util_lognormal_param_estimate: Estimate Lognormal Parameters

View source: R/est-param-lognormal.R

util_lognormal_param_estimateR Documentation

Estimate Lognormal Parameters

Description

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 lognormal data.

Three different methods of shape parameters are supplied:

  • mme, see EnvStats::elnorm()

  • mle, see EnvStats::elnorm()

Usage

util_lognormal_param_estimate(.x, .auto_gen_empirical = TRUE)

Arguments

.x

The vector of data to be passed to the function.

.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 attempt to estimate the lognormal meanlog and log sd parameters given some vector of values.

Value

A tibble/list

Author(s)

Steven P. Sanderson II, MPH

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_exponential_param_estimate(), util_gamma_param_estimate(), util_geometric_param_estimate(), util_hypergeometric_param_estimate(), util_logistic_param_estimate(), util_negative_binomial_param_estimate(), util_normal_param_estimate(), util_pareto_param_estimate(), util_poisson_param_estimate(), util_uniform_param_estimate(), util_weibull_param_estimate()

Other Lognormal: tidy_lognormal(), util_lognormal_stats_tbl()

Examples

library(dplyr)
library(ggplot2)

x <- mtcars$mpg
output <- util_lognormal_param_estimate(x)

output$parameter_tbl

output$combined_data_tbl %>%
  tidy_combined_autoplot()

tb <- tidy_lognormal(.meanlog = 2, .sdlog = 1) %>% pull(y)
util_lognormal_param_estimate(tb)$parameter_tbl


TidyDensity documentation built on Nov. 2, 2023, 5:38 p.m.