NEWS.md

In rvalavi/blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation

version 3.1.3

• the biomod2 and gstat packages are added to the Suggests section
• Some minor edits in messages

version 3.1.2

• The iteration in cv_spatial and spatialBlock is increased to 100 to make the result matches with v2.1.4
• Removed the requirement of C++11
• Some warnings are added for the miss use of the column argument

version 3.1.1

• some internal fix.
• the extend parameter is now added to spatialBlock and the function now uses cv_spatial internally.
• the user_blocks in cv_spatial is restricted to random and predefined and systematic selection.
• no raster package dependency

version 3.1.0

• the result of the cv_spatial function for square blocks now matches the one of version 2 function spatialBlock (i.e. fold assignment starts from top-right corner; this is not the case for hexagon blocks)
• square spatial blocks can be expanded to ensure no points fall outside the border of the blocks. This can be controlled by extend parameter now.

version 3.0.3

• fixing a bug in counting records in the reporting of cv_spatial

version 3.0.2

• fixing fold numbering of cv_spatial to reproducibility of earlier versions

version 3.0.1

• Massive performance improvement in the C++ code of cv_nndm function for large datasets

version 3.0

• Dependency to rgdal and rgeos are removed, and overall less dependency
• Function names have been changed, with all functions now starting with cv_
• The old functions (v2.x) still work to allow appropriate time for adapting the new code
• The CV blocking functions are now: cv_spatial, cv_cluster, cv_buffer, and cv_nndm
• Spatial blocks now support hexagonal (default), rectangular, and user-defined blocks
• A fast C++ implementation of Nearest Neighbour Distance Matching (NNDM) algorithm (Milà et al. 2022) is now added
• The NNDM algorithm can handle species presence-background data and other types of data
• The cv_cluster function generates blocks based on kmeans clustering. It now works on both environmental rasters and the spatial coordinates of sample points
• The cv_spatial_autocor function now calculates the spatial autocorrelation range for both the response (i.e. the binary or continuous data) and a set of continuous raster covariates
• The new cv_plot function allows for visualization of folds from all blocking strategies using ggplot facets
• The terra package is now used for all raster processing and supports both stars and raster objects, as well as files on disk.
• The new cv_similarity provides measures on possible extrapolation to testing folds

version 2.1.4

• fixed CRAN error for ggplot guide
• added rgdal as a suggest
• changed the crs of raster data in the package to avoid datum warnings

version 2.1.3

• fix the warning for spatialBlock function on geographic coordinate system

version 2.1.2

• predefined folds from user-defined blocks are noe accepted
• add seed argument to spatialBlock to have consistent results where needed

version 2.1.0

• snowfall package for parallel processing is replaces by future.apply package; #7
• future.apply, shiny, shinydashboard, geosphere and ggplot2 packages moved to SUGGESTION packages. These are not install by default and the user is asked if needed. #7
• RStoolbox is no longer used for clustering
• an argument is added to envBlock function for sampling from raster layers
• no dependency on sp package any more
• doParallel = FALSE by default in spatialAutoRange function

version 2.0.1

• print() and cat() are removed from the functions and verbose argument is added instead

version 2.0.0

• most of the underlying functions are migrated to sf functions;
• the parallel processing changed from foreach to snowfall;
• the species argument in spatialBlock function accepts multi-class responses to find evenly distributed records in train and test folds;

version 1.1.0

• change spatialAutoRange function to accepts rasters with low number of pixels; #2
• the maskBySpecies = FALSE in spatialBlock function is no longer supported;
• the numLimit argument in spatialBlock function is only accepts numeric values, and 0 means searching for evenly distributed folds;

version 1.0.1

• add speciesData to spatialAutoRange function;

rvalavi/blockCV documentation built on Feb. 3, 2024, 7:26 a.m.