
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.
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.
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_pareto1(),
tidy_pareto(),
tidy_t(),
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 0.541 -3.36 0.000925 0.351 0.541
#> 2 1 2 6.19 -2.54 0.00696 0.861 6.19
#> 3 1 3 1.16 -1.71 0.0318 0.538 1.16
#> 4 1 4 0.565 -0.891 0.0882 0.361 0.565
#> 5 1 5 0.947 -0.0693 0.155 0.486 0.947
#> 6 1 6 0.0751 0.753 0.183 0.0699 0.0751
#> 7 1 7 1.20 1.57 0.162 0.545 1.20
#> 8 1 8 1.69 2.40 0.126 0.628 1.69
#> 9 1 9 4.92 3.22 0.0922 0.831 4.92
#> 10 1 10 3.65 4.04 0.0635 0.785 3.65
#> # ℹ 40 more rows