ChaoShared: Estimation of the number of shared species in two communities

Description Usage Arguments Value Author(s) Examples

Description

ChaoShared is a function to provide a shared species estimator in tow communities based on the following two sampling schemes.

  1. In each community, a random sample of individuals is taken and species frequencies or abundances are recored;

  2. Each communtiy is sample several times or the whole area is divided into several quadrats and species presence/absence data for multiple samples/quadrats are recorded.

Usage

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ChaoShared(data, datatype = c("abundance", "incidence"), se = TRUE,
  nboot = 200, conf = 0.95)

Arguments

data

a numerical matrix or a data frame with two columns. Each column represent the species abundances or incidence frequencies of each community. If datatype = "incidence", then the input format of first entry should be total number of sampling units, and followed by species incidence frequencies in each column (See examples).

datatype

the data type of input data. That is individual-based abundance data (datatype = "abundance") or presence/absence sample-base incidence data (datatype = "incidence").

se

calculate bootstrap standard error and show confidence interval; default is TRUE.

nboot

the number of bootstrap resampling times, default is 200.

conf

a confidence coefficient between 0 and 1.

Value

returns a list of two. First is the basic data informaiton; the other is a table of various estimators, their standard error and 100*conf % confidence interval.

Author(s)

Anne Chao, K. H. Ma and T. C. Hsieh

Examples

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# load the individual-base (abundance) data
data(SharedSpecDemoAbu)
# Estimation of shared species
ChaoShared(SharedSpecDemoAbu, datatype="abundance", se=TRUE, nboot=200, conf=0.95)
# load the presence/absence sample-base (incidence) data
data(SharedSpecDemoInci)
# Estimation of shared species
ChaoShared(SharedSpecDemoInci, datatype="incidence", se=TRUE, nboot=200, conf=0.95)

JohnsonHsieh/SpadeR documentation built on May 7, 2019, 12:02 p.m.