Disclaimer: Please note that the codes provided are to assist researchers and practitioners in using some recent model estimation (and computational) advances. As such, the codes have not been thoroughly vetted for all possible model specification variants, nor have the codes gone through a rigorous control and documentation check (some of the codes have been written by my current or former graduate students, and I do not have the time to carefully look into each of these codes and the corresponding documentations). If you want to use these codes, please be prepared to spend a good bit of time to understand the code. Some of the codes may be better documented than other codes.
I will be pleased to work with software programmers who want to formalize these codes within their programs and provide rigorous documentation and customer support. Note also that, for some models and procedures, the R code has been provided (in addition to the GAUSS code).
CODES
Bhat, C.R. and A. Mondal, "On the Almost Exact-Equivalence of the Radial and Spherical Unconstrained Cholesky-Based Parameterization Methods for Correlation Matrices," Technical paper, Department of Civil, Architectural and Environmental Engineering, The University of Texas at Austin, original version May 2021; revised version October 2021 (Keywords: correlation matrix, unconstrained optimization, spherical parameterization, radial parameterization, Cholesky decomposition, simulation).
Mondal, A., and C.R. Bhat (2022), "A Spatial Rank-Ordered Probit Model with an Application to Travel Mode Choice," Transportation Research Part B, Vol. 155, pp. 374-393 (Keywords: ranked data analysis, probit models, spatial econometrics, travel mode choice, autonomous vehicles).
Pinjari, A.R., and C.R. Bhat (2021), "Computationally Efficient Forecasting Procedures for Kuhn-Tucker Consumer Demand Model Systems: Application to Residential Energy Consumption Analysis," Journal of Choice Modelling, Vol. 39, 100283 (Keywords: discrete-continuous models, Kuhn-Tucker consumer demand systems, MDCEV model, forecasting procedure, residential energy consumption, climate change impacts).
Mondal, A. and C.R. Bhat (2021), "A New Closed Form Multiple Discrete-Continuous Extreme Value (MDCEV) Choice Model with Multiple Linear Constraints," Transportation Research Part B, Vol. 147, pp. 42-66 (Keywords: consumer theory, multiple discrete-continuous extreme value model, extreme value distribution, multivariate distributions, multiple constraints, closed-form structure).
Bhat, C.R., A. Mondal, K.E. Asmussen, and A.C. Bhat (2020), "A Multiple Discrete Extreme Value Choice Model with Grouped Consumption Data and Unobserved Budgets,"Transportation Research Part B, Vol. 141, pp. 196-222 (Keywords: multiple discrete-grouped choice models, MDCEV models, multiple discrete outcomes, linear outside good utility, grouped consumption, unobserved budgets, utility theory, time use, consumer theory).
Bhat, C.R. (2018), "A New Flexible Multiple Discrete-Continuous Extreme Value (MDCEV) Choice Model," Transportation Research Part B, Vol. 110, pp. 261-279 (Keywords: multiple discrete-continuous choice models, multiple discrete-continuous extreme value model, utility theory, time use, consumer theory).
Bhat, C.R. (2018), "New Matrix-Based Methods for the Analytic Evaluation of the Multivariate Cumulative Normal Distribution Function," Transportation Research Part B, Vol. 109, pp. 238-256 (Keywords: multivariate normal cumulative distribution function, multinomial probit, discrete choice models, econometric models).
Bhat, C.R., S.K. Dubey, M. Jobair Bin Alam, and W.H. Khushefati (2015), "A New Spatial Multiple Discrete-Continuous Modeling Approach to Land Use Change Analysis,"Journal of Regional Science, Vol. 55, No. 5, pp. 801-841 (Keywords: spatial econometrics, multiple discrete-continuous model, random-coefficients, land use analysis, MACML approach).
Bhat, C.R. (2015), "A New Spatial (Social) Interaction Discrete Choice Model Accommodating for Unobserved Effects due to Endogenous Network Formation," Transportation, Vol. 42, No. 5, pp. 879-914 (Keywords: spatial interactions, social interactions, spatial lag, spatial drift, endogenous group formation, maximum approximate composite marginal likelihood, panel data).
Bhat, C.R., R. Paleti, and M. Castro (2015), "A New Utility-Consistent Econometric Approach to Multivariate Count Data Modeling,," Journal of Applied Econometrics, Vol. 30, No. 5, pp. 806-825 (Keywords: multivariate count data, generalized ordered-response, multinomial probit, multivariate normal distribution).
Bhat, C.R., and S.K. Dubey (2014), "A New Estimation Approach to Integrate Latent Psychological Constructs in Choice Modeling," Transportation Research Part B, Vol. 67, pp. 68-85 (Keywords: multinomial probit, ICLV models, MACML estimation approach).
Bhat, C.R., R. Paleti, and P. Singh (2014), "A Spatial Multivariate Count Model for Firm Location Decisions,," Journal of Regional Science, Vol. 54, No. 3, pp. 462-502 (Keywords: multivariate analysis, spatial econometrics, business counts, composite marginal likelihood).
Paleti, R., C.R. Bhat, and R.M. Pendyala (2013), "Integrated Model of Residential Location, Work Location, Vehicle Ownership, and Commute Tour Characteristics," Transportation Research Record, Vol. 2382, pp. 162-172 (Keywords: residential location choice, simultaneous equations model, self-selection effects, auto ownership, commute characteristics, multi-dimensional choice model estimation).
Paleti, R., C.R. Bhat, R.M. Pendyala, and K.G. Goulias (2013), "Modeling of Household Vehicle Type Choice Accommodating Spatial Dependence Effects," Transportation Research Record, Vol. 2343, pp. 86-94 (Keywords: vehicle ownership, vehicle type choice, spatial dependence, unobserved heterogeneity, social interactions).
Bhat, C.R., M. Castro, and M. Khan (2013), "A New Estimation Approach for the Multiple Discrete-Continuous Probit (MDCP) Choice Model," Transportation Research Part B, Vol. 55, pp. 1-22 (Keywords: multiple discrete-continuous model, maximum approximate composite marginal likelihood, recreation choice).
Paleti, R., and C.R. Bhat (2013), "The Composite Marginal Likelihood (CML) Estimation of Panel Ordered-Response Models," Journal of Choice Modelling, Vol. 7, pp. 24-43 (Keywords: ordered-response model, simulated likelihood, composite marginal likelihood, cross-sectional model, panel model).
Castro, M., R. Paleti, and C.R. Bhat (2013), "A Spatial Generalized Ordered Response Model to Examine Highway Crash Injury Severity," Accident Analysis and Prevention, Vol. 52, pp. 188-203 (Keywords: crash injury severity, generalized ordered response model, unobserved heterogeneity, spatial dependence, highway crashes, composite marginal likelihood, spatial econometrics).
Sidharthan, R., and C.R. Bhat (2012), "Incorporating Spatial Dynamics and Temporal Dependency in Land Use Change Models," Geographical Analysis, Vol. 44, No. 4, pp. 321-349 (Keywords: spatial econometrics, spatial multipliers, discrete spatial panel, random-coefficients, land use analysis).
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 (Keywords: multinomial probit, mixed models, maximum approximate composite marginal likelihood, maximum simulated likelihood, multivariate skew-normal distribution).
Castro, M., R. Paleti, and C.R. Bhat (2012), "A Latent Variable Representation of Count Data Models to Accommodate Spatial and Temporal Dependence: Application to Predicting Crash Frequency at Intersections," Transportation Research Part B, Vol. 46, No. 1, pp. 253-272 (Keywords: count data, multivariate analysis, spatial econometrics, accident analysis, composite marginal likelihood, generalized ordered response).
Bhat, C.R. (2011), "The Maximum Approximate Composite Marginal Likelihood (MACML) Estimation of Multinomial Probit-Based Unordered Response Choice Models," Transportation Research Part B, Vol. 45, No. 7, pp. 923-939 (Keywords: multinomial probit, mixed models, composite marginal likelihood, discrete choice models, spatial econometrics, panel data).
Pinjari, A.R., and C.R. Bhat (2010), "A Multiple Discrete-Continuous Nested Extreme Value (MDCNEV) Model: Formulation and Application to Non-Worker Activity Time-Use and Timing Behavior on Weekdays," Transportation Research Part B, Vol. 44, No. 4, pp. 562-583 (Keywords: multiple discrete-continuous choices, random utility maximization, Kuhn-Tucker demand model systems, Flexible substitution patters, activity time-use, activity timing).
Bhat, C.R. (2008), "The Multiple Discrete-Continuous Extreme Value (MDCEV) Model: Role of Utility Function Parameters, Identification Considerations, and Model Extensions," Transportation Research Part B, Vol. 42, No. 3, pp. 274-303 (Keywords: Discrete-continuous system, multiple discreteness, Kuhn-Tucker demand systems, mixed discrete choice, random utility maximization).
Sivakumar, A., C.R. Bhat, and G. Okten (2005), "Simulation Estimation of Mixed Discrete Choice Models with the Use of Randomized Quasi-Monte Carlo Sequences: A Comparative Study," Transportation Research Record, Vol. 1921, pp. 112-122.
Bhat, C.R. (2003), "Simulation Estimation of Mixed Discrete Choice Models Using Randomized and Scrambled Halton Sequences", Transportation Research Part B, Vol. 37, No. 9, pp. 837-855. (Keywords: Maximum simulated likelihood estimation, pseudo-random sequences, quasi-random sequences, hybrid sequences, multinomial probit model, mixed logit model, mixed probit model).