Submodel selection using dredge and gam (mgcv)

Hi Arnaud,
please read ?dredge -> "Details" -> "Subsetting", where this is explained.


On 2014-11-12 15:19, Arnaud Mosnier wrote:

Hi Kamil,

Thanks for your answer. In fact, I already tried something with
operators in such a way you advise, but it seems more complicated due to
the use of the s() and ti() operators.

Can you provide a solution for the following example ?

library(mgcv)
set.seed(2)
dat <- gamSim(1,n=400,dist="normal",scale=2)

bt <- gam(y~s(x0)+s(x1)+ti(x0,x1), data=dat,method="ML")

library(MuMIn)

# this does not work
dredge(bt, subset = (!(x0,x1) | (x0 & x1)))
dredge(bt, subset = (!ti(x0,x1) | (s(x0) & s(x1))))

Cheers,

Arnaud


2014-11-11 4:11 GMT-05:00 Kamil Barto? <kamil.barton at o2.pl
<mailto:kamil.barton at o2.pl>>:


    Hi Arnaud,
    your question has in fact nothing to do with gam or model selection.
    What you are asking is: what is the logical expression that yields
    True when AB is False or both A and B are True. Now replace the
    words with operators (!AB | (A & B)) and voil?.

    See also:
    help("Logic", "base")
    fortunes::fortune(350)

    best,
    kamil



    On 2014-11-10 21:26, Arnaud Mosnier wrote:

        Hi,

        I want to use dredge to test several gam submodels including
        interactions.
        I tried to find a way in order to keep models with interaction
        only if
        the single variables occurring in the interaction are also
included.

        i.e.: for
           y~s(x0)+s(x1)+ti(x0, x1)

        I want to keep
        y ~ s(x0)
        y ~ s(x1)
        y ~ s(x0) + s(x1)
        y ~ s(x0) + s(x1) + ti(x0,x1)

        and I want to remove

        y ~ s(x0) + ti(x0,x1)
        y ~ s(x1) + ti(x0,x1)
        y ~ ti(x0,x1)


        I know that I should use the "subset" option of the dredge
function.
        However, I can not find the correct matrix / expression to
        obtain what I
        need !


        Here a small example.

        ################

        # Create some data (use mgcv example)
        library(mgcv)
        set.seed(2)
        dat <- gamSim(1,n=400,dist="normal",__scale=2)

        # Create the global gam model
        # Here a model with interaction. Note the use of ti()
        bt <- gam(y~s(x0)+s(x1)+s(x2)+s(x3)+__ti(x1,x2),
        data=dat,method="ML")

        # Use dredge to test sub-models
        library(MuMIn)
        print(modstab <- dredge(bt))

        # Here the 11th model include the interaction but do not include
the
        single variables x1 and x2
        # ... I want to avoid that kind of model.
        get.models(modstab, subset = 11)

        ################


        Any help would be appreciated !

        Arnaud