collapse.fv
Collapse Several Function Tables into One
Combines several function tables (objects of class "fv")
into a single function table, merging columns that are identical
and relabelling columns that are different.
Usage
collapse.fv(..., same = NULL, different = NULL)Arguments
- ...
- Arguments which are objects of class
"fv", or a list of objects of class"fv". - same
- Character string or character vector specifying a column or columns,
present in each
"fv"object, that are identical in each object. This column or columns will be included only once. - different
- Character string or character vector specifying a column or columns,
present in each
"fv"object, that contain different values in each object. Each of these columns of data will be included, with labels that distinguish them from
Details
This command combines the data in several function tables
(objects of class "fv", see fv.object)
to make a single function table.
It is essentially a smart wrapper for
cbind.fv.
A typical application is to calculate the same summary statistic
(such as the $K$ function) for different point patterns,
and then to use collapse.fv to combine the results into a
single object that can easily be plotted. See the Examples.
The arguments ... should be function tables
(objects of class "fv", see fv.object)
that are compatible in the sense that they
have the same values of the function argument.
The argument same identifies any columns that are present
in each function table, and which are known to contain exactly
the same values in each table. This column or columns will be
included only once in the result.
The argument different identifies any columns that are present
in each function table, and which contain different numerical values
in each table. Each of these columns will be included, with labels
to distinguish them.
Columns that are not named in same or different will not
be included.
Value
- Object of class
"fv".
See Also
Examples
# generate simulated data
X <- replicate(3, rpoispp(100), simplify=FALSE)
names(X) <- paste("Simulation", 1:3)
# compute K function estimates
Klist <- lapply(X, Kest)
# collapse
K <- collapse.fv(Klist, same="theo", different="iso")
K