[R-sig-eco] forward selection RDA after controlling for constraints
Hello all, I would like to run this by everyone and maybe get some hints as to what R functions I could use for this. Ok, so I have macroinvertebrate assemblage data from across the SE. I would like to control for geographic distance (lat/long), Watershed area, and year before submitting these data to an RDA with the rest of the environmental data using a variable selection technique. Does it make sense to detrend the data using a mlm on hellinger transfomed abundances with the above env variables as regressors and then submit the residuals to rda with the rest of the env variables I am interested in? Many thanks for all of the help. kindest regards, -- Stephen Sefick ** Auburn University Biological Sciences 331 Funchess Hall Auburn, Alabama 36849 ** sas0...@auburn.edu http://www.auburn.edu/~sas0025 ** Let's not spend our time and resources thinking about things that are so little or so large that all they really do for us is puff us up and make us feel like gods. We are mammals, and have not exhausted the annoying little problems of being mammals. -K. Mullis A big computer, a complex algorithm and a long time does not equal science. -Robert Gentleman ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] forward selection RDA after controlling for constraints
On 10/07/2013, at 21:00 PM, Stephen Sefick wrote: Hello all, I would like to run this by everyone and maybe get some hints as to what R functions I could use for this. Ok, so I have macroinvertebrate assemblage data from across the SE. I would like to control for geographic distance (lat/long), Watershed area, and year before submitting these data to an RDA with the rest of the environmental data using a variable selection technique. Does it make sense to detrend the data using a mlm on hellinger transfomed abundances with the above env variables as regressors and then submit the residuals to rda with the rest of the env variables I am interested in? Stephen, If you happen to use vegan functions for forward selection, please note that they all (should) take a scope argument that can (should) be a list of lower and upper scopes. Put your controlled variables (distance???, watershed area, year) in the lower scope and these plus other candidate variables in the upper scope, and there you go. I have used should, because I have rarely used these functions myself, and I'm not sure if lower scope really is implemented in all, but is *should* be: file a bug report if this fails. I have no idea how to have distance RDA. Well, I have ideas, but none that I have are very good. Using separate mlm and modelling residuals will not work quite correctly, because that ignores correlations between groups of variables. Vegan functions do not ignore those. Cheers, Jari Oksanen -- Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland jari.oksa...@oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] forward selection RDA after controlling for constraints
Jari, Thank you for the quick reply. Maybe I should use something like PCNM first with the lat/long data to then use in the rda? I really appreciate all of your help. Are there anyother/better ways to account for spatial autocorrelation. I guess I need to show that spatial autocorellation exists and then if it does account for it? Any reading etc. would be greatly appreciated. I appreciate all of the help. kindest regards, Stephen P.S. I will let you know about the stepwise selection and scope argument On Wed, Jul 10, 2013 at 2:28 PM, Jari Oksanen jari.oksa...@oulu.fi wrote: On 10/07/2013, at 21:00 PM, Stephen Sefick wrote: Hello all, I would like to run this by everyone and maybe get some hints as to what R functions I could use for this. Ok, so I have macroinvertebrate assemblage data from across the SE. I would like to control for geographic distance (lat/long), Watershed area, and year before submitting these data to an RDA with the rest of the environmental data using a variable selection technique. Does it make sense to detrend the data using a mlm on hellinger transfomed abundances with the above env variables as regressors and then submit the residuals to rda with the rest of the env variables I am interested in? Stephen, If you happen to use vegan functions for forward selection, please note that they all (should) take a scope argument that can (should) be a list of lower and upper scopes. Put your controlled variables (distance???, watershed area, year) in the lower scope and these plus other candidate variables in the upper scope, and there you go. I have used should, because I have rarely used these functions myself, and I'm not sure if lower scope really is implemented in all, but is *should* be: file a bug report if this fails. I have no idea how to have distance RDA. Well, I have ideas, but none that I have are very good. Using separate mlm and modelling residuals will not work quite correctly, because that ignores correlations between groups of variables. Vegan functions do not ignore those. Cheers, Jari Oksanen -- Jari Oksanen, Dept Biology, Univ Oulu, 90014 Finland jari.oksa...@oulu.fi, Ph. +358 400 408593, http://cc.oulu.fi/~jarioksa [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
