On Thu, 2013-03-07 at 11:13 -0800, Rich Shepard wrote: > On Thu, 7 Mar 2013, Philippi, Tom wrote: > > > I would look at packages bio.infer, paltran, fossil, and analogue, and > > search to see if anyone has pushed them in the direction you want to go.
To this list I would add Steve Juggins' excellent rioja package. In addition to several WA methods it also includes maximum likelihood regression and calibration in the flavour of bio.infer. > bio.infer is based on the EPA's EMAP-West (Environmental Monitoring and > Analysis Program for the western states) and uses benthic macroinvertebrates > and fish with selected water chemistry parameters. It uses the ITIS > (International Taxonomic Identification System) to provide consistency in > naming taxa to the lowest reasonable level. As far as I can tell, bio.infer contains all you say but as higher-level utility functions. However, IIRC at the heart of bio.infer is what we call maximum likelihood regression and calibration; fit a Gaussian logistic regression to each species to characterise species-env relationships, then "invert" this set of models to find the value of the environmental variable that maximises the likelihood of observing a sample of new counts over the set of species. Invariably, the inversion involves numerical optimisation to search for the value of the env that made the new counts most likely. You just need to give mlsolve() the relevant data objects, which seem to be somewhat easy to create by hand if you don't need to look-up harmonised or correct taxon names. You really don't need all the nice ITIS hand-holding, though I'm sure it is very handy for those working on relevant species groups. G > Conceptually, one could assemble equivalent dataframes for diatom taxa and > environmental conditions, but I don't know if ITIS has plants/algae in the > system; problably does. However, the biota-environments relationships would > be based on current conditions and whether this would be valid for sediment > core data would need to be judged by a limnologist, not a stream ecologist > like me. > > Rich > > _______________________________________________ > R-sig-ecology mailing list > R-sig-ecology@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-ecology > _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology