IDEAS home Printed from https://ideas.repec.org/p/usi/wpaper/622.html
   My bibliography  Save this paper

A Permutation-based Combination of Sign Tests for Assessing Habitat Selection

Author

Listed:
  • Lorenzo Fattorini
  • Caterina Pisani
  • Francesco Riga
  • Marco Zaccaroni

Abstract

The analysis of habitat use in radio-tagged animals is approached by comparing the portions of use vs the portions of availability observed for each habitat type. Since data are linearly dependent with singular variance-covariance matrices, standard multivariate statistical test cannot be applied. To overcome the problem, compositional data analysis is customary performed via log-ratio transform of sample observations. The procedure is criticized in this paper, emphasizing the many drawbacks which may arise from the use of compositional analysis. An alternative nonparametric solution is proposed in the framework of multiple testing. The habitat use is assessed separately for each habitat type by means of the sign test performed on the original observations. The resulting p-values are combined in an overall test statistic whose significance is determined permuting sample observations. The theoretical findings of the paper are checked by simulation studies. Applications to some case studies are considered.

Suggested Citation

  • Lorenzo Fattorini & Caterina Pisani & Francesco Riga & Marco Zaccaroni, 2011. "A Permutation-based Combination of Sign Tests for Assessing Habitat Selection," Department of Economics University of Siena 622, Department of Economics, University of Siena.
  • Handle: RePEc:usi:wpaper:622
    as

    Download full text from publisher

    File URL: http://repec.deps.unisi.it/quaderni/622.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Devin S. Johnson & Dana L. Thomas & Jay M. Ver Hoef & Aaron Christ, 2008. "A General Framework for the Analysis of Animal Resource Selection from Telemetry Data," Biometrics, The International Biometric Society, vol. 64(3), pages 968-976, September.
    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. Svetlana V. Tishkovskaya & Paul G. Blackwell, 2021. "Bayesian estimation of heterogeneous environments from animal movement data," Environmetrics, John Wiley & Sons, Ltd., vol. 32(6), September.
    2. James C. Russell & Ephraim M. Hanks & Murali Haran, 2016. "Dynamic Models of Animal Movement with Spatial Point Process Interactions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 21(1), pages 22-40, March.
    3. Thomas M Newsome & Guy-Anthony Ballard & Christopher R Dickman & Peter J S Fleming & Chris Howden, 2013. "Anthropogenic Resource Subsidies Determine Space Use by Australian Arid Zone Dingoes: An Improved Resource Selection Modelling Approach," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-11, May.
    4. Dhanushi A. Wijeyakulasuriya & Ephraim M. Hanks & Benjamin A. Shaby & Paul C. Cross, 2019. "Extreme Value-Based Methods for Modeling Elk Yearly Movements," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 24(1), pages 73-91, March.
    5. Wells, Adam G. & Blair, Colby C. & Garton, Edward O. & Rice, Clifford G. & Horne, Jon S. & Rachlow, Janet L. & Wallin, David O., 2014. "The Brownian bridge synoptic model of habitat selection and space use for animals using GPS telemetry data," Ecological Modelling, Elsevier, vol. 273(C), pages 242-250.
    6. Simon Benhamou, 2011. "Dynamic Approach to Space and Habitat Use Based on Biased Random Bridges," PLOS ONE, Public Library of Science, vol. 6(1), pages 1-8, January.
    7. Ephraim M. Hanks & Devin S. Johnson & Mevin B. Hooten, 2017. "Reflected Stochastic Differential Equation Models for Constrained Animal Movement," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 22(3), pages 353-372, September.
    8. Dhanushi A Wijeyakulasuriya & Elizabeth W Eisenhauer & Benjamin A Shaby & Ephraim M Hanks, 2020. "Machine learning for modeling animal movement," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-30, July.
    9. Chloe Bracis & Eliezer Gurarie & Bram Van Moorter & R Andrew Goodwin, 2015. "Memory Effects on Movement Behavior in Animal Foraging," PLOS ONE, Public Library of Science, vol. 10(8), pages 1-21, August.

    More about this item

    Keywords

    compositional data analysis; Johnson’s second order selection; Johnson’s third order selection; Monte Carlo studies; multiple testing; random habitat use.;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    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:usi:wpaper:622. 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: Fabrizio Becatti (email available below). General contact details of provider: https://edirc.repec.org/data/desieit.html .

    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.