random_steps: Generate Random Steps

Description

Function to generate a given number of random steps for each observed step.

Usage

random_steps(x, ...)
# S3 method for numeric
random_steps(
  x,
  n_control = 10,
  angle = 0,
  rand_sl = random_numbers(make_exp_distr(), n = 1e+05),
  rand_ta = random_numbers(make_unif_distr(), n = 1e+05),
  ...
)
# S3 method for steps_xy
random_steps(
  x,
  n_control = 10,
  sl_distr = fit_distr(x$sl_, "gamma"),
  ta_distr = fit_distr(x$ta_, "vonmises"),
  rand_sl = random_numbers(sl_distr, n = 1e+05),
  rand_ta = random_numbers(ta_distr, n = 1e+05),
  include_observed = TRUE,
  start_id = 1,
  ...
)
# S3 method for bursted_steps_xyt
random_steps(
  x,
  n_control = 10,
  sl_distr = fit_distr(x$sl_, "gamma"),
  ta_distr = fit_distr(x$ta_, "vonmises"),
  rand_sl = random_numbers(sl_distr, n = 1e+05),
  rand_ta = random_numbers(ta_distr, n = 1e+05),
  include_observed = TRUE,
  ...
)

Value

A tibble of class random_steps.

Arguments

x: Steps.
...: Further arguments, none implemented.
n_control: [integer(1)=10]{>1}
The number of control steps paired with each observed step.
angle: [numeric(1) = 0]{-pi < rel_angle < pi}
Angle for the first step.
rand_sl: [numeric]
Numeric vector with random step lengths an animal can make. This will usually be random numbers drawn from a suitable distribution (e.g., gamma or exponential).
rand_ta: [numeric]
Numeric vector with relative turning angles an animal can make. This will usually be random numbers drawn from a suitable distribution (e.g., von Mises or uniform).
sl_distr: [amt_distr]
The step-length distribution.
ta_distr: [amt_distr]
The turn-angle distribution.
include_observed: [logical(1) = TRUE]
Indicates if observed steps are to be included in the result.
start_id: integer Index where the numbering for step ids start.