Criteria for selecting model updating methods for better temporal transferability
| Autor: | Nobuhiro Sanko |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
050210 logistics & transportation
Discrete choice 05 social sciences Transferability 0211 other engineering and technologies General Engineering 021107 urban & regional planning Transportation 02 engineering and technology computer.software_genre Geography Model updating data collection time points number of observations temporal transferability 0502 economics and business Data mining repeated cross-sectional data computer |
| Zdroj: | Transportmetrica A: Transport Science. 16:1310-1332 |
| ISSN: | 2324-9943 2324-9935 |
| Popis: | When older and more recent datasets have large and small numbers of observations, respectively, then discrete choice modellers must decide whether to utilise both datasets with model updating (transfer scaling, joint context estimation, Bayesian updating, and combined transfer estimation) or only the more recent dataset. This study investigates the case when the data collection time points and the number of observations from each time point differ. Bootstrapping was applied to commuting mode choice models utilising datasets from Nagoya, Japan. The following criteria are proposed: (1) when the more recent time point has a large number of observations, use only the more recent data; (2) when the more recent time point has a smaller number of observations, use transfer scaling or joint context estimation based on the differences in the contexts of the two time points and the sample size from the older time point. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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