency

Value

A tibble

Orders: Kit orders per time and region
regions: Numeric index indicating region of orders and distributions
Reported_Used: Number of kits reported as used
Reported_Distributed: Number of kits reported as distributed
p_use: Probability that a kit was used
p_reported: Probability that a distributed kit was reported
times: Index for time
region_name: String index for the region

Arguments

Value

See also