Species richness estimation is an important problem in biodiversity analysis. This package provides methods for total species richness estimation (observed plus unobserved) and a method for modelling total diversity with covariates. breakaway() estimates total (observed plus unobserved) species richness. Microbial diversity datasets are characterized by a large number of rare species and a small number of highly abundant species. The class of models implemented by breakaway() is flexible enough to model both these features. breakaway_nof1() implements a similar procedure however does not require a singleton count. betta() provides a method for modelling total diversity with covariates in a way that accounts for its estimated nature and thus accounts for unobserved taxa, and betta_random() permits random effects modelling.
|Author||Amy Willis and John Bunge|
|Date of publication||2016-03-30 08:14:27|
|Maintainer||Amy Willis <email@example.com>|
apples: "apples" dataset
betta: modelling total diversity
betta_pic: function for plotting total diversity
betta_random: modelling total diversity with random effects
breakaway: function for species richness estimation
breakaway_nof1: species richness estimation without singletons
breakaway-package: Species richness estimation and modelling in the...
chao1: species richness lower bound
chao1_bc: species richness estimator under equal detection...
chao_bunge: function for species richness estimation
hawaii: "hawaii" dataset
wlrm_transformed: function for species richness estimation
wlrm_untransformed: function for species richness estimation