Tidy Randomly Generated Zero Truncated Poisson Distribution Tibble
Source:R/random-tidy-zero-truc-poisson.R
tidy_zero_truncated_poisson.RdThis function will generate n random points from a Zero Truncated
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_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.
- .lambda
A vector of non-negative means.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying actuar::rztpois(), and its underlying
p, d, and q functions. For more information please see actuar::rztpois()
See also
https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html
Other Poisson:
tidy_poisson(),
util_poisson_param_estimate(),
util_poisson_stats_tbl()
Other Zero Truncated Distribution:
tidy_zero_truncated_binomial(),
tidy_zero_truncated_geometric()
Other Discrete Distribution:
tidy_bernoulli(),
tidy_binomial(),
tidy_hypergeometric(),
tidy_negative_binomial(),
tidy_poisson(),
tidy_zero_truncated_binomial(),
tidy_zero_truncated_negative_binomial()
Examples
tidy_zero_truncated_poisson()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <int> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1 0.0786 0.00642 0.582 1
#> 2 1 2 2 0.177 0.0160 0.873 2
#> 3 1 3 1 0.276 0.0358 0.582 1
#> 4 1 4 3 0.375 0.0725 0.970 3
#> 5 1 5 2 0.474 0.132 0.873 2
#> 6 1 6 3 0.573 0.218 0.970 3
#> 7 1 7 2 0.672 0.323 0.873 2
#> 8 1 8 1 0.770 0.433 0.582 1
#> 9 1 9 2 0.869 0.522 0.873 2
#> 10 1 10 1 0.968 0.570 0.582 1
#> # … with 40 more rows