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This function will attempt to estimate the gamma shape and scale parameters given some vector of values. 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 gamma data.

Usage

util_gamma_param_estimate(.x, .auto_gen_empirical = TRUE)

Arguments

.x

The vector of data to be passed to the function. Must be numeric.

.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.

Author

Steven P. Sanderson II, MPH

Examples

library(dplyr)
library(ggplot2)

tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y)
output <- util_gamma_param_estimate(tg)

output$parameter_tbl
#> # A tibble: 3 × 10
#>   dist_type samp_size    min   max  mean variance method shape scale shape_ratio
#>   <chr>         <int>  <dbl> <dbl> <dbl>    <dbl> <chr>  <dbl> <dbl>       <dbl>
#> 1 Gamma            50 0.0124  1.76 0.304    0.310 NIST_… 0.964 0.316        3.05
#> 2 Gamma            50 0.0124  1.76 0.304    0.310 EnvSt… 0.945 0.316        2.99
#> 3 Gamma            50 0.0124  1.76 0.304    0.310 EnvSt… 0.920 0.316        2.91

output$combined_data_tbl %>%
  tidy_combined_autoplot()