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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