I am trying to use R to do a weighted GAM with PA (presence/random) as the
response variable (Y, which is a 0 or a 1) and ASPECT (values go from
0-3340), DEM (from 1500-3300), HLI (from 0-5566), PLAN (from -3 to 3),
PROF (from -3 to 3), SLOPE (from 100-500) and TRI (from 0-51) as
predictor variables (Xs).  I need to weight each observation by its WO
value (from 0.18 to 0.98).  I have specified the following models in R
(see below), but I can't figure out what the R reported errors plainly
mean. One of the errors seems to tell me my dataset is too big (it's
109,729 rows by 16 columns) - is this possible?  Given what I am trying to
accomplish (a weighted, logistic GAM with 7 variables), am I specifying my
model correctly?  I would like to attach my dataset (it's 2,064 KB
as a WinZip file), but I don't know if it'll go through to the list given
the HTML & attachment contraints of the list...  I even tried a weighted,
logistic GLM with the seven variables to see if that would work and if so,
perhaps it was a GAM problem.  I also tried a logistic, weighted GAM with
one variable to see if that would work.  My next step while I wait to
hear back from the list is to try a dummy dataset that is small to see if
a weighted, logistic GAM with seven variables will work at all or if I am
speciying the model correctly.  Would anyone be willing to have my dataset
sent so they can check it out if that would help solve the issue?  Thank you!
Hillary ([EMAIL PROTECTED])

> # trial, all, weighted
> topo8 <- gam(PA ~ s(SLOPE10) + s(ASPECT10) + s(GYADEMPLUS) + s(TRI) +
s(HLI) + s(PLAN10) + s(PROF10), family=binomial, data=topox, weights = w0)
Warning in eval(expr, envir, enclos) : non-integer #successes in a
binomial glm!
Error: cannot allocate vector of size 60865 Kb

> topo9 <- glm(PA ~ SLOPE10 + ASPECT10 + GYADEMPLUS + TRI + HLI + PLAN10 +
PROF10, family=binomial, data=topox, weights = w0)
Warning in eval(expr, envir, enclos) : non-integer #successes in a
binomial glm!

> # trial, weighted, slope only
> topo10 <- gam(PA ~ s(SLOPE10), family=binomial, data=topox, weights =
w0)
Warning in eval(expr, envir, enclos) : non-integer #successes in a
binomial glm!

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