Application of an Adaptive Monte Carlo Algorithm to Mixed Logit Estimation

[1]  J. Halton On the efficiency of certain quasi-random sequences of points in evaluating multi-dimensional integrals , 1960 .

[2]  Bronwyn H Hall,et al.  Estimation and Inference in Nonlinear Structural Models , 1974 .

[3]  John E. Dennis,et al.  Numerical methods for unconstrained optimization and nonlinear equations , 1983, Prentice Hall series in computational mathematics.

[4]  George L. Nemhauser,et al.  Handbooks in operations research and management science , 1989 .

[5]  Reuven Y. Rubinstein,et al.  Discrete Event Systems , 1993 .

[6]  David J. Thuente,et al.  Line search algorithms with guaranteed sufficient decrease , 1994, TOMS.

[7]  R. Caflisch,et al.  Quasi-Monte Carlo integration , 1995 .

[8]  Ronald L. Wasserstein,et al.  Monte Carlo: Concepts, Algorithms, and Applications , 1997 .

[9]  Stephen J. Wright,et al.  Numerical Optimization , 2018, Fundamental Statistical Inference.

[10]  C. Bhat Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model , 2001 .

[11]  Alexander Shapiro,et al.  Stochastic programming by Monte Carlo simulation methods , 2000 .

[12]  K. Train Halton Sequences for Mixed Logit , 2000 .

[13]  Nicholas I. M. Gould,et al.  Trust Region Methods , 2000, MOS-SIAM Series on Optimization.

[14]  Pierre L'Ecuyer,et al.  Recent Advances in Randomized Quasi-Monte Carlo Methods , 2002 .

[15]  David A. Hensher,et al.  The Mixed Logit Model: the State of Practice and Warnings for the Unwary , 2001 .

[16]  A. Shapiro Monte Carlo Sampling Methods , 2003 .

[17]  P. Toint,et al.  Numerical Experiments with AMLET, a New Monte-Carlo Al- gorithm for Estimating Mixed Logit Models , 2003 .

[18]  Zsolt Sándor,et al.  Quasi-random simulation of discrete choice models , 2004 .

[19]  C. Bhat,et al.  Simulation Estimation of Mixed Discrete Choice Models with the Use of Randomized Quasi–Monte Carlo Sequences , 2005 .

[20]  C. Bhat,et al.  Simulation Estimation of Mixed Discrete Choice Models Using Randomized Quasi-Monte Carlo Sequences: A Comparison of Alternative Sequences, Scrambling Methods, and Uniform-to-Normal Variate Transformation Techniques , 2005 .

[21]  F. Bastin,et al.  Evaluation of Optimization Methods for Estimating Mixed Logit Models , 2005 .

[22]  Philippe L. Toint,et al.  An adaptive Monte Carlo algorithm for computing mixed logit estimators , 2006, Comput. Manag. Sci..

[23]  Philippe L. Toint,et al.  Convergence theory for nonconvex stochastic programming with an application to mixed logit , 2006, Math. Program..

[24]  Stephane Hess,et al.  On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice , 2006 .

[25]  K. Axhausen,et al.  Evidence on the distribution of values of travel time savings from a six-week diary , 2006 .