We present a broad literature survey of parameter and state estimation for queueing systems. Our approach is based on various inference activities, queueing models, observations schemes, and statistical methods. We categorize these into branches of research that we call estimation paradigms. These include: the classical sampling approach, inverse problems, inference for non-interacting systems, inference with discrete sampling, inference with queueing fundamentals, queue inference engine problems, Bayesian approaches, online prediction, implicit models, and control, design, and uncertainty quantification. For each of these estimation paradigms, we outline the principles and ideas, while surveying key references. We also present various simple numerical experiments. In addition to some key references mentioned here, a periodically updated comprehensive list of references dealing with parameter and state estimation of queues will be kept in an accompanying annotated bibliography.

我们介绍了有关排队系统的参数和状态估计的广泛文献调查。我们的方法基于各种推理活动，排队模型，观察方案和统计方法。我们将它们归类为研究领域，我们将其称为估计范式。其中包括：经典采样方法，反问题，非交互系统的推理，离散采样的推理，排队基本原理的推理，队列推理引擎问题，贝叶斯方法，在线预测，隐式模型以及控制，设计和不确定性量化。对于这些估计范式，我们在调查关键参考文献时概述了原理和思想。我们还提出了各种简单的数值实验。除了此处提到的一些关键参考，