JoSAE
, rsae
and sae
to
the Suggests-Field in file DESCRIPTION.auxiliaryWeights
to class
saeObj
, allowing for weighting the auxiliary information
for incomplete spatial support. This is inspired by package
forestinventory
.This lead to refactoring the functions used in method
predict
. I have nearly halved the lines of code in these
functions, they are now much easier to read, understand and
maintain.
The return value predict() has changed, it is giving the (pseudo) small area estimator and the (pseudo) synthetic estimator as well but not the attributes hinting to Mandallaz’ publications
If you don’t care about weights and (pseudo) small area estimator and
the (pseudo) synthetic estimators, you might want to stick with the old
predict method from version 1.0.0. You can use
predict(..., version = "1.0.0)
or set options(maSAE_version = "1.0.0")
to do so. The
predictions for the extended (pseudo) synthetic estimator and its
variance are identical for version 1.0.0 and 2.0.0. This is ensured by
tests in runit_tests/runit-v1.R.
bind_data
to coerce different sampling
phase data into a suitable data.frame
.maASE
and
forestinventory
.NEWS.md
file to track changes to the
package.