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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_]You can install the released version of {TidyDensity} from CRAN with:
And the development version from GitHub with:
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 0.227 -2.97 0.000238 0.590 0.227
#> 2 1 2 1.12 -2.84 0.000640 0.869 1.12
#> 3 1 3 1.26 -2.71 0.00153 0.897 1.26
#> 4 1 4 0.204 -2.58 0.00326 0.581 0.204
#> 5 1 5 1.04 -2.44 0.00620 0.852 1.04
#> 6 1 6 -0.180 -2.31 0.0106 0.429 -0.180
#> 7 1 7 0.299 -2.18 0.0167 0.618 0.299
#> 8 1 8 1.73 -2.04 0.0243 0.959 1.73
#> 9 1 9 -0.770 -1.91 0.0338 0.221 -0.770
#> 10 1 10 0.385 -1.78 0.0463 0.650 0.385
#> # ℹ 40 more rowsAn example plot of the tidy_normal data.
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.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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