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Welcome to the domir wiki!

This wiki will be used as a supplement to the domir package’s vignettes. This wiki will illustrate how to use the features of the primary domin() function and will include a multitude of examples of applying domir() to different predictive modeling functions.

If you have not already done so, I recommend you read over the Conceptal Introduction to Dominance Analysis vignette. This vignette provides an example of dominance statistic computations and interpretation as well as a broad overview of what dominance analysis is doing in the background. This vignette also suggests how dominance analysis is implemented in terms of the API that functions in the domir package use.

Broadly, the domir() and domin() functions work by:

1. taking a stats::formula() (or domir::formula_list()) as input and parse each of them in a structured way to obtain names.
2. obtaining all requested combinations of names given the input and arguments changing parsing rules described in the Features page.
3. submitting all combinations of independent variable names, in the original input format (e.g., as a formula()) to the predictive modeling function.
4. collecting the returned values from running the predictive modeling function for all combinations of independent variable names.
5. using all collected returned values to compute dominance statistics and designations.

This very general structure makes domir() and domin() applicable to a wide variety of predictive modeling functions. So long as the predictive modeling function accepts a formula or formula_list—or can be adapted to use them with a custom wrapper function—and returns a scalar valued number, the function can be dominance analyzed using domir().