`R/print.R`

, `R/new_p.R`

, `R/new_d.R`

, and 2 more
`methods-print.Rd`

Pdqr-functions have their own methods for `print()`

which displays function's
metadata in readable and concise form.

```
# S3 method for p
print(x, ...)
# S3 method for d
print(x, ...)
# S3 method for q
print(x, ...)
# S3 method for r
print(x, ...)
```

x | Pdqr-function to print. |
---|---|

... | Further arguments passed to or from other methods. |

Print output of pdqr-function describes the following information:

Full name of function class:

P-function is "Cumulative distribution function".

D-function is "Probability mass function" for "discrete" type and "Probability density function" for "continuous".

Q-function is "Quantile function".

R-function is "Random generation function".

Type of function in the form "of * type" where "*" is "discrete" or "continuous" depending on actual type.

Support of function.

Number of elements in distribution for "discrete" type or number of intervals of piecewise-linear density for "continuous" type.

If pdqr-function has "discrete" type and exactly two possible values 0 and 1, it is treated as "boolean" pdqr-function and probability of 1 is shown. This is done to simplify interactive work with output of comparing functions like

`>=`

, etc. (see description of methods for S3 group generic functions). To extract probabilities from "boolean" pdqr-function, use`summ_prob_true()`

and`summ_prob_false()`

.

Symbol "~" in `print()`

output indicates that printed value or support is an
approximation to a true one (for readability purpose).

Other pdqr methods for generic functions:
`methods-group-generic`

,
`methods-plot`

```
#> Probability mass function of discrete type
#> Support: [1, 10] (10 elements)#> Random generation function of continuous type
#> Support: [0, 1] (250 intervals)#> Random generation function of discrete type
#> Support: [0, 1] (2 elements, probability of 1: 0.7)
```