STATISTICAL-ANALYSIS OF SPATIAL DATA IN THE PRESENCE OF MISSING OBSERVATIONS - A METHODOLOGICAL GUIDE AND AN APPLICATION TO URBAN CENSUS-DATA
STATISTICAL-ANALYSIS OF SPATIAL DATA IN THE PRESENCE OF MISSING OBSERVATIONS - A METHODOLOGICAL GUIDE AND AN APPLICATION TO URBAN CENSUS-DATA
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DOI：
10.1068/a211511
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发表时间：
1989-11-01
期刊：
影响因子：
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通讯作者：
HAINING, RP
中科院分区：
文献类型：
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作者：
GRIFFITH, DA;BENNETT, RJ;HAINING, RP
本文简单介绍和指导了一种广泛适用于人口普查地图或陆地卫星图像等调查领域的缺失数据估计方法。给出的方法是一种极大似然法。它具有以下特点：(1)其分布特性已知，(2)它既适用于规则间隔的观测，也适用于不规则间隔的观测，(3)它可以处理丢失单元的不同空间构形，(4)它充分利用了已知空间数据中包含的信息(特别是它的空间自相关)，(5)它没有系统性的误差倾向，(6)它提供了“概率极限”。该算法以简单教程指南的形式给出。以休斯敦的收入中值水平为例，详细介绍了人口普查数据中缺失的单元格。这个例子的特点是一个变量均值和一个一般的方差-协方差矩阵。
In this paper a simple introduction and guide to a widely applicable method for estimating missing data in fields of enquiry such as census maps or LANDSAT images are presented. The method given is a maximum likelihood procedure. This is argued to have the particularly favourable characteristics (1) that its distribution properties are known, (2) it is applicable both to regularly and to irregularly spaced observations, (3) it can handle different spatial configurations of missing cells, (4) it makes full use of the information contained in the known spatial data (particularly its spatial autocorrelation), (5) it has no systematic tendency to error, and (6) it provides ‘probability limits’. The algorithm is presented in the form of a simple tutorial guide. An example, of median income levels in Houston, is worked through in detail for missing cells in census data. The example is characterised by a variable mean and a general variance — covariance matrix.