This function simplifies the process of checking which parameters a given idmodelr model depends on. It is effectively an interface to parameter_details via model_details. As fuzzy matching has been used it can also given information of the parameter requirements of a subset of the available models.

required_parameters(model = NULL)

Arguments

model

A character string containing the name of the model of interest. Defaults to NULL.

Value

A dataframe extracted from parameter_details containing the details of the parameters required by the model of interest.

Examples

## Check the parameters required by the "SIR_ode" model required_parameters("SIR_ode")
#> # A tibble: 2 x 6 #> parameter parameter_family description type risk_stratified non_exponential #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 beta transmission Transmission… rate no no #> 2 tau recovery Recovery rat… rate no no
## Use fizzy matching to look at parameters for all SIR models required_parameters("SIR")
#> # A tibble: 5 x 6 #> parameter parameter_family description type risk_stratified non_exponential #> <chr> <chr> <chr> <chr> <chr> <chr> #> 1 beta transmission Transmission… rate no no #> 2 tau recovery Recovery rat… rate no no #> 3 lambda vaccination The effectiv… prob… no no #> 4 alpha vaccination The coverage… prop… no no #> 5 mu demographics The natural … rate no no