Um Framework para Dimensionar o Total Populacional em Redes Compostas por População Rara e Agrupada
Resumo
Dimensionar o total populacional em redes cuja estrutura é composta por uma população rara e agrupada não é uma tarefa trivial. Neste cenário, é usual sobrepor uma grade à região na qual a população está contida e selecionar células dessa grade. Um framework chamado de Método 2-Camadas e 2-Estimadores - M2C2E foi proposto e ele implementa o Método de Captura e Recaptura Múltipla - MCRM na camada 1 para gerar as estimativas dentro da célula a serem usadas como entrada para a Amostragem Adaptativa por Conglomerados - AAC que é a camada 2 na qual estima-se o total populacional na grade. Os estudos com dados sintéticos e com dados reais revelam que o M2C2E fornece estimativas relevantes em relação à AAC e ao MCRM.
Palavras-chave:
Multiple Capture and Recapture Method, Adaptive Cluster Sampling, Horvitz-Thompson Estimator, Hansen-Hurwitz Estimator, Schnabel Estimator
Referências
Accettura, N., Neglia, G., and Grieco, L. A. (2015). The capture-recapture approach for population estimation in computer networks. Computer Networks, 89:107–122.
Dalal, S. R. and Mallows, C. L. (1990). Some graphical aids for deciding when to stop testing software. IEEE Journal on Selected Areas in Communications, 8(2):169–175.
El Emam, K. and Laitenberger, O. (2001). Evaluating capture-recapture models with two inspectors. IEEE Transactions on Software Engineering, 27(9):851–864.
Hansen, M. H. and Hurwitz, W. N. (1943). On the theory of sampling from finite populations. The Annals of Mathematical Statistics, 14(4):333–362.
Horvitz, D. G. and Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260):663–685.
Peng, S., Li, S., et al. (2009). Estimation of a population size in large-scale wireless sensor networks. Journal of Computer Science and Technology, 24(5):987–997.
Schnabel, Z. E. (1938). The estimation of the total fish population of a lake. The American Mathematical Monthly, 45(6):348–352.
Singham, D. I. (2010). Analysis of Sequential Stopping Rules for Simulation Experiments. PhD thesis, University of California, Berkeley, USA.
Smith, P. J. (1988). Bayesian methods for multiple capture-recapture surveys. Biometrics, pages 1177–1189.
Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412):1050–1059.
Turk, P. and Borkowski, J. J. (2005). A review of adaptive cluster sampling: 1990–2003. Environmental and Ecological Statistics, 12(1):55–94.
Dalal, S. R. and Mallows, C. L. (1990). Some graphical aids for deciding when to stop testing software. IEEE Journal on Selected Areas in Communications, 8(2):169–175.
El Emam, K. and Laitenberger, O. (2001). Evaluating capture-recapture models with two inspectors. IEEE Transactions on Software Engineering, 27(9):851–864.
Hansen, M. H. and Hurwitz, W. N. (1943). On the theory of sampling from finite populations. The Annals of Mathematical Statistics, 14(4):333–362.
Horvitz, D. G. and Thompson, D. J. (1952). A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260):663–685.
Peng, S., Li, S., et al. (2009). Estimation of a population size in large-scale wireless sensor networks. Journal of Computer Science and Technology, 24(5):987–997.
Schnabel, Z. E. (1938). The estimation of the total fish population of a lake. The American Mathematical Monthly, 45(6):348–352.
Singham, D. I. (2010). Analysis of Sequential Stopping Rules for Simulation Experiments. PhD thesis, University of California, Berkeley, USA.
Smith, P. J. (1988). Bayesian methods for multiple capture-recapture surveys. Biometrics, pages 1177–1189.
Thompson, S. K. (1990). Adaptive cluster sampling. Journal of the American Statistical Association, 85(412):1050–1059.
Turk, P. and Borkowski, J. J. (2005). A review of adaptive cluster sampling: 1990–2003. Environmental and Ecological Statistics, 12(1):55–94.
Publicado
31/07/2022
Como Citar
SILVA, Camila D. da; ROCHA, Antonio A. de A..
Um Framework para Dimensionar o Total Populacional em Redes Compostas por População Rara e Agrupada. In: WORKSHOP EM DESEMPENHO DE SISTEMAS COMPUTACIONAIS E DE COMUNICAÇÃO (WPERFORMANCE), 21. , 2022, Niterói.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 60-71.
ISSN 2595-6167.
DOI: https://doi.org/10.5753/wperformance.2022.223259.
