A New Approach to Specify and Estimate Non-Normally Mixed Multinomial Probit Models
dc.creator | Bhat, Chandra R. | en |
dc.creator | Sidharthan, Raghuprasad | en |
dc.date.accessioned | 2013-08-23T15:16:03Z | en |
dc.date.available | 2013-08-23T15:16:03Z | en |
dc.date.issued | 2012 | en |
dc.description.abstract | The current paper proposes the use of the multivariate skew-normal distribution function to accommodate non-normal mixing in cross-sectional and panel multinomial probit (MNP) models. The combination of skew-normal mixing and the MNP kernel lends itself nicely to estimation using Bhat’s (2011) maximum approximate composite marginal likelihood (MACML) approach. Simulation results for the cross-sectional case show that our proposed approach does well in recovering the underlying parameters, and also highlights the pitfalls of ignoring non-normality of the continuous mixing distribution when such non-normality is present. At the same time, the proposed model obviates the need to assume a pre-specified parametric distribution for the mixing, and allows the estimation of a very flexible, but still parsimonious, mixing distribution form. | en |
dc.description.department | Civil, Architectural, and Environmental Engineering | en |
dc.identifier.citation | Bhat, C.R., and R. Sidharthan (2012), "A New Approach to Specify and Estimate Non-Normally Mixed Multinomial Probit Models,"Transportation Research Part B, Vol. 46, No. 7, pp. 817-833. | en |
dc.identifier.issn | 0191-2615 | en |
dc.identifier.uri | http://hdl.handle.net/2152/21110 | en |
dc.language.iso | eng | en |
dc.publisher | Elsevier | en |
dc.source.uri | http://www.journals.elsevier.com/transportation-research-part-b-methodological/ | en |
dc.subject | multinomial probit | en |
dc.subject | mixed models | en |
dc.subject | maximum approximate composite marginal likelihood | en |
dc.subject | maximum simulated likelihood | en |
dc.subject | multivariate skew-normal distribution | en |
dc.title | A New Approach to Specify and Estimate Non-Normally Mixed Multinomial Probit Models | en |
dc.type | Article | en |