designdist from library vegan.
The methods can be specified by name or by the distance measure number they were
given in Table 29.10; e.g. Steinhaus index = "D8".
Minkowski's distance requires an additional specification for power.
The default is power = 2 which makes the measure equivalent to Euclidean distance.get.dist(data, method, minkowski.power = 2)"matching", "rogers", "jaccard.pa", "sorenson", "kulkczynski.pa", "ochiai",
"gower", "steinhaus", "kulkczynski.q", "jaccard.q", "euclidean", "rel.euclidean",
"manhattan", "czekanminkowski.power = 2 which makes the measure equivalent to Euclidean distance.class(dist).distlibrary(vegan)
data(varespec)
get.dist(varespec,method="steinhaus")Run the code above in your browser using DataLab