Functions to compute center of distribution. `summ_center()`

is a wrapper for
respective `summ_*()`

functions (from this page) with default arguments.

```
summ_center(f, method = "mean")
summ_mean(f)
summ_median(f)
summ_mode(f, method = "global")
summ_midrange(f)
```

f | A pdqr-function representing distribution. |
---|---|

method | Method of center computation. For |

`summ_center()`

, `summ_mean()`

, `summ_median()`

and `summ_mode(*, method = "global")`

always return a single number representing a center of
distribution. `summ_mode(*, method = "local")`

can return a numeric vector
with multiple values representing local maxima.

`summ_mean()`

computes distribution's mean.

`summ_median()`

computes a smallest `x`

value for which cumulative
probability is not less than 0.5. Essentially, it is a `as_q(f)(0.5)`

. This
also means that for pdqr-functions with type "discrete" it always returns an
entry of "x" column from `f`

's "x_tbl" metadata.

`summ_mode(*, method = "global")`

computes a smallest `x`

(which is an entry
of "x" column from `f`

's `x_tbl`

) with the highest probability/density.
`summ_mode(*, method = "local")`

computes all `x`

values which represent
non-strict **local maxima** of probability mass/density function.

`summ_midrange()`

computes middle point of `f`

's support
(average of left and right edges).

`summ_spread()`

for computing distribution's spread, `summ_moment()`

for general moments.

Other summary functions:
`summ_classmetric()`

,
`summ_distance()`

,
`summ_entropy()`

,
`summ_hdr()`

,
`summ_interval()`

,
`summ_moment()`

,
`summ_order()`

,
`summ_prob_true()`

,
`summ_pval()`

,
`summ_quantile()`

,
`summ_roc()`

,
`summ_separation()`

,
`summ_spread()`

```
# Type "continuous"
d_norm <- as_d(dnorm)
## The same as `summ_center(d_norm, method = "mean")`
summ_mean(d_norm)
#> [1] -1.358047e-16summ_median(d_norm)
#> [1] 2.292681e-14summ_mode(d_norm)
#> [1] -2.904343e-12## As pdqr-functions always have finite support, output here is finite
summ_midrange(d_norm)
#> [1] -2.904788e-12#> [1] 9.999985summ_median(d_pois)
#> [1] 10## Returns the smallest `x` with highest probability
summ_mode(d_pois)
#> [1] 9## Returns all values which are non-strict local maxima
summ_mode(d_pois, method = "local")
#> [1] 9 10## As pdqr-functions always have finite support, output here is finite
summ_midrange(d_pois)
#> [1] 14
# Details of computing local modes
my_d <- new_d(data.frame(x = 11:15, y = c(0, 1, 0, 2, 0) / 3), "continuous")
## Several values, which are entries of `x_tbl`, are returned as local modes
summ_mode(my_d, method = "local")
#> [1] 12 14
```