opticut: Likelihood Based Optimal Partitioning and Indicator Species Analysis

Likelihood based optimal partitioning for indicator species analysis and more. Finding the best binary partition for each species based on model selection, possibly controlling for modifying/confounding variables as described in Kemencei et al. (2014).

Versions

Install stable version from CRAN:

install.packages("opticut")

Install development version from GitHub:

devtools::install_github("psolymos/opticut")

User visible changes in the package are listed in the NEWS file.

Report a problem

Use the issue tracker to report a problem.

Typical workflow

library(opticut)

## --- community data ---
y <- cbind(
    Sp1 = c(4,6,3,5, 5,6,3,4, 4,1,3,2),
    Sp2 = c(0,0,0,0, 1,0,0,1, 4,2,3,4),
    Sp3 = c(0,0,3,0, 2,3,0,5, 5,6,3,4))

## --- stratification ---
g <-      c(1,1,1,1, 2,2,2,2, 3,3,3,3)

## --- find optimal partitions for each species ---
oc <- opticut(y, strata = g, dist = "poisson")
summary(oc)
#  Multivariate opticut results, comb = rank, dist = poisson
#
#  Call:
#  opticut.default(Y = y, strata = g, dist = "poisson")
#
#  Best supported models with logLR >= 2:
#      split assoc      I  mu0  mu1 logLR      w
#  Sp3   2 3    ++ 0.6471 0.75 3.50 4.793 0.6962
#  Sp2     3   +++ 0.8571 0.25 3.25 9.203 0.9577
#  2 binary splits
#  1 species not shown

## --- visualize the results ---
plot(oc, cut = -Inf)

## --- quantify uncertainty ---
uc <- uncertainty(oc, type = "asymp", B = 999)
summary(uc)
#  Multivariate opticut uncertainty results
#  type = asymp, B = 999, level = 0.95
#
#      split R      I   Lower  Upper
#  Sp1   1 2 1 0.2860 0.02341 0.5668
#  Sp3   2 3 1 0.6218 0.21456 0.8813
#  Sp2     3 1 0.8274 0.51229 0.9680

Dynamic documents with opticut

Here is a minimal Rmarkdown example: Rmd source, knitted PDF.

References

Kemencei, Z., Farkas, R., Pall-Gergely, B., Vilisics, F., Nagy, A., Hornung, E. & Solymos, P. (2014): Microhabitat associations of land snails in forested dolinas: implications for coarse filter conservation. Community Ecology 15:180--186. [link, PDF]