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Spatially-balanced adaptive web sampling

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Abstract

The paper deals with sampling from a finite population that is distributed over space and has a highly uneven spatial distribution. It suggests a sampling design that allocates a portion of the sample units that are well spread over the population and sequentially selects the remaining units in sub-areas that appear to be of more interest according to the study variable values observed during the survey. In order to estimate the population mean while using this sampling design, a computationally intense estimator, obtained via the Rao–Blackwell approach, is proposed and a resampling method is used that makes the inference computationally feasible. The whole sampling strategy is evaluated through several Monte Carlo experiments.

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Authors and Affiliations

  1. Department of Statistics, Informatics, Applications “G. Parenti” (DISIA), University of Florence, Viale Morgagni 59, 50134, Florence, Italy

    Emilia Rocco

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  1. Emilia Rocco
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Correspondence to Emilia Rocco.

Additional information

Handling Editor: Bryan F. J. Manly.

Appendix

Appendix

Here are given the four populations with an uneven spatial distribution that are considered in the simulation study.

Fig. 1
figure 1

Blue-winged teal population. Study area divided into 50 plots

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Fig. 2
figure 2

Blue-winged teal population. Study area divided into 200 plots

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Fig. 3
figure 3

Pseudo Blue-winged teal population. Study area divided into 200 plots

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Fig. 4
figure 4

Caste Hill buttercups population. Study area divided into 300 plots

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Rocco, E. Spatially-balanced adaptive web sampling. Environ Ecol Stat 23, 219–231 (2016). https://doi.org/10.1007/s10651-015-0336-5

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  • DOI: https://doi.org/10.1007/s10651-015-0336-5

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