Kernel logit method for the longitudinal analysis of discrete choice data: some numerical experiments

[1]  K. Binder.  Applications of the Monte Carlo Method in Statistical Physics , 2012 .

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

[3]  Hani S. Mahmassani,et al.  Forecasting freight transportation demand with the space-time multinomial probit model , 2000 .

[4]  H. Mahmassani,et al.  GLOBAL MAXIMUM LIKELIHOOD ESTIMATION PROCEDURE FOR MULTINOMIAL PROBIT (MNP) MODEL PARAMETERS , 2000 .

[5]  F. Koppelman,et al.  The paired combinatorial logit model: properties, estimation and application , 2000 .

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

[7]  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 .

[8]  John Geweke,et al.  Statistical inference in the multinomial multiperiod probit model , 1997 .

[9]  Pradeep K. Chintagunta,et al.  A Framework for Investigating Habits, “The Hand of the Past,” and Heterogeneity in Dynamic Brand Choice , 1996 .

[10]  Paul A. Ruud,et al.  Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results , 1996 .

[11]  Lung-fei Lee.  On Efficiency of Methods of Simulated Moments and Maximum Simulated Likelihood Estimation of Discrete Response Models , 1992, Econometric Theory.

[12]  K. Axhausen,et al.  Activity‐based approaches to travel analysis: conceptual frameworks, models, and research problems , 1992 .

[13]  Michael Keane,et al.  A Note on Identification in the Multinomial Probit Model , 1992 .

[14]  J. Horowitz.  RECONSIDERING THE MULTINOMIAL PROBIT MODEL , 1991 .

[15]  Ryuichi Kitamura,et al.  Panel Analysis in Transportation Planning: An Overview , 1990 .

[16]  D. S. Bunch,et al.  Estimability in the Multinomial Probit Model , 1989 .

[17]  B. R. Dansie.  PARAMETER ESTIMABILITY IN THE MULTINOMIAL PROBIT MODEL , 1985 .

[18]  C. Daganzo,et al.  Multinomial Probit with Time-Series Data: Unifying State Dependence and Serial Correlation Models , 1982 .

[19]  J. Kohlas,et al.  Monte Carlo Simulation in Operations Research , 1975 .

[20]  Chandra R. Bhat,et al.  Recent Methodological Advances Relevant to Activity and Travel Behavior Analysis , 2002 .

[21]  Hani S. Mahmassani,et al.  Role of Congestion and Information in Trip-Makers’ Dynamic Decision Processes: Experimental Investigation , 1999 .

[22]  Hani S. Mahmassani,et al.  DAY-TO-DAY DYNAMICS OF URBAN COMMUTER DEPARTURE TIME AND ROUTE SWITCHING DECISIONS: JOINT MODEL ESTIMATION (CHAPTER 20 OF TRAVEL BEHAVIOUR RESEARCH: UPDATING THE STATE OF PLAY) , 1998 .

[23]  Hani S. Mahmassani,et al.  EMPLOYEE ATTITUDES AND STATED PREFERENCES TOWARD TELECOMMUTING: AN EXPLORATORY ANALYSIS , 1993 .