[R] density vs. mass for discrete probability functions

[Spencer Graves]

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 <sschreib using 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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