spatial_block_cv {spatialsample} | R Documentation |
Spatial block cross-validation
Description
Block cross-validation splits the area of your data into a number of grid cells, or "blocks", and then assigns all data into folds based on the blocks their centroid falls into.
Usage
spatial_block_cv(
data,
method = c("random", "snake", "continuous"),
v = 10,
relevant_only = TRUE,
radius = NULL,
buffer = NULL,
...,
repeats = 1,
expand_bbox = 1e-05
)
Arguments
data |
An object of class |
method |
The method used to sample blocks for cross validation folds.
Currently supports |
v |
The number of partitions for the resampling. Set to |
relevant_only |
For systematic sampling, should only blocks containing data be included in fold labeling? |
radius |
Numeric: points within this distance of the initially-selected
test points will be assigned to the assessment set. If |
buffer |
Numeric: points within this distance of any point in the
test set (after |
... |
Arguments passed to |
repeats |
The number of times to repeat the V-fold partitioning. |
expand_bbox |
A numeric of length 1, representing a proportion to expand
the bounding box of |
Details
The grid blocks can be controlled by passing arguments to
sf::st_make_grid()
via ...
. Some particularly useful arguments include:
-
cellsize
: Target cellsize, expressed as the "diameter" (shortest straight-line distance between opposing sides; two times the apothem) of each block, in map units. -
n
: The number of grid blocks in the x and y direction (columns, rows). -
square
: A logical value indicating whether to create square (TRUE
) or hexagonal (FALSE
) cells.
If both cellsize
and n
are provided, then the number of blocks requested
by n
of sizes specified by cellsize
will be returned, likely not
lining up with the bounding box of data
. If only cellsize
is provided, this function will return as many blocks of size
cellsize
as fit inside the bounding box of data
. If only n
is provided,
then cellsize
will be automatically adjusted to create the requested
number of cells.
Value
A tibble with classes spatial_block_cv
, spatial_rset
, rset
,
tbl_df
, tbl
, and data.frame
. The results include a column for the
data split objects and an identification variable id
.
References
D. R. Roberts, V. Bahn, S. Ciuti, M. S. Boyce, J. Elith, G. Guillera-Arroita, S. Hauenstein, J. J. Lahoz-Monfort, B. Schröder, W. Thuiller, D. I. Warton, B. A. Wintle, F. Hartig, and C. F. Dormann. "Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure," 2016, Ecography 40(8), pp. 913-929, doi: 10.1111/ecog.02881.
Examples
spatial_block_cv(boston_canopy, v = 3)