Spatial models for spatial statistics: some unification



Publication Details

Van Hoef, J., Cressie, N. A. & Glenn-Lewin, D. (1993). Spatial models for spatial statistics: some unification. Journal of Vegetation Science, 4 (4), 441-452.


A general statistical framework is proposed for comparing linear models of spatial process and pattern. A spatial linear model for nested analysis of variance can be based on either fixed effects or random effects. Assuming intrinsic stationarity for a linear model, the expectations of a spatial nested ANOVA and two term local variance (TTLV) are functions of the variogram, and several examples are given. Paired quadrat variance (PQV) is a variogram estimator which can be used to approximate TTLV. Both nested ANOVA and TTLV can be seen as weighted lag-1 variogram estimators that are functions of support, rather than distance. There are two unbiased estimators for the variogram under aggregation. Computer simulation shows that the estimator with smaller variance depends on the process autocorrelation. -from Authors

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