RandomWalker (version 1.1.0)

random_normal_drift_walk: Generate Multiple Random Walks with Drift

Description

This function generates a specified number of random walks, each consisting of a specified number of steps. The steps are generated from a normal distribution with a given mean and standard deviation. An additional drift term is added to each step to introduce a consistent directional component to the walks.

Usage

random_normal_drift_walk(
  .num_walks = 25,
  .n = 100,
  .mu = 0,
  .sd = 1,
  .drift = 0.1,
  .initial_value = 0,
  .dimensions = 1
)

Value

A tibble containing the generated random walks with columns depending on the number of dimensions:

• walk_number: Factor representing the walk number.

• step_number: Step index.

• y: If .dimensions = 1, the value of the walk at each step.

• x, y: If .dimensions = 2, the values of the walk in two dimensions.

• x, y, z: If .dimensions = 3, the values of the walk in three dimensions.

The following are also returned based upon how many dimensions there are and could be any of x, y and or z:

• cum_sum: Cumulative sum of dplyr::all_of(.dimensions).

• cum_prod: Cumulative product of dplyr::all_of(.dimensions).

• cum_min: Cumulative minimum of dplyr::all_of(.dimensions).

• cum_max: Cumulative maximum of dplyr::all_of(.dimensions).

• cum_mean: Cumulative mean of dplyr::all_of(.dimensions).

Arguments

.num_walks

Integer. The number of random walks to generate. Default is 25.

.n

Integer. The number of steps in each random walk. Default is 100.

.mu

Numeric. The mean of the normal distribution used for generating steps. Default is 0.

.sd

Numeric. The standard deviation of the normal distribution used for generating steps. Default is 1.

.drift

Numeric. The drift term to be added to each step. Default is 0.1.

.initial_value

A numeric value indicating the initial value of the walks. Default is 0.

.dimensions

The default is 1. Allowable values are 1, 2 and 3.

Author

Steven P. Sanderson II, MPH

Details

This function generates multiple random walks with a specified drift. Each walk is generated using a normal distribution for the steps, with an additional drift term added to each step.

See Also

Other Generator Functions: brownian_motion(), custom_walk(), discrete_walk(), double_pendulum_walk(), geometric_brownian_motion(), random_beta_walk(), random_binomial_walk(), random_cauchy_walk(), random_chisquared_walk(), random_displacement_walk(), random_exponential_walk(), random_f_walk(), random_gamma_walk(), random_geometric_walk(), random_hypergeometric_walk(), random_logistic_walk(), random_lognormal_walk(), random_multinomial_walk(), random_negbinomial_walk(), random_normal_walk(), random_poisson_walk(), random_smirnov_walk(), random_t_walk(), random_uniform_walk(), random_weibull_walk(), random_wilcox_walk(), random_wilcoxon_sr_walk()

Other Continuous Distribution: brownian_motion(), double_pendulum_walk(), geometric_brownian_motion(), random_beta_walk(), random_cauchy_walk(), random_chisquared_walk(), random_exponential_walk(), random_f_walk(), random_gamma_walk(), random_logistic_walk(), random_lognormal_walk(), random_normal_walk(), random_t_walk(), random_uniform_walk(), random_weibull_walk()

Examples

set.seed(123)
random_normal_drift_walk()

set.seed(123)
random_normal_drift_walk(.dimensions = 3) |>
  head() |>
  t()