Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences

By Chandra R. Bhat. 2003

888 citations recorded by the source corpus.

Subfields: Numerical Analysis, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/4aafbbc04b717af3720c7c3689f9ab364cf8b15b

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Numerical Analysis

In Statistics and Probability

Citations in the corpus

An analysis of bicycle route choice preferences in Texas, US (2009, methodology): “The positive coefficient corresponding to the continuous bicycle facility dummy variable clearly underscores the preference among bicyclists for a continuous bicycle facility, especially for long commute trips (see Stinson and Bhat, 2003, and Antonakos, 1994 for a similar result).”
A Comprehensive Analysis of Built Environment Characteristics on Household Residential Choice and Auto Ownership Levels (2007, methodology): “Details of the Halton sequence and the procedure to generate this sequence are available in Bhat (2003) and Sivakumar et al. (2005). qc”
Latent class model or mixed logit model? A comparison by transport mode choice data (2009, methodology): “Among these models, the MLM is probably the most flexible one (see, for instance, Revelt and Train, 1998; McFadden and Train, 2000; Persson, 2002; Bhat, 2001, 2003; Greene and Hensher, 2003; Bhat and Gossen, 2004; Viton, 2004; Kim et al., 2005, etc.).”
On the Asymmetric User Perception of Transit Service Quality (2011, background): “Instead, the probability is usually approximated through simulation (Bhat 2001 , 2003 ; Bastin Cirillo, and Toint 2006 ).”
A simulation evaluation of the maximum approximate composite marginal likelihood (MACML) estimator for mixed multinomial probit models (2011, positive): “Within the context of Halton draws, we experimented with different kinds of scramblings and randomizations of the Halton sequence (see Bhat, 2003 and Sivakumar et al., 2005 for a review of these scrambling and randomization techniques).”
A comparison of the maximum simulated likelihood and composite marginal likelihood estimation approaches in the context of the multivariate ordered-response model (2010, methodology): “…context of a frequentist approach, Bhat and Srinivasan (2005) suggested a maximum simulated likelihood (MSL) method for evaluating the multi-dimensional integral in a crosssectional multivariate ordered response model system, using quasi-Monte Carlo simulation methods proposed by Bhat (2001; 2003).”
The Impact of Demographics, Built Environment Attributes, Vehicle Characteristics, and Gasoline Prices on Household Vehicle Holdings and Use (2009, methodology): “We use Halton draws in the current research (see Bhat, 2003).”
Rewarding rush-hour avoidance: A study of commuters' travel behavior. (2011, methodology): “Simulated log likelihoods of all models were estimated with 1,000 Halton draws (Halton, 1960) which significantly reduce the number of draws required compared to pseudo-random draws (Train, 2000; Bhat, 2003).”
Recent Progress on Endogeneity in Choice Modeling (2005, background): “This extension results in a multiple discrete-continuous equivalent of mixed multinomial logit (MMNL) (see Bhat, 2003 or Train, 2003 for discussions of the MMNL model).”
Household Vehicle Type Holdings and Usage: An Application of the Multiple Discrete-Continuous Extreme Value (MDCEV) Model (2006, methodology): “Specifically, we use 200 draws of the Halton sequence (details of the Halton sequence are available in Bhat, 2001; 2003).”
Simulation error in maximum likelihood estimation of discrete choice models (2019, background): “…Hypercube (Hess, Train and Polak 2006) ‒ Lattice rules (Munger et al. 2012) ‒ Generalized antithetic draws with double base shuffling (Sidharthan and Srinivasan 2010) ‒ Shuffling, scrambling sequences (Bhat 2003, Hess, Polak and Daly 2003, Hess and Polak 2003, Wang and Kockelman…”
Modeling the choice continuum: an integrated model of residential location, auto ownership, bicycle ownership, and commute tour mode choice decisions (2011, background): “Waddell (2001) and Bhat et al. (2004) present frameworks toward the behavioral integration of land use and transportation models, and Waddell et al. (2002) and Eluru et al.”