select_best_models: "Best" parametric models for estimating species richness with...

Description Usage Arguments Value Examples

Description

This function gives the "best" models among Poisson model, geometric model, two-component geometric mixture model and three-component geometric model.

Usage

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select_best_models(input_data, parallel = F, tau_range = NULL,
  control = list(ncores = ceiling(detectCores()/2)))

Arguments

input_data

An input type that can be processed by convert()

parallel

A logic scalar that decides whether the richness estimates are computed with parallelization. Currently an error is returned for Windows.

control

A list containing an integer ncores that specifies the number of cores to use in parallelization when parallel == T

Value

A data frame displaying the point estimates, standard errors, AICc, GOF0 and GOF5 for different parametric models and cutoffs.

Examples

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library(breakaway)
data(apples)
select_best_models(apples)

data(hawaii)
select_best_models(hawaii)

statdivlab/CatchMore documentation built on May 8, 2019, 8:12 a.m.