generate_model_data {bennu} | R Documentation |

## generate model data for testing purposes

### Description

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%

### Usage

```
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 |

### 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

### See Also

Other data generation:
`model_random_walk_data()`

*bennu*version 0.3.0 Index]