Accommodating Correlation Across Days in Multiple-Discrete Continuous Models for Activity Scheduling: Estimation and Forecasting Considerations

The MDCEV modelling framework has established itself as a preferred method for modelling time allocation, with data very often coming from travel or activity diaries. However, standard implementations fail to recognise that fact that many of these datasets contain information on multiple days for the same individual, with possible substitution between days. The authors discuss how the theoretical accommodation of these effects is not straightforward, especially with budget constraints at the day and multi-day level. They instead rely on additive utility functions where they accommodate correlation between activities at the within-day and between-day level using a mixed MDCEV model, with multi-variate random distributions. They authors put forward adaptations of the standard forecasting approach for MDCEV to allow them to make links across days also in model application. They illustrate the issue and the methods using two different time use datasets, confirming their theoretical points and highlighting the benefits of allowing for correlation across days in estimation and substitution in forecasting.

• Supplemental Notes:
  • This paper was sponsored by TRB committee ADB40 Standing Committee on Transportation Demand Forecasting.
• Authors:
  • Calastri, Chiara
  • Hess, Stephane
  • Pinjari, Abdul Rawoof
  • Daly, Andrew
• Conference:
  • Transportation Research Board 97th Annual Meeting
  • Location: Washington DC, United States
  • Date: 2018-1-7 to 2018-1-11
• Date: 2018

Language

• English

Media Info

• Media Type: Digital/other
• Features: References; Tables;
• Pagination: 19p

Subject/Index Terms

• TRT Terms: Activity choices; Estimating; Forecasting; Mathematical models; Scheduling
• Uncontrolled Terms: Multiple discrete continuous extreme value model
• Subject Areas: Planning and Forecasting; Transportation (General);

Filing Info

• Accession Number: 01661400
• Record Type: Publication
• Report/Paper Numbers: 18-05677
• Files: TRIS, TRB, ATRI
• Created Date: Feb 27 2018 9:45AM