The goal of TidyDensity is to make working with random numbers from different distributions easy. All tidy_
distribution functions provide the following components:
- [
r_
] - [
d_
] - [
q_
] - [
p_
]
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")