Hello-

Upon searching the email archives and reading documentation I haven't found
what I'm looking for.  I have a dataset with a time/date stamp on a series
of geographic locations (lat/lon) associated with the movements of animals.
On some days there are numerous locations and some days there is only one
location.  Associated with each location is an indication that the quality
of the location is either "good", "poor", or "unknown".  For each animal, I
want to extract only one location for each day.  And I want the location
extracted to be nearest to 12pm on any given day, and highest quality
possible.  

So the order of priority for my extraction will be: 1. only one location per
animal each day; 2. the location selected be as close to 12pm as possible;
3. the selected location comes from the best locations available (ie. take
from pool of "good" locations first, or select from "poor" locations if a
"good" location isn't available, or "unknown" if nothing else is available).


 

I think aspect of this task that has me particularly stumped is how to
select only one location for each day, and for that location to be a close
to 12pm as possible.  

 

An example of my dataset follows:

 



DeployID

 

Date.Time

 

LocationQuality

Latitude

Longitude


STM05-1

 

28/02/2005 17:35

 

Good

-35.562

177.158


STM05-1

 

28/02/2005 19:44

 

Good

-35.487

177.129


STM05-1

 

28/02/2005 23:01

 

Unknown

-35.399

177.064


STM05-1

 

01/03/2005 07:28

 

Unknown

-34.978

177.268


STM05-1

 

01/03/2005 18:06

 

Poor

-34.799

177.027


STM05-1

 

01/03/2005 18:47

 

Poor

-34.85

177.059


STM05-2

 

28/02/2005 12:49

 

Good

-35.928

177.328


STM05-2

 

28/02/2005 21:23

 

Poor

-35.926

177.314

 

 

 

 

 

 

 

 

 

 

 

 

 

 


 

 

 

 

 

 

 

 

 

 

 

Many thanks for your input.  I'm using R 2.5.1 on Windows XP.  

 

Cheers,

 

Tim Sippel (MSc)

School of Biological Sciences

Auckland University

Private Bag 92019

Auckland 1020

New Zealand

+64-9-373-7599 ext. 84589 (work)

+64-9-373-7668 (Fax)

+64-21-593-001 (mobile)

 


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