Package 'MuMIn'

subset.model.selection 39
Arguments
Value
Note
x a model.selection object to be subsetted.
subset,select logical expressions indicating columns and rows to keep. See subset.
i,j indices specifying elements to extract.
recalc.weights logical value specyfying whether Akaike weights should be normalized across
the new set of models to sum to one.
recalc.delta logical value specyfying whether delta[IC] should be calculated for the new set
of models (this is not done by default).
... further arguments passed to [.data.frame.
A model.selection object containing only the selected models (rows). When columns are selected
(arguments select or j are provided), a plain data.frame is returned.
Unlike the method for data.frame, extracting with only one index (i.e. x[i]) will select rows
rather than columns.
To select rows according to presence or absence of the variables (rather than their value), a pseudofunction
has may be used, e.g. subset(x, has(a, !b)) will select rows with a and without b (this
is equivalent to !is.na(a) & is.na(b)). has can take any number of arguments. Importantly, the
has() notation cannot be used in the subset argument for dredge, where the variable names should
be given directly, with the same effect.
To select rows where one variable can be present conditional on the presence of other variable(s),
the function dc (dependency chain) can be used. dc takes any number of variables as arguments,
and allows a variable to be included only if all the preceding arguments are also included (e.g.
subset = dc(a, b, c) allows for models of form a, a+b and a+b+c but not b, c, b+c or a+c).
Author(s)
See Also
Kamil Bartoń
dredge, subset and [.data.frame for subsetting and extracting from data.frames.
Examples
data(Cement)
fm1