This paper introduces mixl, a new R package for the estimation of advanced choice models. The estimation of such models typically relies on simulation methods with a large number of random draws to obtain stable results. mixl uses inherent properties of the log-likelihood problem structure to greatly reduce both the memory usage and runtime of the estimation procedure for specific types of mixed multinomial logit models. Functions for prediction and posterior analysis are included. Parallel computing is also supported, with near linear speedups observed on up to 24 cores. mixl is directly accessible from R, available on CRAN. We show that mixl is fast, easy to use, and scales to very large datasets. This paper presents the architecture and performance of the package, details its use, and presents some results using real world data and models.

本文介绍了mixl，这是一种用于评估高级选择模型的新R包。对此类模型的估计通常依赖于具有大量随机抽取的仿真方法以获得稳定的结果。mixl使用对数似然问题结构的固有属性来极大地减少特定类型的混合多项式logit模型的内存使用量和估计过程的运行时间。包括用于预测和后验分析的功能。还支持并行计算，在多达24个内核上观察到近乎线性的加速。mixl可从R直接访问，可在CRAN上获得。我们证明了mixl快速，易于使用，并且可以扩展到非常大的数据集。本文介绍了该程序包的体系结构和性能，详细介绍了其用法，并使用实际数据和模型给出了一些结果。