Defining scenarios by description vs. from data/cases (i.e., by experience)

[hneth]

Idea

riskyr currently assumes that scenarios are defined by 3 essential probabilities (typically prev, sens, and spec or fart, plus some population size N) or 4 essential frequencies (typically hi, mi, fa, and cr).

A more flexible setup would allow defining scenarios either from parameters (i.e., "by description) or from data or cases (i.e., "by experience").

1. By description: Define a scenario from parameters (to create/simulate cases):

   • provide 4 essential frequencies (i.e., specifying the result)
   • provide 3 essential probabilities, N, and round to exact frequencies
   • provide 3 essential probabilities, N, and sample from given probabilities

2. By experience: Define scenario from data or cases (to compute/extract parameters):

   • provide binary data frame of cases (and frame 2x2 matrix)
   • provide non-binary data frame of cases and a criterion to be maximized to binarize predictor variable

ToDo

See comp_popu() for a first function that generates data/cases (as df popu) from one type of description:

• from 4 essential frequencies

Add option for generating corresponding simulations: Generate popu (as df):

• from probabilities and N (using exact or rounded values)
• from probabilities and N (and sample() from N)

Define a complementary function desc_data() that generates the description from (binary or binarized) data or cases.

[hneth]

This issue is partially addressed by the interplay between the read_popu() and write_popu() functions in riskyr v0.4.0.

More complete treatments are conceivable, but not a current priority.