Dear R developers,
I have seen that plogis silently ignores vector elements of lower.tail,
> plogis(q=0.5, location=1, lower.tail=TRUE)
[1] 0.3775407
> plogis(q=0.5, location=1, lower.tail=FALSE)
[1] 0.6224593
> plogis(q=c(0.5, 0.5), location=1, lower.tail=c(TRUE, FALSE))
[1] 0.3775407 0.3775407
For those familiar with psychological measurement: A use case of the above
function is the so-called Rasch model, where the probability that a person with
some specific ability (q) makes a correct (lower.tail=TRUE) or wrong response
(lower.tail=FALSE) to an item with a specific difficulty (location). A
vectorized version of plogis would enable to determine the likelihood of an
entire response vector in a single call. My current workaround is an
intermediate call to „Vectorize“.
I am wondering if the logical argument of lower.tail can be vectorized (?). I
see that this may be a substantial change in many places (basically, all p and
q functions of probability distributions), but in my understanding, it would
not break existing code which assumes lower.tail to be a single element. If
that’s not
possible/feasible, I suggest to issue a warning if a vector of length > 1 is
given in lower.tail. I am aware that the documentation clearly states that
lower.tail is a single boolean.
Thank you for your consideration.
With best wishes,
Matthias
[[alternative HTML version deleted]]
______________________________________________
R-devel@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-devel
