util_bernoulli_param_estimate: Estimate Bernoulli Parameters

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

Estimate Bernoulli Parameters

Description

This function will attempt to estimate the Bernoulli prob parameter 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 Bernoulli data.

Usage

util_bernoulli_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 prob parameter of a Bernoulli distribution.

Value

A tibble/list

Author(s)

Steven P. Sanderson II, MPH

See Also

Other Parameter Estimation: 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_burr_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 Bernoulli: tidy_bernoulli(), util_bernoulli_stats_tbl()

Examples

library(dplyr)
library(ggplot2)

tb <- tidy_bernoulli(.prob = .1) |> pull(y)
output <- util_bernoulli_param_estimate(tb)

output$parameter_tbl

output$combined_data_tbl |>
  tidy_combined_autoplot()

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