Computational methods for estimating multinomial, nested, and cross-nested logit models that account for semi-aggregate data.

MLA

Newman, Jeffrey P., et al. “Computational Methods for Estimating Multinomial, Nested, and Cross-Nested Logit Models That Account for Semi-Aggregate Data.” Journal of Choice Modelling, vol. 26, Mar. 2018, pp. 28–40. EBSCOhost, https://doi.org/10.1016/j.jocm.2017.11.001.

APA

Newman, J. P., Lurkin, V., & Garrow, L. A. (2018). Computational methods for estimating multinomial, nested, and cross-nested logit models that account for semi-aggregate data. Journal of Choice Modelling, 26, 28–40. https://doi.org/10.1016/j.jocm.2017.11.001

Chicago

Newman, Jeffrey P., Virginie Lurkin, and Laurie A. Garrow. 2018. “Computational Methods for Estimating Multinomial, Nested, and Cross-Nested Logit Models That Account for Semi-Aggregate Data.” Journal of Choice Modelling 26 (March): 28–40. doi:10.1016/j.jocm.2017.11.001.