# [EM] Ossipoff's Weighted Webster...

Michael Ossipoff mikeo2106 at msn.com
Wed Jan 31 01:18:05 PST 2007

```Warren says:

Far as I can see, the simple method that starts out
http://rangevoting.org/NewAppo.html is identical with the method for
apportionment that Ossipoff now proposes ("What I mean by Weighed Webster")

I guess it’s necessary to take your word for that, because  didn’t try to
decypher the method and derivation at your website. If you had briefly and
concisely stated your method and its derivation, as I had requested, then
I’d have acknowledged it, assuming that it was really up at your website at
that time.

Warren continues:

glad to see Ossipoff has now come around to my point of view

Warren must be referring to the point of view that unbias is best achieved
by making each cycle’s s/q = 1. But wait, Warren only expressed disagreement
with that approach.

But did Warren post Weighted Webster at his website, while expressing
disagreement with the unbias approach on which it is based? Who knows.

Warren continues:

Note, the parameters Ossipoff is calling A and B can be deduced from the
number of states and total country population

Yesterday I told how to do that. And I told why least squares would almost
surely be more accurate.

Warren continues:

in which case his formula should simplify to become my formula. Warren D
Smith http://rangevoting.org

Some details:

>Ossipoff: R = (-1/A)*ln[(-1/A)*{exp(-A*b)-exp(-A*a)}] R is the rounding
>point between consecutive integers a & b. I hope that that expression can
>be simplified. --

response, use b=a+1

Of course that should be done.

, then {exp(-A*b)-exp(-A*a)} becomes exp(-A*a) * {exp(-A) - 1} now note R-a
is going to come out depending only on A, B and not on a,b just as in
http://rangevoting.org/NewAppo.html ----

So it does. A fixed rounding point (the same in all the cycles). I couldn’t
ask for more simplification than that.

By the way, I would propose that A be determined, for and from each census,
by the most accurate method available, which is probably least-squares.

Mike Ossipoff

```