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Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure
Author(s) -
Chipeta Michael,
Terlouw Dianne,
Phiri Kamija,
Diggle Peter
Publication year - 2017
Publication title -
environmetrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.68
H-Index - 58
eISSN - 1099-095X
pISSN - 1180-4009
DOI - 10.1002/env.2425
Subject(s) - covariance , variance (accounting) , statistics , sample size determination , sample (material) , sampling (signal processing) , mathematics , sampling design , analysis of covariance , computer science , mathematical optimization , population , chemistry , demography , accounting , filter (signal processing) , chromatography , sociology , business , computer vision
The problem of choosing spatial sampling designs for investigating an unobserved spatial phenomenon S arises in many contexts, for example, in identifying households to select for a prevalence survey to study disease burden and heterogeneity in a study region D . We studied randomized inhibitory spatial sampling designs to address the problem of spatial prediction while taking account of the need to estimate covariance structure. Two specific classes of design are inhibitory designs and inhibitory designs plus close pairs . In an inhibitory design, any pair of sample locations must be separated by at least an inhibition distance δ . In an inhibitory plus close pairs design, n − k sample locations in an inhibitory design with inhibition distance δ are augmented by k locations each positioned close to one of the randomly selected n − k locations in the inhibitory design, uniformly distributed within a disk of radius ζ . We present simulation results for the Matérn class of covariance structures. When the nugget variance is non‐negligible, inhibitory plus close pairs designs demonstrate improved predictive efficiency over designs without close pairs. We illustrate how these findings can be applied to the design of a rolling Malaria Indicator Survey that forms part of an ongoing large‐scale, 5‐year malaria transmission reduction project in Malawi.