Nam Seok Kim
() and Yusak O. Susilo
Nam Seok Kim: The Korea Transport Institute
Yusak O. Susilo: KTH, Postal: Centrum för Transportstudier (CTS), Teknikringen 10, 100 44 Stockholm, Sweden
Abstract: Using Poisson regression and negative binomial regression, this paper presents an empirical comparison of four different regression models for the estimation of pedestrian demand at the regional level and finds the most appropriate model with reference to the National Household Travel Survey (NHTS) 2001 data for the Baltimore (USA) region. The results show that Poisson regression seems to be more appropriate for pedestrian trip generation modeling in terms of x2 ratio test, Pseudo R2, and Akaike’s information criterion (AIC). However, R2 based on deviance residuals and estimated log-likelihood value at convergence confirmed the empirical studies that negative binomial regression is more appropriate for the over-dispersed dependent variable than Poisson regression.
23 pages, September 25, 2013
Note: Published as: Kim, N.S. and Susilo, Y.O. (2013) Comparison of pedestrian trip generation models. Journal of Advanced Transportation, Vol. 47 (4), pp. 399–412. DOI: 10.1002/atr.166
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