TidyDensity

CRAN_Status_Badge Lifecycle: stable PRs Welcome

The goal of {TidyDensity} is to make working with random numbers from different distributions easy. All tidy_ distribution functions provide the following components:

Installation

You can install the released version of {TidyDensity} from CRAN with:

install.packages("TidyDensity")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("spsanderson/TidyDensity")

Example

This is a basic example which shows you how to solve a common problem:

library(TidyDensity)
library(dplyr)
library(ggplot2)

tidy_normal()
#> # A tibble: 50 × 7
#>    sim_number     x       y    dx       dy     p        q
#>    <fct>      <int>   <dbl> <dbl>    <dbl> <dbl>    <dbl>
#>  1 1              1  2.01   -2.88 0.000255 0.5   Inf     
#>  2 1              2 -0.636  -2.76 0.000670 0.508  -0.512 
#>  3 1              3 -0.317  -2.64 0.00159  0.516  -0.284 
#>  4 1              4 -0.319  -2.51 0.00339  0.524  -0.285 
#>  5 1              5  1.01   -2.39 0.00661  0.533   0.631 
#>  6 1              6 -0.0143 -2.27 0.0118   0.541  -0.0809
#>  7 1              7 -0.431  -2.15 0.0197   0.549  -0.363 
#>  8 1              8  0.430  -2.03 0.0309   0.557   0.214 
#>  9 1              9  0.504  -1.90 0.0464   0.565   0.264 
#> 10 1             10 -1.18   -1.78 0.0675   0.573  -0.993 
#> # … with 40 more rows

An example plot of the tidy_normal data.

tn <- tidy_normal(.n = 100, .num_sims = 6)

tidy_autoplot(tn, .plot_type = "density")

tidy_autoplot(tn, .plot_type = "quantile")

tidy_autoplot(tn, .plot_type = "probability")

tidy_autoplot(tn, .plot_type = "qq")

We can also take a look at the plots when the number of simulations is greater than nine. This will automatically turn off the legend as it will become too noisy.

tn <- tidy_normal(.n = 100, .num_sims = 20)

tidy_autoplot(tn, .plot_type = "density")

tidy_autoplot(tn, .plot_type = "quantile")

tidy_autoplot(tn, .plot_type = "probability")

tidy_autoplot(tn, .plot_type = "qq")