This is a wrapper to make it easier to perform
pointwise calculations with the summary functions
used in spatial statistics. An object of class "fv" is essentially a data frame
containing several different statistical estimates of the same
function. Such objects are returned by Kest and its
relatives.
For example, suppose X is an object of class "fv"
containing several different estimates of the Ripley's K function $K(r)$,
evaluated at a sequence of values of $r$.
Then eval.fv(X+3) effectively adds 3 to
each function estimate in X, and returns
the resulting object.
Suppose X and Y are two objects of class "fv"
which are compatible (in particular they have the same vector
of $r$ values). Then
eval.im(X + Y) will add the corresponding function values in
X and Y, and return the resulting function.
In general, expr can be any expression involving
(a) the names of objects of class "fv", (b) scalar
constants, and (c) functions which are vectorised.
See the Examples.
First eval.fv determines which of the variable names
in the expression expr refer to objects of class "fv".
Each such name is replaced by a vector containing the function values.
The expression is then evaluated. The result should be a vector;
it is taken as the new vector of function values.
The expression expr must be vectorised.
There must be at least one object of class "fv" in the expression.
All such objects must be compatible.