Hi,
How is represented your data: a regular grid: raster, irregular samples: points, or slots/parcels: areas? If you want to determine species richness, you can use simpson and shannon indexes with diversity package. On a point pattern object, use spatstat::marktable function as mentionned in http://r-sig-geo.2731867.n2.nabble.com/density-diversity-of-points-td6355348.html On a raster, use raster::focal Then you may perform a linear regression with your explanatory variables. 2011/7/3 ah3881 <ah3...@bristol.ac.uk> > I am trying to run some analysis to determine the percentage contribution > of various factors (minimum temp in lgm, npp, etc) on determining > species richness of 171 species throughout Southeast Asia (on a km by km > basis-so over 4 million rows of cells, and about 14 columns). > I have read about various stats tests, and softwares-but I am no > statistician and I would really appreciate some advice as to the best > method/tests. > So far I have been attempting SPSS, but it does not give me the outputs I > need, and a colleague suggested R might be the best way to analyse the data > Thanks in advance > > -- > View this message in context: > http://r-sig-geo.2731867.n2.nabble.com/Assessing-and-ranking-the-relationships-and-contribution-of-environmental-correlates-to-species-richs-tp6543945p6543945.html > Sent from the R-sig-geo mailing list archive at Nabble.com. > > _______________________________________________ > R-sig-Geo mailing list > R-sig-Geo@r-project.org > https://stat.ethz.ch/mailman/listinfo/r-sig-geo > [[alternative HTML version deleted]] _______________________________________________ R-sig-Geo mailing list R-sig-Geo@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-geo
