Linear Assignment Sampling: Spatially Balanced Sampling With Auxiliary Variables

ABSTRACT Estimating parameters of spatial populations requires a sample of response values distributed over the study region. When spatial trends are present, spatially balanced designs give more precise results for commonly used estimators. If auxiliary variables are available, these can also be included in the design to improve precision further. This article proposes a new spatially balanced design to force sample spread in the space of the auxiliary variables. All we require is a distance measure between population units. Numerical results show that the method generates spatially balanced samples and compares favorably with existing designs. We provide two example applications using spatial populations with auxiliary variables and consider equal and unequal probability designs.

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Publication Details

Journal
Environmetrics
Published
2025-10-01
DOI
https://doi.org/10.1002/env.70042
Primary Topic
Survey Sampling and Estimation Techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Linear Assignment Sampling: Spatially Balanced Sampling With Auxiliary Variables

C. J. Price, B. L. Robertson, Marco Reale
Environmetrics
Survey Sampling and Estimation Techniques
article

Linear Assignment Sampling: Spatially Balanced Sampling With Auxiliary Variables

C. J. Price, B. L. Robertson, Marco Reale
article en

Abstract

ABSTRACT Estimating parameters of spatial populations requires a sample of response values distributed over the study region. When spatial trends are present, spatially balanced designs give more precise results for commonly used estimators. If auxiliary variables are available, these can also be included in the design to improve precision further. This article proposes a new spatially balanced design to force sample spread in the space of the auxiliary variables. All we require is a distance measure between population units. Numerical results show that the method generates spatially balanced samples and compares favorably with existing designs. We provide two example applications using spatial populations with auxiliary variables and consider equal and unequal probability designs.

EnvironmetricsVol. 36(7)
University of Canterbury (NZ)
University of Canterbury
Openalex Percentile: Top 74%
Survey Sampling and Estimation Techniques
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