including mode for the distribution in `describe_distribution`

[IndrajeetPatil]

Saw some discussion on Twitter about how base-R doesn't have a function to calculate mode. So was wondering if it might be a good idea for us to include this info.

library(parameters)

describe_distribution(mtcars$wt)
#> Mean |   SD |  IQR |        Range | Skewness | Kurtosis |  n | n_Missing
#> ------------------------------------------------------------------------
#> 3.22 | 0.98 | 1.19 | [1.51, 5.42] |     0.47 |     0.42 | 32 |         0

getmode <- function(v) {
  uniqv <- unique(v)
  uniqv[which.max(tabulate(match(v, uniqv)))]
}

^{Created on 2021-06-03 by the reprex package (v2.0.0)}

[bwiernik]

Perhaps "modal_value()"?

[strengejacke]

Makes sense for factors or character vectors

[DominiqueMakowski]

For numeric vectors, the MAP estimate isprobably the closest meaningful equivalent

[bwiernik]

Is MAP computationally intensive at all?

[DominiqueMakowski]

Main running time devoted to computing the density curve i think

[bwiernik]

We should include the mode for categorical variables and the map for continuous

[bwiernik]

In light of #232, I think we should add a metrics argument like in performance::model_performance() that enumerates the stats to provide, with something like the current set as the default value.

[etiennebacher]

Closing in favor of #46