decay.model() now allows fitting the Gompertz function (as described in Martín-Devasa et al. 2022, Diversity and Distributions), in addition to negative exponential and power law functions. To do this, nonlinear models are now fitted via the nls.lm() function in the minpack.lm package (which uses the Levenberg-Marquardt Nonlinear Least-Squares Algorithm), instead of glm() as in the previous versions of betapart
boot.coefs.decay() now implements the site-block resampling method introduced in Martínez-Santalla et al. 2022 (J. Biogeogr.)
A new function, zdep() allows assessing the significance of differences between parameters of two distance-decay models, as introduced in Martín-Devasa et al. 2022 (Ecol. Informatics)
plot.decay() was modified to handle the new decay.model() function
decay.model() to implement the block permutation described in Martínez-Santalla et al 2022 (J. Biogeogr.) for assessing the significance of the distance decay modelfunctional.betapart.core() was fixed to run it in parallel with multi = TRUEfunctional.betapart.core.pairwise() to get vertice coordinates in the output detailsfunctional.betapart.core() was updated. Options can be passed to qhull to prevent some crashes and a progress bar can be displayed. When setting multi=TRUE, the function stop earlier if the number of communities is too important.
New function to control options passed to qhull for convexhull estimation: qhull.opt()
New function to compute rapidly pair-wise dissimilarty matrices: functional.betapart.core.pairwise()
functional.beta.pair() was updated to integrate functional.betapart.core.pairwise
functional.betapart.core() to allow internal parallel computingbeta.para.control()functional.betapart.core() to allow parallel computingdecay.model() fits a negative-exponential or mower law function describing the decay of assemblage similarity with spatial distance.
plot.decay() allows plotting the curves fitted with decay.model().
boot.coefs.decay() bootstraps the parameters of the functions fitted with decay.model().