Just guessing, would the following help?

list1 <- c("john", "eric", "steve", "john", "eric", "scott", "john")
list2 <- c("john", "john", "john", "eric", "eric", "steve", "scott")
max(rle(list1)$lengths)
max(rle(list2)$lengths)

Clint

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On Wed, 30 Oct 2013, Adams, Jean wrote:

You should cc r-help on all correspondence so everyone can follow the
thread.

Clearly I'm missing something.  Perhaps others are, too.  I don't  know
what you mean by "a score based on the co-localization of names" unless you
give an example.

Jean


On Wed, Oct 30, 2013 at 10:34 AM, Stevan Lauriault <
stevan.lauria...@gmail.com> wrote:

It would depend on the algorithm.  Which is why I'm writing.  I'm asking
if anyone knows of a preexisting algorithm that would calculate a score
based on the co-localization of names.

S





On Wed, Oct 30, 2013 at 10:56 AM, Adams, Jean <jvad...@usgs.gov> wrote:

What would the calculated score be for the example you give?

Jean


On Wed, Oct 30, 2013 at 7:03 AM, Stevan Lauriault <
stevan.lauria...@gmail.com> wrote:

Hi,

I'm looking for a function that takes a list and calculates a score
based on
how well "like attracts like".
For example:

list1 <- c(john, eric, steve, john, eric, scott, john)
list2 <- c(john, john, john, eric, eric, steve, scott)

score(list1) < score(list2)

Both lists are composed of the same names and frequency of each
name.

Not sure how else to put it.  I am relatively new to R.  Have tried the
modularity function, but can't seem to get it to work for this purpose.


Any help is appreciated.

Steve

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