A Permutation-based Combination of Sign Tests for Assessing Habitat Selection
AbstractThe 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.
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Bibliographic InfoPaper provided by Department of Economics, University of Siena in its series Department of Economics University of Siena with number 622.
Date of creation: Oct 2011
Date of revision:
compositional data analysis; Johnson’s second order selection; Johnson’s third order selection; Monte Carlo studies; multiple testing; random habitat use.;
Find related papers by JEL classification:
- C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
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