sim.yo(x, coord = NULL, method = "(2*a)/((2*a) + b + c)", dn = NULL,
normalize = FALSE, listin = FALSE, listout = FALSE, ...)
data.frame
with
first three columns representing plots, species and data.frame
with two columns containing the coordinate values of the sampling units. If given, it triggers the simultaneous calculation of the geographical distances between the sampling units, the coordinates of virtual centre-points betweesim
for more examples and general explanations.coord
!= NULL. If specified, the output does only contain similarities between neighboring plota
, b
and c
which are calculated in the process should be normalized to 100% (per row, which means per plot comparison). If normalize = TRUE an asymmetric index must x
is given in database (list) format this must be set to TRUE (there is no automatic detection of the format)dist
-object set this to TRUE. Output is automatically given in database-format, when coord
is specified.dist
is returned. If listout = TRUE, a data.frame
is returned with 7 columns giving the names of the compared plots in the first two and the calculated similarity measure in the third column. The rest of the columns give the values for a, b, c,
and d
(in this order). Naming of the first three columns can be changed but defaults to NBX
(one of the compared plots), NBY
(the other one), used index
(the values of the calculated index). If coord
!= NULL, the following columns are given in addition and the columns a:d
shift to the end of the data.frame.sim
already allows for the calculation of a large variety of binary similarity coefficients. But just in case you found or thought of an alternative this function is provided. For details regarding similarity indices see sim
. You have to give your formula in quotation marks like this: "(2*a)/((2*a) + b + c)".vegdist
, designdist
, dist.binary
,
dsvdis
, dist
for other dissimilarity coefficients, and sim
for a variety of formulae for similarity coefficients.data(abis)
##calculate the default Sørensen index
abis.soer <- sim.yo(abis.spec)
##calculate a custom similarity index
abis.sim <- sim.yo(abis.spec, method="(2*a)/((a) + b + c)")
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