Name
Abstract | ||
|---|---|---|
Spatial operations research problems seek “best” locations, often points of minimum aggregate weighted distance, requiring georeferenced data as input. Frequently maps of such data are incomplete, with holes in their geographic distributions. Spatial statistical procedures are available to complete these data sets with best estimates of the missing values. Impacts such imputations have on 2-median facility location–allocation solutions are explored. The sampling distribution of the spatial mean and standard distance of these medians are studied. Population density is used as the weight attribute in determining location-allocation solutions because it can be accurately described with a relatively simple spatial statistical model. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1023/A:1026106825798 | Annals OR |
Keywords | Field | DocType |
spatial autocorrelation,spatial imputation,spatial mean,spatial statistics,standard distance,two-median facility location–allocation | Sampling distribution,Spatial analysis,Data mining,Data set,Spatial dependence,Spatial descriptive statistics,Statistical model,Spatial variability,Missing data,Statistics,Mathematics | Journal |
Volume | Issue | ISSN |
122 | 1-4 | 1572-9338 |
Citations | PageRank | References |
2 | 0.63 | 0 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel A. Griffith | 1 | 91 | 23.76 |