NP. Glad to help.
On Wed, Aug 13, 2014 at 5:25 PM, Dmitriy Lyubimov <[email protected]> wrote: > Aha. just what was needed. Now nonsensical co-occurrences are filtering out > too. Thank you. > > > On Wed, Aug 13, 2014 at 4:59 PM, Ted Dunning <[email protected]> > wrote: > > > I use k_11 / (k_11 + k_12) > k_21 / (k_21 + k_22) for the sign. > > > > > > > > > > On Wed, Aug 13, 2014 at 4:45 PM, Dmitriy Lyubimov <[email protected]> > > wrote: > > > > > perhaps something along the lines p(A and B) > p(notA and notB)? > > > > > > > > > On Wed, Aug 13, 2014 at 4:42 PM, Dmitriy Lyubimov <[email protected]> > > > wrote: > > > > > > > Hello, > > > > > > > > i would be greatful for a hint for a following problem here in > > > > cooccurrence analysis. It may be not most practical one but it > appeared > > > in > > > > the test. > > > > > > > > The problem is that LLR tests for independence. As such, it would > give > > > > high scores for negatively correlated events too. E.g. say countA = > > 91, > > > > countB=91, countA&B=1, total = 213 produces sky-high llr of 139.33. > > > > However, in this situations these events avoid each other (something > we > > > are > > > > not looking for) rather than highly likely to co-occur (somethng we > are > > > > looking for). > > > > > > > > Is there a quick test to filter out negatively co-occuring events? > > > > > > > > thanks. > > > > -d > > > > > > > > > >
