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Fast computing of some generalized linear mixed pseudo-models with temporal autocorrelation

Author

Listed:
  • Jay Ver Hoef
  • Josh London
  • Peter Boveng

Abstract

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Suggested Citation

  • Jay Ver Hoef & Josh London & Peter Boveng, 2010. "Fast computing of some generalized linear mixed pseudo-models with temporal autocorrelation," Computational Statistics, Springer, vol. 25(1), pages 39-55, March.
    • Handle: RePEc:spr:compst:v:25:y:2010:i:1:p:39-55
    DOI: 10.1007/s00180-009-0160-1
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    Citations

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    Cited by:

    1. Matt Higham & Michael Dumelle & Carly Hammond & Jay Hoef & Jeff Wells, 2024. "An Application of Spatio-Temporal Modeling to Finite Population Abundance Prediction," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 29(3), pages 491-515, September.
    2. Megan D. Higgs & Jay M. Ver Hoef, 2012. "Discretized and Aggregated: Modeling Dive Depth of Harbor Seals from Ordered Categorical Data with Temporal Autocorrelation," Biometrics, The International Biometric Society, vol. 68(3), pages 965-974, September.
    3. Peter L. Boveng & Jay M. Ver Hoef & David E. Withrow & Josh M. London, 2018. "A Bayesian Analysis of Abundance, Trend, and Population Viability for Harbor Seals in Iliamna Lake, Alaska," Risk Analysis, John Wiley & Sons, vol. 38(9), pages 1988-2009, September.

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