TY - JOUR

T1 - Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure

AU - Chipeta, Michael Give

AU - Terlouw, Dianne J.

AU - Phiri, Kamija S.

AU - Diggle, Peter John

N1 - This is the peer reviewed version of the following article: Chipeta, M., Terlouw, D., Phiri, K., and Diggle, P. (2016) Inhibitory geostatistical designs for spatial prediction taking account of uncertain covariance structure. Environmetrics, doi: 10.1002/env.2425 which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/env.2425/abstract This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2016/10/3

Y1 - 2016/10/3

N2 - 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.

AB - 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.

U2 - 10.1002/env.2425

DO - 10.1002/env.2425

M3 - Journal article

JO - Environmetrics

JF - Environmetrics

SN - 1180-4009

ER -