Name
Abstract | ||
|---|---|---|
Interest in space–time modeling is experiencing a resurgence, in part because more and more sizeable space–time datasets are
becoming readily available. Currently techniques to describe these data, many of which have existed for years, are being utilized
and improved. This paper surveys general categories of these techniques (i.e., autoregressive-integrated-moving-average models,
space–time autoregressive models, three-dimensional geostatistical models, and panel data models), in retrospect, demonstrates
a future prospect (i.e., spatial filtering models), and suggests important topics for incorporation into a research agenda,
including ones pertaining to non-normal random variables, panel data models, space–time heterogeneity, missing data, and distributional
properties of space–time filters. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1007/s10109-010-0120-x | Journal of Geographical Systems |
Keywords | Field | DocType |
random effectsspace-timespatial filterstar,spatial filtering,spatial filter,space time,autoregressive model,moving average,random effects,missing data,three dimensional,random variable,star | Econometrics,Space time,Panel data,Autoregressive model,Random effects model,Data mining,Random variable,Missing data,Statistics,Geography | Journal |
Volume | Issue | ISSN |
12 | 2 | 1435-5949 |
Citations | PageRank | References |
3 | 0.45 | 1 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daniel A. Griffith | 1 | 91 | 23.76 |