Usage
occ.time(x, y, times = NULL, adjust = TRUE, gen.occ = FALSE,
perc = TRUE, nc.acc = FALSE, ...)occ.tmp(x, y, adjust=TRUE, gen.occ=FALSE, perc=TRUE,
nc.acc=FALSE, ...)
Arguments
x
Species data in matrix or database-format representing species occurrence at time step one or throughout a time series. The latter means that you have a table with three columns where the columns represent plots, species and
y
Species data in matrix or database-format representing species occurrence at time step two. Obsolete when times are given. Otherwise the same as for x applies.
times
A vector describing the timesteps which has to be coercible to a factor. If your data comes from a database and contains species records for different time-steps, just export the time information with the species data. If you have single matrices for each
adjust
Do not change the default behaviour (TRUE) unless you know what you do. Would spare some calculation time if set to FALSE, when your species data do not need adjustment, which means that in both or all time steps, there are exactly the same species and th
gen.occ
Triggers if general occurrence is regarded or specific occurrence. The latter is default (gen.occ=FALSE) and it means that it is calculated on which exact plots a species is changing. When set to TRUE only general occurence is regarded and it is calculate
perc
If output shall be in percentage of species. Defaults to TRUE.
nc.acc
Per default, species which are not changing on a plot are counted as single species (also when they do not change on more than one plot). This can be changed when setting nc.acc = TRUE. Then each occurence of species which has not changed is
...
Further arguments to functions.