iSCAM assessments often make use of multiple indices of abundance. The data object and MPs currently only make use of a single index. combiSCAMinds is a function that creates a single index from many using linear modelling. It is a simple way of providing initial calculations of management recommendations and it should be noted that this process is important and in a real application would require due diligence (ie peer reviewed data workshop).
iSCAMinds(idata, Year, fleeteffect = T)
List: the indices recorded in a read from an iSCAM data folder, e.g. replist$data$indices
Integer vector: the years of the data object ie Data@Year
Logical: should a fleet effect be added to the linear model?