Functions to compute spread (variability, dispersion) of distribution (i.e.
"how wide it is spread"). `summ_spread()`

is a wrapper for respective
`summ_*()`

functions (from this page) with default arguments.

```
summ_spread(f, method = "sd")
summ_sd(f)
summ_var(f)
summ_iqr(f)
summ_mad(f)
summ_range(f)
```

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

method | Method of spread computation. Should be one of "sd", "var", "iqr", "mad", "range". |

All functions return a single number representing a spread of distribution.

`summ_sd()`

computes distribution's standard deviation.

`summ_var()`

computes distribution's variance.

`summ_iqr()`

computes distribution's interquartile range. Essentially, it is
a `as_q(f)(0.75) - as_q(f)(0.25)`

.

`summ_mad()`

computes distribution's *median* absolute deviation around the
distribution's *median*.

`summ_range()`

computes range length (difference between maximum and minimum)
of "x" values within region of positive probability. **Note** that this might
differ from length of support because the latter might be
affected by tails with zero probability (see Examples).

`summ_center()`

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

for general moments.

Other summary functions:
`summ_center()`

,
`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()`

```
# Type "continuous"
d_norm <- as_d(dnorm)
# The same as `summ_spread(d_norm, method = "sd")`
summ_sd(d_norm)#> [1] 0.9999766summ_var(d_norm)#> [1] 0.9999531summ_iqr(d_norm)#> [1] 1.348976summ_mad(d_norm)#> [1] 0.6744882summ_range(d_norm)#> [1] 9.506849#> [1] 3.162233summ_var(d_pois)#> [1] 9.999717summ_iqr(d_pois)#> [1] 4summ_mad(d_pois)#> [1] 2summ_range(d_pois)#> [1] 28
# Difference of `summ_range(f)` and `diff(meta_support(f))`
zero_tails <- new_d(data.frame(x = 1:5, y = c(0, 0, 1, 0, 0)), "continuous")
# This returns difference between 5 and 1
diff(meta_support(zero_tails))#> [1] 4 # This returns difference between 2 and 4 as there are zero-probability
# tails
summ_range(zero_tails)#> [1] 2
```