USING A LAPLACE APPROXIMATION TO ESTIMATE THE RANDOM COEFFICIENTS LOGIT MODEL BY NONLINEAR LEAST SQUARES*
提出用多元拉普拉斯近似替代模拟方法估计随机系数Logit模型，解决了参数相关估计困难和维度诅咒问题，模拟显示该方法在精度和计算时间上表现良好。
Current methods of estimating the random coefficients logit model employ simulations of the distribution of the taste parameters through pseudo‐random sequences. These methods suffer from difficulties in estimating correlations between parameters and computational limitations such as the curse of dimensionality. This article provides a solution to these problems by approximating the integral expression of the expected choice probability using a multivariate extension of the Laplace approximation. Simulation results reveal that our method performs very well, in terms of both accuracy and computational time.