All functions

add.distance()

Add distance information to resampling objects

as.represampling() print(<represampling>) is_represampling()

Resampling objects with repetition, i.e. sets of partitionings or boostrap samples

as.resampling() validate.resampling() is.resampling() print(<resampling>)

Resampling objects such as partitionings or bootstrap samples

as.tilename() as.character(<tilename>) as.numeric(<tilename>) print(<tilename>)

Alphanumeric tile names

dataset_distance()

Calculate mean nearest-neighbour distance between point datasets

err_default()

Default error function

get_small_tiles()

Identify small partitions that need to be fixed.

partition_cv()

Partition the data for a (non-spatial) cross-validation

partition_cv_strat()

Partition the data for a stratified (non-spatial) cross-validation

partition_disc() partition_loo()

Leave-one-disc-out cross-validation and leave-one-out cross-validation

partition_factor()

Partition the data for a (non-spatial) leave-one-factor-out cross-validation based on a given, fixed partitioning

partition_factor_cv()

Partition the data for a (non-spatial) k-fold cross-validation at the group level

partition_kmeans()

Partition samples spatially using k-means clustering of the coordinates

partition_tiles()

Partition the study area into rectangular tiles

plot(<represampling>) plot(<resampling>)

Plot spatial resampling objects

represampling_bootstrap()

Non-spatial bootstrap resampling

represampling_disc_bootstrap()

Overlapping spatial block bootstrap using circular blocks

represampling_factor_bootstrap()

Bootstrap at an aggregated level

represampling_kmeans_bootstrap()

Spatial block bootstrap at the level of spatial k-means clusters

represampling_tile_bootstrap()

Spatial block bootstrap using rectangular blocks

resample_factor()

Draw uniform random (sub)sample at the group level

resample_strat_uniform()

Draw stratified random sample

resample_uniform()

Draw uniform random (sub)sample

sperrorest-package

Spatial Error Estimation and Variable Importance

sperrorest()

Perform spatial error estimation and variable importance assessment in parallel

summary(<represampling>) summary(<resampling>)

Summary statistics for a resampling objects

summary(<sperrorestreperror>) summary(<sperrorest>) print(<sperrorestimportance>) print(<sperroresterror>) print(<sperrorestreperror>) print(<sperrorest>) print(<sperrorestbenchmarks>) print(<sperrorestpackageversion>)

Summary and print methods for sperrorest results

summary(<sperroresterror>)

Summarize error statistics obtained by sperrorest

summary(<sperrorestimportance>)

Summarize variable importance statistics obtained by sperrorest

tile_neighbors()

Determine the names of neighbouring tiles in a rectangular pattern