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In general, models using more predictors have better performance, but there's a trade-off, as including predictors with missing data will lead to missing areas in resulting maps. Mosaic mitigates for this problem by combining multiple maps. Missing values in the first map are replaced with values from the second map, missing values in the first two maps are replaced from the third, and so on. The new composite map will have data for all cells that any of the source maps have data.

Usage

mosaic(mapids, resources = NULL, local = FALSE, trap = FALSE, comment = NULL)

Arguments

mapids

Vector of two or more map ids to process, with preferred maps listed before less-preferred ones

resources

Slurm launch resources. See launch. These take priority over the function's defaults.

local

If TRUE, run locally; otherwise, spawn a batch run on Unity

trap

If TRUE, trap errors in local mode; if FALSE, use normal R error handling. Use this for debugging. If you get unrecovered errors, the job won't be added to the jobs database. Has no effect if local = FALSE.

comment

Optional launch / slurmcollie comment

Details

A shapefile will be produced with map id, fit id, CCR, and Kappa for underlying cells.

Maps must all be from the same site.