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The use of a hazard-based duration model for imputation of missing personal income data

机译:使用基于危害的持续时间模型来估算缺失的个人收入数据

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摘要

This paper suggests using a proportional hazard model to predict personal income, for the purpose of imputing missing income data in household travel surveys. The model has a hazard function that comprises two multiplicative components: (1) a non-parametric baseline hazard function that is dependent only on the income level and (2) a function that is dependent only on the other personal attributes of the survey respondents (excluding income). To estimate and validate the model, data is drawn from a travel characteristics survey conducted in Hong Kong in year 2001. The model is found to have a much higher accuracy when compared with a conventional ordered probit model based on the assumption that the logarithm of income is normally distributed.
机译:本文建议使用比例风险模型预测个人收入,目的是在家庭旅行调查中估算缺失的收入数据。该模型的危害函数包括两个乘性成分:(1)仅取决于收入水平的非参数基线危害函数;(2)仅取决于调查受访者的其他个人属性的函数(不包括收入)。为了评估和验证该模型,数据来自2001年在香港进行的旅行特征调查。基于收入对数的假设,与传统的有序概率模型相比,该模型具有更高的准确性。正态分布。

著录项

  • 来源
    《Transportation》 |2009年第5期|565-579|共15页
  • 作者

    C. O. Tong; Jackie K. L. Lee;

  • 作者单位

    Department of Civil Engineering, The University of Hong Kong. Hong Kong, China;

    Department of Civil Engineering, The University of Hong Kong. Hong Kong, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    hazard-based duration model; income model; data imputation;

    机译:基于危害的持续时间模型;收入模型;数据插补;

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