On Sat, Sep 25, 2010 at 3:16 PM, Dennis Murphy wrote:
> Hi:
>
> On Sat, Sep 25, 2010 at 3:47 AM, Lorenzo Isella >wrote:
>
> > Dear All,
> > Suppose you are given two distributions (or better: two equally-sized
> lists
> > of data); how can you evaluate the difference between them?
>
Evaluate, f
On Sat, Sep 25, 2010 at 6:24 PM, Lorenzo Isella wrote:
> ld represent the distance as the proportion of maximum possible
>
>> distance, i.e. scaling it to be between 0 and 1.
>>
>> An example:
>> A and B have the same length (x), and you calculate the emd(A, B), which
>> is d.
>> Now you have to d
ld represent the distance as the proportion of maximum possible
distance, i.e. scaling it to be between 0 and 1.
An example:
A and B have the same length (x), and you calculate the emd(A, B), which
is d.
Now you have to determine the maximum distance between these two:
remembering the analogy of
On Sat, Sep 25, 2010 at 3:53 PM, Lorenzo Isella wrote:
> On 09/25/2010 03:23 PM, Rainer M Krug wrote:
>
>
>> Evaluate, for me, does not necessary mean "test if they are
>> significantly different", but rather to quantify the difference. If that
>> is what you are looking for, you could look at the
On 09/25/2010 03:23 PM, Rainer M Krug wrote:
Evaluate, for me, does not necessary mean "test if they are
significantly different", but rather to quantify the difference. If that
is what you are looking for, you could look at the "Earth Movers
Distance", where a package is available at R-forge
(
Hi:
On Sat, Sep 25, 2010 at 3:47 AM, Lorenzo Isella wrote:
> Dear All,
> Suppose you are given two distributions (or better: two equally-sized lists
> of data); how can you evaluate the difference between them?
> I need something like an overlap measure of the two (let us say 0 == no
> overlap an
Dear All,
Suppose you are given two distributions (or better: two equally-sized
lists of data); how can you evaluate the difference between them?
I need something like an overlap measure of the two (let us say 0 == no
overlap and 1== complete overlap). I should add that there is a 1-1
correspon
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