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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.

Value

A tibble/list

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.

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)
library(ggplot2)

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

output$parameter_tbl
#> # A tibble: 1 × 8
#>   dist_type samp_size   min   max  mean variance sum_x  prob
#>   <chr>         <int> <dbl> <dbl> <dbl>    <dbl> <dbl> <dbl>
#> 1 Bernoulli        50     0     1  0.08   0.0736     4  0.08

output$combined_data_tbl |>
  tidy_combined_autoplot()