On 2019-03-15 08:37, peter dalgaard 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.
Correct. That's for clearing up my "mud". sg
-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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