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分类依据与纠错

AI 根据所提供的论文材料归类:文本明确研究概率选择模型及按已选替代项抽样的参数估计,并以交通方式等选择为例,直接对应离散选择。

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代码、数据与补充材料

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关注这篇论文的作者
Charles F. Manski
Steven R. Lerman

基于选择结果抽样的选择概率估计

研究问题
当样本按已选择的替代项抽取,而非先抽取决策者再观察其选择时,如何从这种样本推断总体选择模型的参数?
方法与思路
作者从按选择结果抽样的机制出发,研究总体模型参数能否由此推断,并构造相应估计量,分析常规抽样估计方法的表现。
材料陈述的贡献
摘要称确认这类样本能够用于推断选择模型参数,提出合适的估计量,并刻画原本用于外生抽样的估计方法在此情形下的行为。
阅读关注点
阅读时核对参数可识别的条件、样本选择比例与总体选择概率的关系,以及所提估计量和常规方法各自的统计性质。
阅读边界
所给文本主要是引言,未说明识别条件、抽样比例要求、估计量公式或具体统计性质,不能直接据此实施抽样校正。

原文摘要

Ti-H CONCERN of this paper is the estimation of the parameters of a probabilistic choice model when choices rather than decision makers are sampled. Existing estimation methods presuppose an exogeneous sampling process, that is one in which a sequence of decision makers are drawn and their choice behaviors observed. In contrast, in choice based sampling processes, a sequence of chosen alternatives are drawn and the characteristics of the decision makers selecting those alternatives are observed. The problem of estimating a choice model from a choice based sample has suibstantive interest because data collection costs for such processes are often considerably smaller than for exogeneous sampling. Particular instances of this differential occur in the analysis of transportation behavior. For example, in studying choice of mode for work trips, it is often less expensive to survey transit users at the station and auto users at the parking lot than to interview commuters at their homes. Similarly, in examining choice of destination for shopping trips, surveys conducted at various shopping centers offer significant cost savings relative to home interviews.2 While interest in transportation applications provided the original motivation for our work, it has become apparent that choice based sampling processes can be cost effective in the analysis of numerous decision problems. In particular, wherever decision makers are physically clustered according to the alternatives they select, choice based sampling processes can achieve economies of scale not available with exogeneous sampling. Some non-transportation decision problems in which decision makers do cluster as described include the schooling decisions of students, the job decisions of workers, the medical care decisions of patients and the residential location decisions of households. Realization of the sampling cost benefits of choice based samples presupposes of course that the parameters of the underlying choice model can logically be inferred from such samples and that a tractable estimator with desirable statistical properties can be found. We shall, in this paper, confirm the logical supposition, develop a suitable estimator, and characterize the behavior of existing, exogeneous sampling, estimators in the context of choice based samples. An outline of the presentation and summary of major results follows.

笔记与分组