IDEAS home Printed from https://ideas.repec.org/a/eee/thpobi/v155y2024icp1-9.html
   My bibliography  Save this article

Exact confidence intervals for population growth rate, longevity and generation time

Author

Listed:
  • Hernandez-Suarez, Carlos
  • Rabinovich, Jorge

Abstract

By quantifying key life history parameters in populations, such as growth rate, longevity, and generation time, researchers and administrators can obtain valuable insights into its dynamics. Although point estimates of demographic parameters have been available since the inception of demography as a scientific discipline, the construction of confidence intervals has typically relied on approximations through series expansions or computationally intensive techniques. This study introduces the first mathematical expression for calculating confidence intervals for the aforementioned life history traits when individuals are unidentifiable and data are presented as a life table. The key finding is the accurate estimation of the confidence interval for r, the instantaneous growth rate, which is tested using Monte Carlo simulations with four arbitrary discrete distributions. In comparison to the bootstrap method, the proposed interval construction method proves more efficient, particularly for experiments with a total offspring size below 400. We discuss handling cases where data are organized in extended life tables or as a matrix of vital rates. We have developed and provided accompanying code to facilitate these computations.

Suggested Citation

  • Hernandez-Suarez, Carlos & Rabinovich, Jorge, 2024. "Exact confidence intervals for population growth rate, longevity and generation time," Theoretical Population Biology, Elsevier, vol. 155(C), pages 1-9.
  • Handle: RePEc:eee:thpobi:v:155:y:2024:i:c:p:1-9
    DOI: 10.1016/j.tpb.2023.11.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040580923000655
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tpb.2023.11.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Arun Hendi, 2023. "Estimation of confidence intervals for decompositions and other complex demographic estimators," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(5), pages 83-108.
    2. Nakamura, Miguel & Perez-Abreu, Victor, 1993. "Empirical probability generating function : An overview," Insurance: Mathematics and Economics, Elsevier, vol. 12(3), pages 287-295, June.
    3. Masami Fujiwara & Hal Caswell, 2001. "Demography of the endangered North Atlantic right whale," Nature, Nature, vol. 414(6863), pages 537-541, November.
    4. Ernest Lo & Dan Vatnik & Andrea Benedetti & Robert Bourbeau, 2016. "Variance models of the last age interval and their impact on life expectancy at subnational scales," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 35(15), pages 399-454.
    5. Bernard Ycart, 2013. "Fluctuation Analysis: Can Estimates Be Trusted?," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. M. D. Jiménez-Gamero & A. Batsidis, 2017. "Minimum distance estimators for count data based on the probability generating function with applications," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 503-545, July.
    2. Chiquet, Ross A. & Ma, Baoling & Ackleh, Azmy S. & Pal, Nabendu & Sidorovskaia, Natalia, 2013. "Demographic analysis of sperm whales using matrix population models," Ecological Modelling, Elsevier, vol. 248(C), pages 71-79.
    3. Arun Hendi, 2023. "Estimation of confidence intervals for decompositions and other complex demographic estimators," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 49(5), pages 83-108.
    4. Banks, J.E. & Dick, L.K. & Banks, H.T. & Stark, J.D., 2008. "Time-varying vital rates in ecotoxicology: Selective pesticides and aphid population dynamics," Ecological Modelling, Elsevier, vol. 210(1), pages 155-160.
    5. Apostolos Batsidis & María Dolores Jiménez-Gamero & Artur J. Lemonte, 2020. "On goodness-of-fit tests for the Bell distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(3), pages 297-319, April.
    6. Zhou, Can & Fujiwara, Masami & Grant, William E., 2013. "Dynamics of a predator–prey interaction with seasonal reproduction and continuous predation," Ecological Modelling, Elsevier, vol. 268(C), pages 25-36.
    7. Bramanti, Lorenzo & Iannelli, Mimmo & Santangelo, Giovanni, 2009. "Mathematical modelling for conservation and management of gorgonians corals: youngs and olds, could they coexist?," Ecological Modelling, Elsevier, vol. 220(21), pages 2851-2856.
    8. Jiménez-Gamero, M.D. & Alba-Fernández, M.V., 2019. "Testing for the Poisson–Tweedie distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 164(C), pages 146-162.
    9. Kendall, Bruce E. & Fujiwara, Masami & Diaz-Lopez, Jasmin & Schneider, Sandra & Voigt, Jakob & Wiesner, Sören, 2019. "Persistent problems in the construction of matrix population models," Ecological Modelling, Elsevier, vol. 406(C), pages 33-43.
    10. Barabás, György & Meszéna, Géza & Ostling, Annette, 2014. "Fixed point sensitivity analysis of interacting structured populations," Theoretical Population Biology, Elsevier, vol. 92(C), pages 97-106.
    11. Rouby, Etienne & Authier, Matthieu & Cam, Emmanuelle & Siebert, Ursula & Plard, Floriane, 2024. "Addressing temporal trends in survivorship from cross-sectional sampling designs: A modelling framework with applications for megafauna conservation," Ecological Modelling, Elsevier, vol. 490(C).
    12. Mullen, Kaitlyn A. & Peterson, Michael L. & Todd, Sean K., 2013. "Has designating and protecting critical habitat had an impact on endangered North Atlantic right whale ship strike mortality?," Marine Policy, Elsevier, vol. 42(C), pages 293-304.
    13. Williams, Byron K., 2007. "Optimal management of non-Markovian biological populations," Ecological Modelling, Elsevier, vol. 200(1), pages 234-242.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:thpobi:v:155:y:2024:i:c:p:1-9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/intelligence .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.