Returns distribution statistics in a tibble.
Details
This function will take in a tibble and returns the statistics
of the given type of tidy_
distribution. It is required that data be
passed from a tidy_
distribution function.
See also
Other Pareto:
tidy_generalized_pareto()
,
tidy_inverse_pareto()
,
tidy_pareto()
,
tidy_pareto1()
,
util_pareto1_aic()
,
util_pareto1_param_estimate()
,
util_pareto1_stats_tbl()
,
util_pareto_param_estimate()
Other Distribution Statistics:
util_bernoulli_stats_tbl()
,
util_beta_stats_tbl()
,
util_binomial_stats_tbl()
,
util_burr_stats_tbl()
,
util_cauchy_stats_tbl()
,
util_chisquare_stats_tbl()
,
util_exponential_stats_tbl()
,
util_f_stats_tbl()
,
util_gamma_stats_tbl()
,
util_generalized_beta_stats_tbl()
,
util_generalized_pareto_stats_tbl()
,
util_geometric_stats_tbl()
,
util_hypergeometric_stats_tbl()
,
util_inverse_burr_stats_tbl()
,
util_inverse_pareto_stats_tbl()
,
util_inverse_weibull_stats_tbl()
,
util_logistic_stats_tbl()
,
util_lognormal_stats_tbl()
,
util_negative_binomial_stats_tbl()
,
util_normal_stats_tbl()
,
util_paralogistic_stats_tbl()
,
util_pareto1_stats_tbl()
,
util_poisson_stats_tbl()
,
util_t_stats_tbl()
,
util_triangular_stats_tbl()
,
util_uniform_stats_tbl()
,
util_weibull_stats_tbl()
,
util_zero_truncated_binomial_stats_tbl()
,
util_zero_truncated_geometric_stats_tbl()
,
util_zero_truncated_negative_binomial_stats_tbl()
,
util_zero_truncated_poisson_stats_tbl()
Examples
library(dplyr)
tidy_pareto() |>
util_pareto_stats_tbl() |>
glimpse()
#> Rows: 1
#> Columns: 17
#> $ tidy_function <chr> "tidy_pareto"
#> $ function_call <chr> "Pareto c(10, 0.1)"
#> $ distribution <chr> "Pareto"
#> $ distribution_type <chr> "continuous"
#> $ points <dbl> 50
#> $ simulations <dbl> 1
#> $ mean <dbl> 0.1111111
#> $ mode_lower <dbl> 0.1
#> $ range <chr> "0 to Inf"
#> $ std_dv <dbl> 0.0124226
#> $ coeff_var <dbl> 0.000154321
#> $ skewness <dbl> 2.811057
#> $ kurtosis <dbl> 14.82857
#> $ computed_std_skew <dbl> 2.313421
#> $ computed_std_kurt <dbl> 9.375681
#> $ ci_lo <dbl> 0.0003162781
#> $ ci_hi <dbl> 0.04447684