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.
## S3 method for class 'fv' collapse(object, ..., same = NULL, different = NULL) ## S3 method for class 'anylist' collapse(object, ..., same = NULL, different = NULL)
object |
An object of class |
... |
Additional objects of class |
same |
Character string or character vector specifying a column or columns,
present in each |
different |
Character string or character vector specifying a column or columns,
present in each |
This is a method for the generic function
collapse
.
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 object
and ...
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.
The arguments same
and different
can be NULL
,
or they can be character vectors containing the names
of columns of object
. The argument different
can be
one of the abbreviations recognised by fvnames
.
Object of class "fv"
.
Adrian Baddeley Adrian.Baddeley@curtin.edu.au and Rolf Turner r.turner@auckland.ac.nz
# generate simulated data X <- replicate(3, rpoispp(100), simplify=FALSE) names(X) <- paste("Simulation", 1:3) # compute K function estimates Klist <- anylapply(X, Kest) # collapse K <- collapse(Klist, same="theo", different="iso") K
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