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TODO.md

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TO DO

v_{} functions

Functions to deal with raster data representing environmental information

import4D: rename to v_import

Changes in arguments:

  • raster.template -> rename to v.template
  • raster.template.crs -> rename to v.template.crs
  • folder -> rename to v.folder
  • dynamic.vars -> rename to v.dynamic
  • static.vars -> rename to v.static
  • times -> rename to v.times
  • vars.crs -> rename to
  • to.data.frame -> remove this option and keep it in a helper function

importTIF: include in v_import

importASC: include in v_import

o_{} functions

Functions to deal with occurrence data

o_make_training()

Changes in argumets:

  • variables -> find proper name for this argument after v_{} functions are ready
  • n -> rename to n.background
  • presence.only -> remove this option
  • background -> remove this option
  • restricted.background -> remove this option, link it to non-null restricted.background.buffer
  • restricted.background.buffer -> restriction.radius? restrict.to.buffer?
  • thinning -> remove this option, link it to non-null minimum.distance
  • minimum.distance -> rename to same as in o_thinning(), maybe min.dist

o_thinning()

This function should be paired with the function to test spatial correlation (testSpatialCorrelation()). Maybe o_thinning() should be s_thinning() and testSpatialCorrelation() should be s_spatial_cor(), so if there are variables with a high spatial correlation for the presences, the user can apply thinning and/or remove the offending variables. This should be done most likely before assessing multicollinearity.

Changes in arguments:

  • variables -> find proper name for this argument after v_{} functions are ready
  • minimum.distance -> rename to min.dist
  • random.start -> remove this option, link to a non-null random.seed
  • seed -> rename to random.seed

s_{} functions

Functions for variable selection and reduction of multicollinearity