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_number
The current simulation number.x
The current value ofn
for the current simulation.y
The randomly generated data point.dx
Thex
value from thestats::density()
function.dy
They
value from thestats::density()
function.p
The values from the resulting p_ function of the distribution family.q
The 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.
- .return_tibble
A logical value indicating whether to return the result as a tibble. Default is TRUE.
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_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
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 × 6
#> sim_number x y dx dy p
#> <fct> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.100 -0.302 0.00433 0.100
#> 2 1 2 0.0332 -0.259 0.0148 0.0332
#> 3 1 3 0.0908 -0.217 0.0435 0.0908
#> 4 1 4 0.230 -0.174 0.110 0.230
#> 5 1 5 0.312 -0.132 0.242 0.312
#> 6 1 6 0.431 -0.0896 0.461 0.431
#> 7 1 7 0.178 -0.0472 0.764 0.178
#> 8 1 8 0.480 -0.00481 1.11 0.480
#> 9 1 9 1.13 0.0376 1.42 1.13
#> 10 1 10 1.15 0.0800 1.62 1.15
#> # ℹ 40 more rows