fossil (version 0.4.0)

jack1: First- and second-order jacknife estimators

Description

Computes the extrapolated species richness of a population using first- or second-order jacknife stimators

Usage

jack1(x, taxa.row = TRUE, abund = TRUE)
jack2(x, taxa.row = TRUE, abund = TRUE)

Arguments

x

a vector, matrix or data frame of positive integers or zero of any size

taxa.row

whether each row of the matrix is a different taxon; if so, value is set to TRUE

abund

If true, data is assumed to be abundance, if false, presence absence is assumed

Value

The value returned is the Jackknife estimated species diversity of the dataset in question.

Details

These functions compute the first and second-order jacknife species richness estimators, respectively. Both functions will accept a vector, matrix or data frame of any size made up of positive integers and zeros. Matrices are by default treated such that each row is a different taxon and each column is a sample or locality, however if they are arranged with the taxa as columns, change the argument taxa.row to FALSE. If the data is abundance based, abund should be set to TRUE. If abund is set to FALSE, the data will be converted to presence/absence if not already in that format. For single vectors/columns, taxa.row and abund are ignored.

References

Burnham, K.P. & W.S. Overton. 1978. Estimation of the size of a closed population when capture probabilities vary among animals. Biometrika 65, 623-633.

Burnham, K.P. & W.S. Overton. 1979. Robust estimation of population size when capture probabilities vary among animals. Ecology 60, 927-936.

Heltshe, J. & Forrester, N.E. 1983 . Estimating species richness using the jackknife procedure. Biometrics 39, 1-11.

See Also

ACE

Examples

# NOT RUN {
## sample vector
a<-c(0,5,1,1,2,0,0,1,0,0,8,45)
jack1(a)

## matrix format
a<-matrix(c(0,5,1,1,2,0,0,1,0,0,8,45),4,3)
jack1(a)
jack2(a)
jack2(a,abund = FALSE)

## presence absence matrix of the above abundance matrix
a<-matrix(c(0,1,1,1,1,0,0,1,0,0,1,1),4,3)
jack1(a)
jack2(a)
jack2(a, abund = FALSE)
# }