util_inverse_burr_param_estimate: Estimate Inverse Burr Parameters

In TidyDensity: Functions for Tidy Analysis and Generation of Random Data

Estimate Inverse Burr Parameters

Description

This function will attempt to estimate the inverse Burr shape1, shape2, and rate parameters given some vector of values .x. The function will return a list output by default, and if the parameter .auto_gen_empirical is set to TRUE then the empirical data given to the parameter .x will be run through the tidy_empirical() function and combined with the estimated inverse Burr data.

Usage

util_inverse_burr_param_estimate(.x, .auto_gen_empirical = TRUE)

Arguments

.x	The vector of data to be passed to the function. Must be non-negative integers.
.auto_gen_empirical	This is a boolean value of TRUE/FALSE with default set to TRUE. This will automatically create the tidy_empirical() output for the .x parameter and use the tidy_combine_distributions(). The user can then plot out the data using ⁠$combined_data_tbl⁠ from the function output.

Details

This function will see if the given vector .x is a numeric vector. It will attempt to estimate the shape1, shape2, and rate parameters of an inverse Burr distribution.

Value

A tibble/list

See Also

Other Parameter Estimation: util_bernoulli_param_estimate(), util_beta_param_estimate(), util_binomial_param_estimate(), util_burr_param_estimate(), util_cauchy_param_estimate(), util_chisquare_param_estimate(), util_exponential_param_estimate(), util_f_param_estimate(), util_gamma_param_estimate(), util_generalized_beta_param_estimate(), util_generalized_pareto_param_estimate(), util_geometric_param_estimate(), util_hypergeometric_param_estimate(), util_inverse_pareto_param_estimate(), util_inverse_weibull_param_estimate(), util_logistic_param_estimate(), util_lognormal_param_estimate(), util_negative_binomial_param_estimate(), util_normal_param_estimate(), util_paralogistic_param_estimate(), util_pareto1_param_estimate(), util_pareto_param_estimate(), util_poisson_param_estimate(), util_t_param_estimate(), util_triangular_param_estimate(), util_uniform_param_estimate(), util_weibull_param_estimate(), util_zero_truncated_binomial_param_estimate(), util_zero_truncated_geometric_param_estimate(), util_zero_truncated_negative_binomial_param_estimate(), util_zero_truncated_poisson_param_estimate()

Other Inverse Burr: util_inverse_burr_stats_tbl()

Examples

library(dplyr)
library(ggplot2)

set.seed(123)
tb <- tidy_burr(.shape1 = 1, .shape2 = 2, .rate = .3) |> pull(y)
output <- util_inverse_burr_param_estimate(tb)

output$parameter_tbl

output$combined_data_tbl |>
  tidy_combined_autoplot()

TidyDensity documentation built on May 29, 2024, 11:06 a.m.