ARPobservation package - RDocumentation

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ARPobservation provides a set of tools for simulating the sort of data generated during direct observation of a behavior over time. It works by first simulating a behavior stream based on an alternating renewal process, given specified distributions of event durations and interim times. The following distributions are currently supported:

Exponential
Gamma with fixed shape parameter
Mixture of two gammas
Weibull with fixed shape parameter
Uniform(0,x)
Constant (degenerate)

Different methods of recording data can then be applied to the simulated behavior stream. Functions are provided for the following recording methods:

continuous duration recording
event counting
momentary time sampling
partial interval recording
whole interval recording

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Version

Install

install.packages('ARPobservation')

Monthly Downloads

262

Version

1.2.2

License

GPL-3

Maintainer

James Pustejovsky

Last Published

August 25th, 2023

Functions in ARPobservation (1.2.2)

Moment estimator for prevalence and incidence, with bootstrap confidence intervals

interval_recording

Applies interval recording to a behavior stream

Calculate log-response ratio, variance, and confidence interval

Interim bounds and confidence interval

incidence_bounds

Incidence bounds and confidence interval

momentary_time_recording

Applies momentary time recording to a behavior stream

An interactive alternating renewal process simulator

r_continuous_recording

Generates random samples of continuously recorded behavior streams

Calculate log-likelihood

augmented_recording

Applies augmented interval recording to a behavior stream

plot.behavior_stream

Plot method for behavior_stream objects

continuous_duration_recording

Applies continuous duration recording to a behavior stream

Mixture of two gamma distributions and related equilibrium distribution

Generates random partial interval recording behavior streams

Generates random momentary time sampling behavior streams

Constructor for class eq_dist

Applies event counting to a behavior stream

Generates random whole interval recording behavior streams

Uniform distribution and related equilibrium distribution

r_behavior_stream

Generates random behavior streams

r_event_counting

Generates random samples of event counts

reported_observations

Applies multiple recording procedures to a behavior stream

prevalence_bounds

Prevalence bounds and confidence interval

Generates random augmented interval recording behavior streams

Exponential distribution and related equilibrium distribution

Gamma distribution and related equilibrium distribution

Moes(1998) data

Weibull distribution and related equilibrium distribution

Constant (degenerate) distribution and related equilibrium distribution

Dunlap et al.(1994) data