ARPobservation: ARPobservation

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Tools for simulating different methods of observing alternating renewal processes


ARPobservation provides a set of tools for simulating data based on direct observation of behavior. It works by first simulating a behavior stream based on an alternating renewal process, using specified distributions of event durations and interim times. Different procedures for recording data can then be applied to the simulated behavior stream.

The main function for simulating a behavior stream is r_behavior_stream. Currently, the event duration and interim time distributions must come from the class eq_dist. (See the documentation for this class for distributions that are currently implemented.)

Several different observation recording procedures can then be applied as filters to a simulated behavior stream. The following procedures are currently implemented:

To apply multiple procedures to the same behavior stream, use reported_observations. Data can also be simulated using the convenience functions r_PIR, r_WIR, r_MTS, r_continuous_recording, and r_event_counting. These functions wrap the behavior-stream generation step and the observation recording step into a single function. They are more memory efficient, but slightly less computationally efficient, than executing each step in turn.


James E. Pustejovsky <>

ARPobservation documentation built on May 1, 2021, 1:08 a.m.