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Computational aspects of N-mixture models

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  • Emily B. Dennis
  • Byron J.T. Morgan
  • Martin S. Ridout

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  • Emily B. Dennis & Byron J.T. Morgan & Martin S. Ridout, 2015. "Computational aspects of N-mixture models," Biometrics, The International Biometric Society, vol. 71(1), pages 237-246, March.
    • Handle: RePEc:bla:biomet:v:71:y:2015:i:1:p:237-246
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    File URL: http://hdl.handle.net/10.1111/biom.12246
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    References listed on IDEAS

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    1. Dimitris Karlis, 2003. "An EM algorithm for multivariate Poisson distribution and related models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(1), pages 63-77.
    2. J. Andrew Royle, 2004. "N-Mixture Models for Estimating Population Size from Spatially Replicated Counts," Biometrics, The International Biometric Society, vol. 60(1), pages 108-115, March.
    3. D. Dail & L. Madsen, 2011. "Models for Estimating Abundance from Repeated Counts of an Open Metapopulation," Biometrics, The International Biometric Society, vol. 67(2), pages 577-587, June.
    4. Wang, Ji-Ping Z. & Lindsay, Bruce G., 2005. "A Penalized Nonparametric Maximum Likelihood Approach to Species Richness Estimation," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 942-959, September.
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    Cited by:

    1. Alberto Cocaña-Fernández & Luciano Sánchez & José Ranilla, 2016. "Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster," Energies, MDPI, vol. 9(3), pages 1-16, March.
    2. Rafael A. Moral & John Hinde & Clarice G. B. Demétrio & Carolina Reigada & Wesley A. C. Godoy, 2018. "Models for Jointly Estimating Abundances of Two Unmarked Site-Associated Species Subject to Imperfect Detection," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(1), pages 20-38, March.
    3. Linda M. Haines, 2016. "Maximum likelihood estimation for N‐mixture models," Biometrics, The International Biometric Society, vol. 72(4), pages 1235-1245, December.
    4. Richard J. Barker & Matthew R. Schofield & William A. Link & John R. Sauer, 2018. "On the reliability of N†mixture models for count data," Biometrics, The International Biometric Society, vol. 74(1), pages 369-377, March.
    5. Xinyi Lu & Mevin B. Hooten & Andee Kaplan & Jamie N. Womble & Michael R. Bower, 2022. "Improving Wildlife Population Inference Using Aerial Imagery and Entity Resolution," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 27(2), pages 364-381, June.
    6. Laura L. E. Cowen & Panagiotis Besbeas & Byron J. T. Morgan & Carl J. Schwarz, 2017. "Hidden Markov models for extended batch data," Biometrics, The International Biometric Society, vol. 73(4), pages 1321-1331, December.

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