search for: pcoa

Hello everyone, I mail you because of my lake of knowlegde regarding statistics. I'm using the CA and PCoA (but maybe should I use some other techniques) to determine the differences and similarities between a large sample of plants using different kind of traits through matrix of mixte variables. I understood that the daisy() function using the gower metric and defining the different type of variable i...

Hi, I am working with a species-by-trait .csv file (columns=traits, rows=species) and get the following warning message when trying to plot results of both metaMDS and pcoa:  "Warning message: In ordiplot(x, choices = choices, type = type, display = display,  :   Species scores not available" I am using a Gower's transformation in both procedures within the metaMDS or pcoa functions, and I know I am not using something already made into a distance matr...

I think it is an easy question but i haven´t found a solution since I am r beginner. I did this plot3d(PCoA, type="p", col=rainbow(1000),size=5) text3d(PCoA, text=Nam) How can I save it including the labels to a jpg-file? Thanks in advance. Birgit Birgit Lemcke Institut für Systematische Botanik Zollikerstrasse 107 CH-8008 Zürich Switzerland Ph: +41 (0)44 634 8351 birgit.lemcke@systbot....

...;, 8), rep("7", 51), rep("8", 1), rep("9", 15), rep("10", 53), rep ("11",3), rep("12",3), rep("13", 8), rep("14", 90), rep("15", 8), rep ("16", 9), rep("17", 32), rep("18",11)) PCoA<-cmdscale(Dist.Gower, k = 3) plot3d(PCoA, type="s",col= colors, size=0.5) but I get only different colors for the numbers 1 to 8 and after that it starts again with the first colour black. How can get more different colours? And two further questions: how can I ad a legend to the...

Dear all, I was looking for methods in R that allow assessing the number of significant principal coordinates. Unfortunatly I was not very successful. I expanded my search to the web and Current Contents, however, the information I found is very limited. Therefore, I tried to write code for doing a randomization. I would highly appriciate if somebody could comment on the following approach.

...binary data. I'm trying to write a function that will allow me to interactively exclude species using the inofrmation in the third text column. My function, matrix.slicer, appears to work as I intend. However, when I pass the resulting matrix to my homemade principal coordinates function, pcoa, the results include all of the data, with nothing excluded. I've read the help for factors, levels, subset, [, and some threads here relating to subsetting and drop=true issues, but I'm afraid I just don't understand what I need to do. I've pasted the functions below - any hel...

Dear All, It's Eszter from Hungary, a total beginner with R. My problem is the following: I have a dataset with binary values as a comma separated textfile. The samples are in the coloumns and the species are in the rows. I have to transpose it for the further PCoA analysis. There is no problem with reading the dataset. When I transpose the dataset, the original values become strings (instead of 0,1,0,0,1 I have "0","1","0","0","1"). The distance matrix cannot be counted from the transposed dataset, I hav...

Dear all, Does anyone know how to run Principal Coordinates Analysis (PCoA) from a squared euclidean dissimilarity matrix with R ? Thanks, ************************* Arnaud DOWKIW Department of Primary Industries J. Bjelke-Petersen Research Station KINGAROY, QLD 4610 Australia T : + 61 7 41 600 700 T : + 61 7 41 600 728 (direct) F : + 61 7 41 600 760 ********************...

Hi, I need to run a PCoA (PCO) for a data set wich has both positive and negative values for variables. I  could not find any distancecoefficient other than euclidean distace running for the data set. Are there any other coefficient works with negtive values.Also I cannot get summary out put (the eigen values) for PCO as f...

...values are calculated. Could you please tell me how can I fix this problem and have the FRic value for my data? Func.div?dbFD ( trait_data, abundance_data, calc.FRic = T, corr="cailliez", w.abun = T, CWM.type = "all" ) FRic: Dimensionality reduction was required. The last PCoA axis (out of 6 in total) was removed. FRic: Quality of the reduced-space representation = 0.9402678 QH6114 qhull precision error: initial simplex is not convex. Distance=-2.7e-15 Error in convhulln(tr.FRic, "FA") : Received error code 2 from qhull. Best, Elisae [[alternative HTML...