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")
devtools::install_github("spsanderson/RandomWalker")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 0.826Here 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>