Error in terms.formula(formula, data = data) :
invalid term in model formula
Error in predict(model.bm, Data[, expl_var_names, drop = FALSE], on_0_1000 = TRUE) :
error in evaluating the argument 'object' in selecting a method for function 'predict': Error: object 'model.bm' not found
After lots of digging in the source code of BIOMOD I discovered what happened and how to fix it.
The line where the error was occurring looked like this:
model.sp <- try(randomForest(formula = makeFormula(resp_name, head(Data), "simple", 0), data = Data[calibLines, ], ntree = Options@RF$ntree, importance = FALSE, norm.votes = TRUE, strata = factor(c(0, 1)), nodesize = Options@RF$nodesize, maxnodes = Options@RF$maxnodes))
As you can see a formula is created from our data. The generated formula looked like this:
654987634 ~ 1 + nitrate_mean + par_mean + sst_mean + sst_range
The number 654987634 is my response variable name that I set when calling BIOMOD_FormatingData which apparently has been added to the Data data.frame as the first column.
Solution: adding a letter prefix to my response variable name fixed my issue.
Lessons learned:
- It's incredibly useful that you can take a look at external source code in an RSession by typing its name, for iternals you add the package name and 3 double dots e.g. biomod2:::.Biomod.Models. Generics functions can be fetched with getMethod e.g. getMethod(biomod2::predict, signature="RF_biomod2_model")
- Read the docs very carefully: this is the description for resp.name: response variable name (character). The species name.
- An assertion in BIOMOD_FormatingData would have saved me an hour or two. But note that a naive check like is.character(resp.name) wouldn't work in this case, because once the formula is made it isn't a character anymore.
- Adding more diagnostic information in your error messages saves people time. If the generated formula would have been printed as well then I would probably have noticed the issue directly.
- Libraries make you win time, but you lose some as well.
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