Visualise the distribution of a single parameter

This function plots the distribution of a single parameter.

Usage

vis_1_param(
  df,
  param = NULL,
  binwidth = NULL,
  type = "histogram",
  dist = c("lnorm", "norm", "beta"),
  user_dist = NULL,
  user_param_1 = NULL,
  user_param_2 = NULL,
  user_mean = NULL
)

Arguments

df: a dataframe.
param: character. Name of variable of the dataframe for which the distribution should be plotted.
binwidth: numeric. Determine the width of the bins to use, only applied in combination with "histogram". Default is 30 bins.
type: character. Determine which plot to return: "histogram" for a histogram, "density" for a density plot. Default is "histogram".
dist: character or vector of character. Determine which distribution to fit on the density plot.
user_dist: character string. User-defined distribution to fit. Default value is NULL.
user_param_1: character string. First parameter of the user-defined distribution to fit.
user_param_2: character string. Second parameter of the user-defined distribution to fit.
user_mean: numeric value. mean value to plot on the graph. Default is NULL

Value

A ggplot graph.

Details

The available distributions are: "norm" (normal), "beta", "gamma", "lnorm" (lognormal). TO CHECK --> ask for mean and SD/SE for the user-defined distribution???

Examples

# Generating histogram using the example dataframe for the costs of progression-free health state, and bins of 50 euros.
data(df_pa)
vis_1_param(df = df_pa, param = "c_pfs", binwidth = 50)
#> Error in computing default starting values.
#> Error in manageparam(start.arg = start, fix.arg = fix.arg, obs = data,     distname = distname): Error in startargdefault(obs, distname) : 
#>   values must be in [0-1] to fit a beta distribution