This paper explores the potential of a special instance of the Combination of Random Utility Models (CoRUM; Papola, 2016), termed Combination of Nested Logit (CoNL), as kernel model in conjunction with several types of mixing distributions of tastes (parametric, nonparametric, semiparametric). Various model formulations are illustrated with their mathematical properties, and several alternative kernel models are identified for comparison. An estimation exercise is presented on a real mode choice dataset from a stated preference survey on the intercity corridor between Naples and Milan in Italy. Results, in terms of both in-sample and out-of-sample goodness-of-fit on a 10-fold cross-validation show that models with the proposed CoNL kernel outperform contrasted models.

本文探讨了随机效用模型组合（CoRUM; Papola，2016）的一种特殊实例（称为嵌套Logit组合（CoNL））作为内核模型以及多种口味混合分布类型（参数，非参数）的潜力，半参数）。说明了各种模型公式及其数学特性，并确定了几种可供选择的内核模型进行比较。来自意大利那不勒斯和米兰之间城市间走廊的偏好调查中，实模式选择数据集上进行了估算。在10倍交叉验证中，就样本内和样本外拟合优度而言，结果表明，带有建议的CoNL内核的模型优于对比模型。