Flexible Model Structures for Discrete Choice Analysis

[1]  Chandra R. Bhat,et al.  Comprehensive, Unified Framework for Analyzing Spatial Location Choice , 2007 .

[2]  Chandra R. Bhat,et al.  The Impact of Stop-Making and Travel Time Reliability on Commute Mode Choice , 2006 .

[3]  Mark Lijesen,et al.  A mixed logit based valuation of frequency in civil aviation from SP-data , 2006 .

[4]  Gitakrishnan Ramadurai,et al.  Dynamics and Variability in Within-Day Mode Choice Decisions: Role of State Dependence, Habit Persistence, and Unobserved Heterogeneity , 2006 .

[5]  John M. Rose,et al.  Accounting for heterogeneity in the variance of unobserved effects in mixed logit models , 2006 .

[6]  Chandra R. Bhat,et al.  Modeling Demographic and Unobserved Heterogeneity in Air Passengers' Sensitivity to Service Attributes in Itinerary Choice , 2006 .

[7]  Karthik K. Srinivasan,et al.  Analysis of within-household effects and between-household differences in maintenance activity allocation , 2005 .

[8]  Juan de Dios Ortúzar,et al.  Valuing Noise Level Reductions in a Residential Location Context , 2005 .

[9]  J. Polak,et al.  MIXED LOGIT MODELLING OF AIRPORT CHOICE IN MULTI-AIRPORT REGIONS , 2005 .

[10]  Juan de Dios Ortúzar,et al.  Willingness-to-Pay Estimation with Mixed Logit Models: Some New Evidence , 2005 .

[11]  M. Bierlaire,et al.  ESTIMATION OF VALUE OF TRAVEL-TIME SAVINGS USING MIXED LOGIT MODELS , 2005 .

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

[13]  Varameth Vichiensan,et al.  MIXED LOGIT MODEL FRAMEWORK WITH STRUCTURALIZED SPATIAL EFFECTS: A TEST OF APPLICABILITY WITH AREA UNIT SYSTEMS IN LOCATION ANALYSIS , 2005 .

[14]  Sean T. Doherty,et al.  Mixed Logit Model of Activity-Scheduling Time Horizon Incorporating Spatial–Temporal Flexibility Variables , 2005 .

[15]  Juan de Dios Ortúzar,et al.  Preference Heterogeneity and Willingness to Pay for Travel Time Savings , 2004 .

[16]  C. Bhat,et al.  A Mixed Multinomial Logit Model Analysis of Weekend Recreational Episode Type Choice , 2004 .

[17]  Paula Iragüen,et al.  Willingness-to-pay for reducing fatal accident risk in urban areas: an Internet-based Web page stated preference survey. , 2004, Accident; analysis and prevention.

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

[19]  Kay W. Axhausen,et al.  Evidence on the distribution of values of travel time savings from a six-week diary , 2004 .

[20]  Chandra R. Bhat,et al.  A MIXED SPATIALLY CORRELATED LOGIT MODEL: FORMULATION AND APPLICATION TO RESIDENTIAL CHOICE MODELING , 2004 .

[21]  K. Chon,et al.  Accommodating Heterogeneity and Heteroscedasticity in Intercity Travel Mode Choice Model: Formulation and Application to HoNam, South Korea, High-Speed Rail Demand Analysis , 2004 .

[22]  John W. Polak,et al.  Development and application of a mixed cross-nested logit model , 2004 .

[23]  Hani S. Mahmassani,et al.  Analyzing heterogeneity and unobserved structural effects in route-switching behavior under ATIS: a dynamic kernel logit formulation , 2003 .

[24]  C. Bhat.  Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences , 2003 .

[25]  Kenneth A. Small,et al.  Valuing time and reliability: assessing the evidence from road pricing demonstrations , 2003 .

[26]  F. Carlsson.  The demand for intercity public transport: the case of business passengers , 2003 .

[27]  K. Train.  Discrete Choice Methods with Simulation , 2003 .

[28]  O A Nielsen,et al.  MSL for mixed logit model estimation - on shape of distributions , 2003 .

[29]  Juan de Dios Ortúzar,et al.  Stated preference in the valuation of interurban road safety. , 2003, Accident; analysis and prevention.

[30]  Kenneth E. Train,et al.  Discrete Choice Methods with Simulation , 2016 .

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

[32]  Antonino Vitetta,et al.  A model of route perception in urban road networks , 2002 .

[33]  Chandra R. Bhat,et al.  A UNIFIED MIXED LOGIT FRAMEWORK FOR MODELING REVEALED AND STATED PREFERENCES: FORMULATION AND APPLICATION TO CONGESTION PRICING ANALYSIS IN THE SAN FRANCISCO BAY AREA , 2002 .

[34]  C. Winston,et al.  UNCOVERING THE DISTRIBUTION OF MOTORISTS' PREFERENCES FOR TRAVEL TIME AND RELIABILITY : IMPLICATIONS FOR ROAD PRICING , 2002 .

[35]  M. Munizaga,et al.  EVALUATION OF MIXED LOGIT AS A PRACTICAL MODELING ALTERNATIVE , 2002 .

[36]  Joan L. Walker.  Mixed Logit (or Logit Kernel) Model: Dispelling Misconceptions of Identification , 2002 .

[37]  Andrew Daly,et al.  FLEXIBLE MODELS FOR ANALYZING ROUTE AND DEPARTURE TIME CHOICE , 2002 .

[38]  Shlomo Bekhor,et al.  Adaptation of Logit Kernel to Route Choice Situation , 2002 .

[39]  Mark Bradley,et al.  A MODEL FOR TIME OF DAY AND MODE CHOICE USING ERROR COMPONENTS LOGIC , 2003 .

[40]  F. Koppelman,et al.  The generalized nested logit model , 2001 .

[41]  D. Hensher.  The valuation of commuter travel time savings for car drivers: evaluating alternative model specifications , 2001 .

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

[43]  Chandra R. Bhat,et al.  A multi-level cross-classified model for discrete response variables , 2000 .

[44]  D. McFadden,et al.  MIXED MNL MODELS FOR DISCRETE RESPONSE , 2000 .

[45]  David A. Hensher,et al.  Measurement of the Valuation of Travel Time Savings , 2000 .

[46]  K. Train,et al.  Forecasting new product penetration with flexible substitution patterns , 1998 .

[47]  K. Train,et al.  Mixed Logit with Repeated Choices: Households' Choices of Appliance Efficiency Level , 1998, Review of Economics and Statistics.

[48]  Chandra R. Bhat,et al.  ACCOMMODATING FLEXIBLE SUBSTITUTION PATTERNS IN MULTI-DIMENSIONAL CHOICE MODELING: FORMULATION AND APPLICATION TO TRAVEL MODE AND DEPARTURE TIME CHOICE , 1998 .

[49]  Art B. Owen,et al.  Latin supercube sampling for very high-dimensional simulations , 1998, TOMC.

[50]  A. Owen.  Scrambled net variance for integrals of smooth functions , 1997 .

[51]  Denis Bolduc,et al.  The Effect of Incentive Policies on the Practice Location of Doctors: A Multinomial Probit Analysis , 1996, Journal of Labor Economics.

[52]  Tuffin Bruno.  On the use of low discrepancy sequences in Monte Carlo methods , 1996 .

[53]  C. Bhat.  A heteroscedastic extreme value model of intercity travel mode choice , 1995 .

[54]  W. Recker,et al.  Discrete choice with an oddball alternative , 1995 .

[55]  Harald Niederreiter,et al.  New Developments in Uniform Pseudorandom Number and Vector Generation , 1995 .

[56]  A. Owen.  Randomly Permuted (t,m,s)-Nets and (t, s)-Sequences , 1995 .

[57]  Jerome Spanier,et al.  Quasi-Random Methods for Estimating Integrals Using Relatively Small Samples , 1994, SIAM Rev..

[58]  William H. Press,et al.  The Art of Scientific Computing Second Edition , 1998 .

[59]  Harald Niederreiter,et al.  Implementation and tests of low-discrepancy sequences , 1992, TOMC.

[60]  Moshe Ben-Akiva,et al.  Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .

[61]  J. Boyd,et al.  THE EFFECT OF FUEL ECONOMY STANDARDS ON THE U.S. AUTOMOTIVE MARKET: AN HEDONIC DEMAND ANALYSIS , 1980 .

[62]  N. S. Cardell,et al.  Measuring the societal impacts of automobile downsizing , 1980 .

[63]  Carlos F. Daganzo,et al.  Multinomial Probit: The Theory and its Application to Demand Forecasting. , 1980 .

[64]  E. Braaten,et al.  An Improved Low-Discrepancy Sequence for Multidimensional Quasi-Monte Carlo Integration , 1979 .

[65]  Gary Chamberlain,et al.  Analysis of Covariance with Qualitative Data , 1979 .

[66]  S. Zaremba.  The Mathematical Basis of Monte Carlo and Quasi-Monte Carlo Methods , 1968 .