Fitting models
Data frame
In general, when fitting any SDM in R, one uses a data frame where each row is an observation or absence. The first column is typically a presence/absence column (0/1). This is followed by columns of the environmental variables for each presence/absence. For debugging, it is probably wise to keep the lat/lon columns and date values associated with the points and perhaps a id column. In the turtorial, we did not do that.
Fitting
Once one has the data frame, fitting will generally look like
fun(pres ~ ., data = df)
For example,
mod <- gam(pres ~ ., data = df)
To fit a generalized additive model.
Thus presence is defined as a function of all the variables in the data frame and fun()
specifies the model.
For maxnet, format is slightly different:
mod <- maxnet(pres, df %>% select(-pres))
Thus the 0/1 for each row is the first argument and the second argument is the environmental variables only.