Rmodels must be functions or objects that have a predict
method, such as lm objects. Models defined as functions will
be called once with an expression of the form y <- f(X) where
X is the design of experiments, i.e. a data.frame with
p columns (the input factors) and n lines (each, an
experiment), and y is the vector of length n of the
model responses (we say that such functions are vectorized).
If the model is external to R, for instance a computational code, it
must be analyzed with the decoupled approach, see
decoupling. This approach can also be used on Rmodels
that doesn't fit the specifications.
src), PCC and PRCC (pcc).morris).sb).sobol), and Saltelli's
scheme (2002) to compute first order and total indices
with a reduced cost (sobol2002).fast99).testmodels) and template file generation
(template.replace).