Hi -

I get the following error occasionally when I run gbm.step in the dismo:

--

Error in var(threshold.stats, use = "complete.obs") :

no complete element pairs

--

I also get several warnings such as:

--

3: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart =

etastart, :

algorithm did not converge

4: In glm.fit(x = X, y = Y, weights = weights, start = start, etastart =

etastart, :

fitted probabilities numerically 0 or 1 occurred

5: In cor(y_i, u_i) : the standard deviation is zero

--

Here is the line I use to run gbm.step:

gbm_object <- gbm.step(data=model.data, gbm.x=9:45, gbm.y=1,

family="bernoulli",

tree.complexity=5, learning.rate=0.001, bag.fraction=0.5)

The response variable is presence/absence (0/1) data for a bird species.

When I run this with the full data set for particular bird species the

data.frame "model.data" has 371 rows (plots) and then the error does not

appear but I still get several warnings. When I run it on a subset of

only 93 rows (I'd like to do k-fold partitioning) I get the error and

warnings mentioned above. For what it's worth, this problem data subset

has 88 presences and only 5 absences. It appears that when I run this

for bird species with more of a balance of presences and absences I

don't get any errors or warnings.

Any thoughts or pointers?

All the best,

Ned

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