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random_wilcox_walk() to
generate a random walk using the Wilcoxon signed-rank test.random_weibull_walk() to
generate a random walk using the Weibull distribution.random_uniform_walk() to
generate a random walk using the Uniform distribution.random_t_walk() to generate a
random walk using the Student’s t-distribution.random_smirnov_walk() to
generate a random walk using the Smirnov distribution.random_wilcoxon_sr_walk() to
generate a random walk using the Wilcoxon signed-rank test with a
specified number of steps.random_poisson_walk() to
generate a random walk using the Poisson distribution.random_negbinomial_walk() to
generate a random walk using the Negative Binomial distribution.random_multinomial_walk() to
generate a random walk using the Multinomial distribution.random_logistic_walk() to
generate a random walk using the Logistic distribution.random_lognormal_walk() to
generate a random walk using the Log-Normal distribution.random_hypergeometric_walk() to
generate a walk using the Hypergeometric distribution.random_geometric_walk() to
generate a random walk using the geometric distribution.random_f_walk() to generate a
random walk using the F-distribution.random_chisquared_walk() to
generate a random walk using the Chi-Squared distribution.random_binomial_walk() to
generate a random walk using the Binomial distribution.random_gamma_walk() to generate
a random walk using the Gamma distribution.random_exponential_walk() to
generate a random walk using the Exponential distribution.random_cauchy_walk() to
generate a random walk using the Cauchy distribution.random_beta_walk() to generate
a random walk using the Beta distribution.random_displacement_walk() to
generate a random walk using a custom displacement function.subset_walks() to allow for a new
parameter of .value to specify the column to subset by. It
defaults to “y”visualize_walks() to allow
.pluck to accept a vector of column names to pluck multiple
graphs.x column
is now called step_number for all random walk functions
including rw30(). The x column is now the first dimension
of a 2D/3D random walk.rand_walk_column_names() to generate column names for
random walks.confidence_interval() to
generate confidence interval tibble..dimensions parameter to random walk
functions to allow for the generation of random walks with up to 3
dimensions!https://www.spsanderson.com/steveondata/posts/2025-05-09/
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std_cum_sum_augment() to
calculate the cumulative sum of a random walk.std_cum_prod_augment() to
calculate the cumulative product of a random walk.std_cum_min_augment() to
calculate the cumulative minimum of a random walk.std_cum_max_augment() to
calculate the cumulative maximum of a random walk.std_cum_mean_augment() to
calculate the cumulative mean of a random walk.get_attributes() to get
attributes without the row.namesrunning_quantile() to calculate
the running quantile of a given vector..interactive parameter to
visualize_walks() to allow for interactive plots..pluck parameter to
visualize_walks() to allow for plucking of specific graph
of walks.https://www.spsanderson.com/steveondata/posts/2024-10-24/
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rw30() to generate 30 random
walks of 100 steps eachgeometric_brownian_motion() to
generate Geometric Brownian Motionrandom_normal_drift_walk() to
generate Random Walk with Driftbrownian_motion() to generate
Brownian Motionrandom_normal_walk() to generate
Random Walkdiscrete_walk() to generate
Discrete Random Walkinternal_rand_walk_helper() to
help generate common columns for random walks.euclidean_distance() to
calculate the Euclidean distance of a random walk.visualize_walks() to visualize
random walks.summarize_walks() to summarize
random walks.None
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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