A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models

By Chandra R. Bhat, Raghuprasad Sidharthan. 2011

56 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/519b98d86d2c1e18fa776f62ac62e3e6e8f4441f

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In Economics and Econometrics

Citations in the corpus

Latent class structures: taste heterogeneity and beyond (2014, background): “…focusses solely on continuous mixed logit rather than probit (cf. Daganzo, 1979), which is seeing a resurgence thanks to the work by Bhat (2011); Bhat and Sidharthan (2011) - many of the same distinctions discussed here apply to probit, albeit that the distributional assumptions are stricter…”
A New Generalized Heterogeneous Data Model (GHDM) to Jointly Model Mixed Types of Dependent Variables (2015, methodology): “As has been demonstrated by Bhat and Sidharthan (2011), the MACML method has the virtue of computational robustness in that the approximate CML surface is smoother and easier to maximize than are traditional simulation-based likelihood surfaces.”
The maximum approximate composite marginal likelihood (MACML) estimation of multinomial probit-based unordered response choice models (2011, methodology): “As we discuss later and show empirically in a companion paper (Bhat and Sidharthan, 2011), the first-order approximation is more than adequate (when combined with the CML approach) for estimation of any MNP model.”
A New Estimation Approach to Integrate Latent Psychological Constructs in Choice Modeling (2014, methodology): “As has been demonstrated by Bhat and Sidharthan (2011), the MACML method has the virtue of computational robustness in that the approximate CML surface is smoother and easier to maximize than traditional simulation-based likelihood surfaces.4 4 We should point out here that it is the combination of…”
The Composite Marginal Likelihood (CML) Inference Approach with Applications to Discrete and Mixed Dependent Variable Models (2014, methodology): “Several studies have demonstrated so in a variety of econometric modeling contexts (see, for example, Bhat and Sidharthan, 2011 and Paleti and Bhat, 2013).”
Consumer preferences and willingness to pay for advanced vehicle technology options and fuel types (2015, background): “As mentioned in Bhat and Sidharthan (2011) and Bhat (2011), the multidimensional integrals can be cumbersome to evaluate in the classical Maximum Simulated Likelihood (MSL) estimation method.”