Orbital Decomposition for Ill-Behaved Event-Sequences: Transients and Superordinate Structures

Authors

Stephen J. Guastello, Marquette UniversityFollow
Anthony F. Peressini, Marquette UniversityFollow
Robert W. Bond, Marquette UniversityFollow

Document Type

Article

Language

eng

Format of Original

12 p.

Publication Date

2011

Publisher

Society for Chaos Theory in Psychology & Life Sciences

Source Publication

Nonlinear Dynamics, Psychology, and Life Sciences

Source ISSN

1090-0578

Abstract

Time series analysis is often challenged by the presence of transient functions. We examined some types of transients found in time series of events that lend themselves to symbolic dynamics analysis through the method of orbital decomposition, which is based on the principle that chaotic series arise from coupled oscillators. Synthetic data sets were constructed to study the impact of intrusive events, intrusive series, merged functions, non-coupled oscillators, and driving oscillations on the patterns of final statistics obtained from orbital decomposition analysis. Two real-world data sets - a logbook of the ritual behaviors of a patient with obsessive compulsive disorder and a time series of kill dates from an infamous serial murderer - were examined for non-ergodic properties similar to those found in the synthetic data.

Comments

Nonlinear dynamics, psychology, and life sciences, Volume 15, No. 4: pp 465-476 (2011). Permalink: http://www.societyforchaostheory.org/ndpls/show_issues.cgi?vol=15

Recommended Citation

Guastello, Stephen J.; Peressini, Anthony F.; and Bond, Robert W., "Orbital Decomposition for Ill-Behaved Event-Sequences: Transients and Superordinate Structures" (2011). Psychology Faculty Research and Publications. 45.
https://epublications.marquette.edu/psych_fac/45