rich: Species richness, their confidence interval and other useful...

In rich: Computes and Compares Species Richnesses

Description

Computes the cumulative and average species richness over a set of samples, the associated bootstrap statistics and other useful indices.

Usage

rich(matrix, verbose = FALSE, nrandom = NULL)

Arguments

matrix	matrix is a typical species-sample matrix. Rows correspond to samples whereas columns stand for species.
verbose	If verbose=FALSE, a simplied output is returned.
nrandom	Number or randomizations if bootstrap estimations are required. Non-null values < 10 are set to 99.

Details

rich computes basic descriptive statistics from typical species by sample data sets.

Value

cr	Cumulated richness over sampling units.
mr	Mean richness over sampling units.
mrsd	Standard deviation of the mean richness.
singletons	Species with at most one observation.
doubletons	Species with at most two observations.
uniques	Species encountered in only one sample.
duplicates	Species encountered in only two samples.
bootCR	A data frame showing the outputs of the bootstrap analyses of the cumulative richness (computed if nrandom != FALSE): cr.obs Observed cumulative richness, equal to cr above. cr.boot Mean of the bootstrap values. cr.bcorr Mean of the bootstrap values corrected for the bias estimated below. cr.bias Bias. cr.se Standard error of the cumulative richness estimated by bootstrap. This is estimated as the standard deviation of the bootstrap values. cr.lbn Lower bound of the first order normal approximation confidence interval (see boot.ci {boot}). cr.ubn Upper bound of the first order normal approximation confidence interval (see boot.ci {boot}).
bootMR	A data frame showing the outputs of the bootstrap analyses of the mean richness (computed if nrandom != FALSE): mr.obs Observed mean richness, equal to mr above. mr.boot Mean of the bootstrap values. mr.bcorr Mean of the bootstrap values corrected for the bias estimated below. mr.bias Bias. mr.se Standard error of the mean richness estimated by bootstrap. This is estimated as the standard deviation of the bootstrap values. mr.lbn Lower bound of the first order normal approximation confidence interval (see boot.ci {boot}). mr.ubn Upper bound of the first order normal approximation confidence interval (see boot.ci {boot}).
nrandom	Number of randomizations used in the bootstrap.
richvec	A vector containing the observed richness in each sample or populations. The mean of richvec corresponds to mr (available if verbose == TRUE).
matrix	The data set passed to rich as the matrix argument (available if verbose == TRUE).
matrixbin	Binary (presence/absence) transformation of the data set passed to rich as the matrix argument (available if verbose == TRUE).
sumrow	A vector of the sum of species for each sample (available if verbose == TRUE).
sumcol	A vector of the sum of sample for each species (available if verbose == TRUE).
zeroes	Number of zeroes in the data set (available if verbose == TRUE).

Author(s)

Jean-Pierre Rossi [e-mail]

References

Manly, B.F.J. (1997). Randomization and Monte Carlo methods in biology. Chapman & Hall.

See Also

rarc, raref2, raref

Examples

data(ef)
# No bootstrap statistics
rich(matrix=ef)

## Not run: 
# Bootstrap estimation based on 499 randomizations
rich(matrix=ef, nrandom=499)
## End(Not run)

Example output

rich version 1.0.1 is loaded
You can access the package vignette by typing vignette('rich_introduction') in the R console
$cr
[1] 121

$mr
[1] 10.4

$mrsd
[1] 4.938239

$bootCR
NULL

$bootMR
NULL

$nrandom
NULL

$cr
[1] 121

$mr
[1] 10.4

$mrsd
[1] 4.938239

$bootCR
 cr.obs  cr.boot cr.bcorr   cr.bias    cr.se   cr.lbn   cr.ubn
    121 90.48297  151.517 -30.51703 8.406419 135.0408 167.9933

$bootMR
   mr.obs  mr.boot mr.bcorr    mr.bias    mr.se   mr.lbn   mr.ubn
 79.63333 79.72712 79.53955 0.09378758 16.30183 47.58856 111.4905

$nrandom
[1] 499

rich documentation built on May 2, 2019, 5:25 p.m.