In the last decade, an increasing number of papers testifies a renewed interest in the topic of individual specialization in resource use and its implication at higher levels of ecological organization. We present the package R Individual Specialization (RInSp) for the free open-source statistical software r. RInSp provides a comprehensive set of classical and recently proposed indices for quantifying the degree of individual specialization using both categorical and continuous resource use data. The package also includes tools for ad hoc Monte Carlo and jackknife resampling procedures for significance testing, plotting and input/output data manipulation. The use of RInSp is demonstrated by two examples. In addition, the potential of the package to be implemented beyond its original scope for multi-level quantitative analyses of individual trait variance in natural communities is illustrated

RInSp: an R package for the analysis of individual specialization in resource use

MANCINELLI, GIORGIO
Ultimo
Membro del Collaboration Group
2013-01-01

Abstract

In the last decade, an increasing number of papers testifies a renewed interest in the topic of individual specialization in resource use and its implication at higher levels of ecological organization. We present the package R Individual Specialization (RInSp) for the free open-source statistical software r. RInSp provides a comprehensive set of classical and recently proposed indices for quantifying the degree of individual specialization using both categorical and continuous resource use data. The package also includes tools for ad hoc Monte Carlo and jackknife resampling procedures for significance testing, plotting and input/output data manipulation. The use of RInSp is demonstrated by two examples. In addition, the potential of the package to be implemented beyond its original scope for multi-level quantitative analyses of individual trait variance in natural communities is illustrated
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11587/381052
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