R: Species Richness Estimation and Modeling

# Species Richness Estimation and Modeling

## Documentation for package ‘breakaway’ version 4.8.4

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package README

## Help Pages

alpha_estimate | alpha_estimate
alpha_estimates | alpha_estimates
apples | (Data) Frequency count table of soil microbes in an apples orchard.
betta | Modelling total diversity with betta
betta_lincom | Confidence intervals and testing for linear combinations of fixed effects estimated via betta() or betta_random()
betta_pic | function for plotting total diversity
betta_random | modelling total diversity with random effects
breakaway | Species richness estimation with breakaway
breakaway_nof1 | species richness estimation without singletons
build_frequency_count_tables | Build frequency count tables from an OTU table
chao1 | Chao1 species richness estimator
chao1_bc | Bias-corrected Chao1 species richness estimator
chao_bunge | Chao-Bunge species richness estimator
chao_shen | The Chao-Shen estimate of Shannon diversity
check_format | Run some basic checks on a possible frequency count table
convert | convert between different inputs for alpha-diversity estimates
cutoff_wrap | Find a cut-off for estimates relying on contiguous counts
F_test | Conduct F test of null hypothesis LB = 0 using output from betta() or betta_random()
get_F_stat | Calculate F statistic under null hypothesis LB = 0 using output from betta() or betta_random()
good_turing | The Good-Turing estimate of species richness
hawaii | (Data) Frequency count table of soil microbes in Hawaii.
kemp | Species richness estimation with Kemp-type models
make_design_matrix | Make design matrix
make_frequency_count_table | Draw frequency count subtables from an OTU table
objective_bayes_geometric | Estimate species richness with an objective Bayes method using a geometric model
objective_bayes_mixedgeo | Objective Bayes species richness estimate with the mixed-geometric model
objective_bayes_negbin | Objective Bayes species richness estimate with the Negative Binomial model
objective_bayes_poisson | Objective Bayes species richness estimate with the Poisson model
pasolli_et_al | (Data) Data frame of covariate information about pasolli_et_al.
physeq_wrap | Wrapper for phyloseq objects
plot.alpha_estimates | Plot function for alpha_estimates class
poisson_model | PoissonModel
poisson_model_nof1 | PoissonModelNof1
proportions_instead | OTU table to relative abundances
rnbinomtable | Negative binomially distributed frequency count tables.
rztnbinomtable | beta version: Zero-truncated negative binomially distributed frequency count tables.
sample_inverse_simpson | Plug-in Inverse Simpson diversity
sample_richness | Sample richness estimator
sample_shannon | Plug-in Shannon diversity
sample_shannon_e | Plug-in Shannon's E ("Equitability")
sample_simpson | Plug-in Simpson diversity
sample_size_estimate | Estimate the sample size needed to do an unpaired one-way test using betta
sample_size_figure | Plot the power obtained with sample size
simulate_betta | Simulate from a fitted betta model
simulate_betta_random | Simulate from a fitted betta_random model
soil_phylo | (Data) Data frame of soil data from whitman_et_al.
test_submodel | Conduct F test of null hypothesis LB = 0 using output from betta() or betta_random()
toy_metadata | (Data) Data frame of covariate information about toy_otu_table.
toy_otu_table | (Data) A toy OTU table.
toy_taxonomy | (Data) The taxonomy of the OTUs in 'toy_otu_table'.
true_gini | Calculate the true Gini-Simpson index
true_hill | Calculate the true Hill numbers
true_inverse_simpson | Calculate the true Inverse Simpson index
true_shannon | Calculate the true Shannon index based on proportions
true_shannon_e | Calculate the true Shannon's equitability index
true_simpson | Calculate the true Simpson index
wlrm_transformed | The transformed weighted linear regression estimator for species richness estimation
wlrm_untransformed | The untransformed weighted linear regression estimator for species richness estimation