Comparing Two Sets of Time-Series: The State Similarity Measure

• Activity Number: 485
• Type: Invited
• Date/Time: Wednesday, August 4, 2010 : 10:30 AM to 12:20 PM
• Sponsor: Section on Statistics and Marketing
• Author(s): Robert E. Marks*+
• Companies: University of New South Wales
• Keywords: time-series sets ; comparison ; State Similarity Measure ; dynamic responses

Abstract

Static estimation treats variation in the dependent data as noise, or error. In simulations using agent-based models, however -- especially with dynamic responses -- such variation in the simulated output may possess valuable information from the simulation. We explore previous methods of estimating simulation models, before examining the simulated output from an early agent-based model in marketing, and asking whether these methods or others allow the modeller to conclude with some degree of confidence that the simulated output is generated by essentially the same process that generated the historical output. We introduce a new measure, the State Similarity Measure (SSM), to measure the distance between two sets of time-series that embody dynamic responses.