This function will generate n
random points from a Poisson
distribution with a user provided, .lambda
, 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.
- .lambda
A vector of non-negative means.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying stats::rpois()
, and its underlying
p
, d
, and q
functions. For more information please see stats::rpois()
See also
https://r-coder.com/poisson-distribution-r/
https://en.wikipedia.org/wiki/Poisson_distribution
Other Poisson:
tidy_zero_truncated_poisson()
,
util_poisson_param_estimate()
,
util_poisson_stats_tbl()
Other Discrete Distribution:
tidy_bernoulli()
,
tidy_binomial()
,
tidy_hypergeometric()
,
tidy_negative_binomial()
,
tidy_zero_truncated_binomial()
,
tidy_zero_truncated_negative_binomial()
,
tidy_zero_truncated_poisson()
Examples
tidy_poisson()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 2 -0.912 0.00502 0.920 2
#> 2 1 2 0 -0.813 0.0126 0.368 0
#> 3 1 3 0 -0.715 0.0283 0.368 0
#> 4 1 4 1 -0.616 0.0574 0.736 1
#> 5 1 5 1 -0.518 0.105 0.736 1
#> 6 1 6 1 -0.420 0.172 0.736 1
#> 7 1 7 0 -0.321 0.256 0.368 0
#> 8 1 8 1 -0.223 0.342 0.736 1
#> 9 1 9 2 -0.124 0.411 0.920 2
#> 10 1 10 1 -0.0258 0.447 0.736 1
#> # … with 40 more rows