sperrorest()now runs in parallel using all available cores.
runreps()are now doing the heavy lifting in the background. All modes are now running on the same code base. Before, all parallel modes were running on different code implementations.
pbmclapply()on Unix and
multicore, etc.). Default option to
cluster. This is also the overall default mode for
sequential: sequential execution using
sperrorest(). Specifying a range like
repetition = 1:10will also stay valid.
sperrorest::parallel-modescomparing the various parallel modes.
sperrorest::custom-pred-and-model-functionsexplaining why and how custom defined model and predict functions are needed for some model setups.
do_tryargument has been removed.
err.trainarguments have been removed because they are all calculated by default now.
sperroresterrored during the predict step when this case occured. Now, this is accounted for and an informative message is given.
parsperrorest(): This function lets you exexute
sperrorest() in parallel. It includes two modes (
par.mode = 1 and
par.mode = 2) which use different parallelization approaches in the background. See
?parsperrorest() for more details.
partition.factor.cv(): This resampling method enables partitioning based on a given factor variable. This can be used, for example, to resample agricultural data, that is grouped by fields, at the agricultural field level in order to preserve spatial autocorrelation within fields.
benchmark item to returned object giving information about execution time, used cores and other system details.
Changes to functions:
sperrorest(): Change argument naming.
err.unpooled is now
err.pooled is now
parsperrorest(): Change order and naming of returned object
sperrorestlist is now ordered as follows:
add package NEWS
add package vignette ->
vignette("sperrorest-vignette", package = "sperrorest")
package is now ByteCompiled
Github repo of
sperrorest now at https://github.com/pat-s/sperrorest/