The goal of RandomWalker is to allow users to easily create Random
Walks of different types that are compatible with the
tidyverse
suite of packages. The package is currently in
the experimental stage of development.
You can install the released version of {TidyDensity} from CRAN with:
install.packages("RandomWalker")
You can install the development version of RandomWalker from GitHub with:
# install.packages("devtools")
::install_github("spsanderson/RandomWalker") devtools
This is a basic example which shows you how to solve a common problem:
library(RandomWalker)
## basic example code
rw30() |>
head(10)
#> # A tibble: 10 × 3
#> walk_number x y
#> <fct> <int> <dbl>
#> 1 1 1 0
#> 2 1 2 1.52
#> 3 1 3 2.02
#> 4 1 4 1.82
#> 5 1 5 -0.120
#> 6 1 6 0.588
#> 7 1 7 0.412
#> 8 1 8 0.998
#> 9 1 9 1.37
#> 10 1 10 0.826
Here is a basic visualization of a Random Walk:
rw30() |>
visualize_walks()
Here is a basic summary of the random walks:
rw30() |>
summarize_walks(.value = y)
#> # A tibble: 1 × 16
#> fns fns_name dimensions mean_val median range quantile_lo quantile_hi
#> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 rw30 Rw30 1 -0.670 -0.132 47.4 -18.3 14.2
#> # ℹ 8 more variables: variance <dbl>, sd <dbl>, min_val <dbl>, max_val <dbl>,
#> # harmonic_mean <dbl>, geometric_mean <dbl>, skewness <dbl>, kurtosis <dbl>
rw30() |>
summarize_walks(.value = y, .group_var = walk_number)
#> # A tibble: 30 × 17
#> walk_number fns fns_name dimensions mean_val median range quantile_lo
#> <fct> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 rw30 Rw30 1 -0.951 0.0447 15.6 -10.5
#> 2 2 rw30 Rw30 1 -0.947 -2.02 13.5 -5.69
#> 3 3 rw30 Rw30 1 -2.91 -3.42 12.9 -8.84
#> 4 4 rw30 Rw30 1 -0.0432 0.299 11.1 -4.63
#> 5 5 rw30 Rw30 1 -4.28 -4.52 12.8 -9.94
#> 6 6 rw30 Rw30 1 -1.77 -1.71 14.6 -9.60
#> 7 7 rw30 Rw30 1 -3.51 -3.43 13.6 -9.47
#> 8 8 rw30 Rw30 1 -4.25 -3.94 20.1 -14.8
#> 9 9 rw30 Rw30 1 1.93 2.16 7.11 -1.46
#> 10 10 rw30 Rw30 1 0.621 1.20 13.7 -5.59
#> # ℹ 20 more rows
#> # ℹ 9 more variables: quantile_hi <dbl>, variance <dbl>, sd <dbl>,
#> # min_val <dbl>, max_val <dbl>, harmonic_mean <dbl>, geometric_mean <dbl>,
#> # skewness <dbl>, kurtosis <dbl>