10 Use Caution in Terminology!
10.1 “Optim”
In the world of R, an algorithm may use the name “optim” if its core/workhorse function is either one of
- Brent–Dekker algorithm in one-dimensional optimization, via function
stats::optimize()and/or its aliasstats::optimise(). - Nelder-Mead, quasi-Newton, conjugate-gradient algorithms in higher-dimensional optimization, via function
stats::optim().
Otherwise, it is strongly advised not to name an algorithm using the word “optim”. In earlier publications, a junior author referred to the methodology in Section 6.5.2 using the term “optim”. This is a wrong practice of nomenclature, indicating a misunderstanding of R terminology. We now name this package maxEff (v0.2.1), meaning “maximum effect size”.
10.2 “Split” vs. “Partition”
In the world of R, the term “split” often indicates a process without randomness, e.g., the S3 generic function base::split() (R Core Team 2025) divides the input object into multiple groups specified by a pre-set formula or factor via the parameter f.
The term “partition”, on the contrary, often indicates either of the following
- a process with randomness, e.g.,
- the training/test partition in
caret::createDataPartition()(Kuhn 2008, v7.0.1).
- the training/test partition in
- an algorithm to maximize/minimize an objective function, e.g.,
- the recursive partitioning in
rpart::rpart()(Therneau and Atkinson 2025, v4.1.24) andparty::ctree()(Hothorn, Hornik, and Zeileis 2006, v1.3.18), - the data clustering in
?cluster::partition.object(Maechler et al. 2025, v2.1.8.1).
- the recursive partitioning in