Rich:   You could try quantile regression from the quantreg package.

Brian


Brian S. Cade, PhD

U. S. Geological Survey
Fort Collins Science Center
2150 Centre Ave., Bldg. C
Fort Collins, CO  80526-8818

email:  brian_cade@usgs.gov
tel:  970 226-9326



From:
Rich Shepard <rshepard@appl-ecosys.com>
To:
r-sig-ecology@r-project.org
Date:
05/15/2012 12:17 PM
Subject:
[R-sig-eco] Continuous (Non-Count) Skewed Data With Many Zeros
Sent by:
r-sig-ecology-bounces@r-project.org



   The water chemistry data of metal concentrations are not normally
distributed (based on Q-Q plots) and are not improved by transformation
(log10, sqrt, cubic root). For the 30 metal species the percentage of 
zeros
ranges from none (10 metals) to 48.6; average 5.6. Most metals are at very
low concentrations with infrequent spikes which might be very high.

   Those with fewer zeros are not a concern, but I'd like your thoughts on 
1)
at what percentage do the number of zeros become a concern and 2) how to
characterize and model these data.

Rich

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