Sen, A. (1986), "Maximum likelihood estimation of gravity model parameters," Journal of Regional Science, 26, 461-474. Home/Search Document Not in Database Summary Related Articles Check |
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Statistical Inference For Gravity Models In Transportation Flow.. - West (1994) (1 citation) (Correct)
....in the transportation research community, so this paper serves, in part, to introduce and exemplify Bayesian inference in an accessible disciplinary context. 2. MODELS FOR ZONE FLOWS The cornerstone of gravity modelling is the class of Poisson log linear models for zone to zone traffic flows (Sen, 1986; Smith, 1987) Label the geographic zones of the area under study as 1; n; and consider a specified period of the day during which zone to zone trips arise at an assumedly constant rate. Write y ij for the number of trips from origin zone i to destination zone j in the period; assume, ....
....model simply by inferences on which of the h ij are reasonably close to unity, and which are significantly larger than unity, respectively. Previous works on inference in gravity models have developed maximum likelihood, and related, approaches to estimation of the a i ; b j and g parameters (Sen, 1986; Smith, 1987) Here, in the context of the elaborated model, Bayesian inference is developed, to both extend and complement other approaches. In particular, Bayesian analysis as developed here delivers not only point estimates of all parameters, but accessible posterior distributions for these ....
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Sen, A. (1986) Maximum likelihood estimation of gravity model parameters, Journal of Regional Science, 26, 461-474.
Bayesian Inference on Network Traffic Using Link Count Data - Tebaldi, West (1996) (28 citations) (Correct)
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Sen, A. (1986), "Maximum likelihood estimation of gravity model parameters," Journal of Regional Science, 26, 461-474.
Bayesian Analysis Of Network Flow Problems - Tebaldi (1997) (Correct)
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Sen, A. (1986), Maximum likelihood estimation of gravity model parameters. Journal of Regional Science, 26, 461-474.
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