Estimating Population Attribute Values in a Table: "Get Me Started in" Iterative Proportional Fitting
Estimating Population Attribute Values in a Table: "Get Me Started in" Iterative Proportional Fitting
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估计表中的总体属性值：“让我开始”迭代比例拟合
DOI：
10.1080/00330124.2015.1099449
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
Lomax N
中科院分区：
文献类型：
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作者：
Lomax N
迭代比例拟合（IPF）是一种可用于根据其他数据集中报告的总数调整一个数据集中报告的分布的技术。IPF用于修订信息不完整、不准确、过时或仅为样本的数据表。指规数方法虽然得到广泛应用，但很少以非专家用户可以使用的方式提出。本文通过讨论如何操作该方法填补了这一空白，并认为IPF是一种可访问和透明的工具，可应用于人口地理和人口统计学的一系列数据情况。它提供了三个案例研究的例子，其中IPF已被应用于地理数据问题;数据和算法提供给用户作为补充材料。
Iterative proportional fitting (IPF) is a technique that can be used to adjust a distribution reported in one data set by totals reported in others. IPF is used to revise tables of data where the information is incomplete, inaccurate, outdated, or a sample. Although widely applied, the IPF methodology is rarely presented in a way that is accessible to nonexpert users. This article fills that gap through discussion of how to operationalize the method and argues that IPF is an accessible and transparent tool that can be applied to a range of data situations in population geography and demography. It offers three case study examples where IPF has been applied to geographical data problems; the data and algorithms are made available to users as supplementary material.