Hello,
Yes, there is even an old discussion on this on r-devel, dated August,
10 2013.
See [1].
[1]
https://r-project.markmail.org/search/?q=broken-link-in-docs-for-Binormial-functions#query:broken-link-in-docs-for-Binormial-functions+page:1+mid:rf6tbiokcdyai6el+state:results
Hope this helps,
Rui Barradas
Às 14:21 de 15/03/2019, Stefan Schreiber escreveu:
Thank you Peter and Spencer. That clears things up. Also since no one
responded the second part of my question, I'm still wondering if it was
noted that there is a hyperlink in the dbinom help file (?dbinom) that
isn't directing correctly?
Stefan
On Fri, Mar 15, 2019, 07:37 peter dalgaard, <pda...@gmail.com> wrote:
Mathematically, you can bring discrete and continuous distributions on a
common footing by defining probability functions as densities wrt. counting
measure. You don't really need Radon-Nikodym derivatives to understand the
idea, just the fact that sums can be interpreted as integrals wrt counting
measure, hence sum_{x in A} f(x) and int_A f(x) dx are essentially the same
concept.
-pd
On 15 Mar 2019, at 01:43 , Stefan Schreiber <sschr...@ualberta.ca>
wrote:
Dear R users,
While experimenting with the dbinom() function and reading its
documentation (?dbinom) it reads that "dbinom gives the density" but
shouldn't it be called "mass" instead of "density"? I assume that it
has something to do with keeping the function for "density" consistent
across discrete and continuous probability functions - but I am not
sure and was hoping someone could clarify?
Furthermore the help file for dbinom() function references a link
(http://www.herine.net/stat/software/dbinom.html) but it doesn't seem
to land where it should. Maybe this could be updated?
Thank you,
Stefan
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Peter Dalgaard, Professor,
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