r_event_counting: Generates random samples of event counts

In ARPobservation: Tools for Simulating Direct Behavioral Observation Recording Procedures Based on Alternating Renewal Processes

Generates random samples of event counts

Description

Random generation of behavior streams (based on an alternating renewal process) of a specified length and with specified mean event durations, mean interim times, event distribution, and interim distribution, summarized as the the total number of behaviors that began during the recording session

Usage

r_event_counting(
  n,
  mu,
  lambda,
  stream_length,
  F_event,
  F_interim,
  equilibrium = TRUE,
  p0 = 0,
  tuning = 2
)

Arguments

n	number of behavior streams to generate
mu	mean event duration
lambda	mean interim time
stream_length	length of behavior stream
F_event	distribution of event durations. Must be of class eq_dist.
F_interim	distribution of interim times. Must be of class eq_dist.
equilibrium	logical; if TRUE, then equilibrium initial conditions are used; if FALSE, then p0 is used to determine initial state and normal generating distributions are used for event durations and interim times.
p0	Initial state probability. Only used if equilibrium = FALSE, in which case default is zero (i.e., behavior stream always starts with an interim time).
tuning	controls the size of the chunk of random event durations and interim times. Adjusting this may be useful in order to speed computation time .

Details

Generates behavior streams by repeatedly drawing random event durations and random interim times from the distributions as specified, until the sum of the durations and interim times exceeds the requested stream length. Then applies an event counting filter to the generated behavior streams.

Value

A vector of behavior counts of length n.

Author(s)

Daniel Swan <[e-mail]>

Examples

r_event_counting(n = 5, mu = 2, lambda = 4, stream_length = 20,
                     F_event = F_exp(), F_interim = F_exp())
                     

ARPobservation documentation built on Aug. 25, 2023, 5:19 p.m.