A Framework for Dimensioning the Total Population in Networks Composed of Rare and Clustered Populations

• Camila D. da Silva UFF
• Antonio A. de A. Rocha UFF

DOI: https://doi.org/10.5753/wperformance.2022.223259

Abstract

Dimensioning the total population in networks whose structure is composed of a rare and clustered population is not a trivial task. In these circumstances, it is usual to overlay a grid over the region in which the population is contained and select cells from that grid. A framework called the 2-Layer and 2-Estimator Method - 2L2EM was proposed and it implements the Multiple Capture and Recapture Method - MCRM in layer 1 to obtain the estimates within the cell to be used as input for the Adaptive Cluster Sampling - ACS which is layer 2 in which the total population in the network is estimated. The studies with synthetic and real data reveal that 2L2EM provides relevant estimates in relation to ACS and MCRM.

Keywords: Multiple Capture and Recapture Method, Adaptive Cluster Sampling, Horvitz-Thompson Estimator, Hansen-Hurwitz Estimator, Schnabel Estimator

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