
Tidy Randomly Generated Paralogistic Distribution Tibble
Source:R/random-tidy-paralogistic.R
tidy_paralogistic.RdThis function will generate n random points from a paralogistic
distribution with a user provided, .shape, .rate, .scale and number of
random simulations to be produced. The function returns a tibble with the
simulation number column the x column which corresponds to the n randomly
generated points, the d_, p_ and q_ data points as well.
The data is returned un-grouped.
The columns that are output are:
sim_numberThe current simulation number.xThe current value ofnfor the current simulation.yThe randomly generated data point.dxThexvalue from thestats::density()function.dyTheyvalue from thestats::density()function.pThe values from the resulting p_ function of the distribution family.qThe values from the resulting q_ function of the distribution family.
Usage
tidy_paralogistic(
.n = 50,
.shape = 1,
.rate = 1,
.scale = 1/.rate,
.num_sims = 1,
.return_tibble = TRUE
)Arguments
- .n
The number of randomly generated points you want.
- .shape
Must be strictly positive.
- .rate
An alternative way to specify the
.scale- .scale
Must be strictly positive.
- .num_sims
The number of randomly generated simulations you want.
- .return_tibble
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Details
This function uses the underlying actuar::rparalogis(), and its underlying
p, d, and q functions. For more information please see actuar::rparalogis()
See also
https://en.wikipedia.org/wiki/Logistic_distribution
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
tidy_cauchy(),
tidy_chisquare(),
tidy_exponential(),
tidy_f(),
tidy_gamma(),
tidy_generalized_beta(),
tidy_generalized_pareto(),
tidy_geometric(),
tidy_inverse_burr(),
tidy_inverse_exponential(),
tidy_inverse_gamma(),
tidy_inverse_normal(),
tidy_inverse_pareto(),
tidy_inverse_weibull(),
tidy_logistic(),
tidy_lognormal(),
tidy_normal(),
tidy_pareto(),
tidy_pareto1(),
tidy_t(),
tidy_triangular(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Logistic:
tidy_logistic(),
util_logistic_param_estimate(),
util_logistic_stats_tbl()
Examples
tidy_paralogistic()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1.25 -2.49 0.000878 0.556 1.25
#> 2 1 2 1.34 -0.936 0.0615 0.573 1.34
#> 3 1 3 0.981 0.623 0.247 0.495 0.981
#> 4 1 4 2.70 2.18 0.149 0.730 2.70
#> 5 1 5 1.04 3.74 0.0599 0.510 1.04
#> 6 1 6 0.251 5.30 0.0371 0.200 0.251
#> 7 1 7 35.6 6.86 0.0101 0.973 35.6
#> 8 1 8 0.917 8.41 0.000610 0.478 0.917
#> 9 1 9 0.462 9.97 0.00770 0.316 0.462
#> 10 1 10 17.4 11.5 0.00459 0.946 17.4
#> # ℹ 40 more rows