This function will generate n random points from a gamma
distribution with a user provided, .shape, .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
This is strictly 0 to infinity.
- .scale
The standard deviation of the randomly generated data. This is strictly from 0 to infinity.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying stats::rgamma(), and its underlying
p, d, and q functions. For more information please see stats::rgamma()
See also
https://www.statology.org/fit-gamma-distribution-to-dataset-in-r/
https://en.wikipedia.org/wiki/Gamma_distribution
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
tidy_cauchy(),
tidy_chisquare(),
tidy_exponential(),
tidy_f(),
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_paralogistic(),
tidy_pareto1(),
tidy_pareto(),
tidy_t(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Gamma:
tidy_inverse_gamma(),
util_gamma_param_estimate(),
util_gamma_stats_tbl()
Examples
tidy_gamma()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.139 -0.228 0.00401 0.370 0.139
#> 2 1 2 0.0314 -0.201 0.0114 0.0993 0.0314
#> 3 1 3 0.623 -0.175 0.0289 0.875 0.623
#> 4 1 4 0.225 -0.148 0.0657 0.528 0.225
#> 5 1 5 0.370 -0.121 0.135 0.708 0.370
#> 6 1 6 0.114 -0.0945 0.250 0.315 0.114
#> 7 1 7 0.157 -0.0679 0.421 0.407 0.157
#> 8 1 8 0.00425 -0.0412 0.649 0.0141 0.00425
#> 9 1 9 0.0915 -0.0145 0.924 0.263 0.0915
#> 10 1 10 0.134 0.0122 1.22 0.360 0.134
#> # ℹ 40 more rows
