similar to: metaMDS using Dissimilarity matrix

H ello R-experts, I want to do ordination plots using vegan metaMDS. I have a where many cells have zero values. Data structure: X[1:10,1:14] Height.1 Height.2 Height.3 Height.4 Height.5 Height.6 Height.7 Height.8 Height.9 Height.10 Height.11 Height.12 Height.13 D30I1A 46 0 0 0 0 0 0 0 0 0 39 0 98 D30I1B

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I try to find the most important variables to divide my dataset as given in a categorical variable using randomForest. Is randomForest() able to deal with count data? Or is there no difference because only the ranks are used in the trees? Thanks in advance Birgit Birgit Lemcke Institut f?r

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I tried rfImpute (randomForest) and as far as I understood should it replace NA`s using a proximity matrix: > set.seed(100000) > Subset5Imputed<-rfImpute(Sex~., data=Subset5) ntree OOB 1 2 300: 11.78% 12.36% 11.21% ntree OOB 1 2 300: 12.07% 12.64%

R version 2.6.2 PowerBook G4 Hello R User, I try to perform an ANCOVA using the glm function. I have a dataset with continuous and categorical data (explanatory variables) and my response variable is also binary categorical. Fehler: NA/NaN/Inf in externem Funktionsaufruf (arg 4) Zus?tzlich: Warning messages: 1: In Ops.factor(y, mu) : - nicht sinnvoll f?r Faktoren (makes no sense for

Hello R-user! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I try to find the most important variables to divide my dataset as given in a categorical variable. code: Test.rf4<-randomForest(Sex~.,na.action=na.roughfix, data=Subset4, importance=TRUE, proximity=TRUE, ntree=10000, do.trace=1000, keep.forest=FALSE) My dataset contains also ordered

Hi, I am currently working on some data and feel that NMDS would return an excellent result. With my current data set however I have been experiencing some problems and cannot carry out metaMDS. I have tried with a few smaller data sets which I created for practice sake and this has worked fine. I think it is the set up of my data set that is causing me trouble. I have 18 columns and 18 rows,

Hello R-user community! I am running R 2.7.0 on a Power Book (Tiger). (I am still R and statistics beginner) I did the following : pdf("InLnegthMaxHomogeneity.pdf") boxplot(inflorescence_length_Max~Sex, main="Bartletts Homogeneity for inflorescence length",data=FemMal_Sex) Homo<-bartlett.test(FemMal_Sex$inflorescence_length_Max,FemMal_Sex$Sex) text( 2, 500,

Hello R-Cracks, I am using R 2.6.1 on a PowerBook G4. I would like to perform a discriminant function analysis. I found lda in MASS but as far as I understood, is it only working with explanatory variables of the class factor. My dataset contains variables of the classes factor and numeric. Is there another function that is able to handle this? Thank you all in advance. Greetings Birgit

Hello R experts, I've used metaMDS to run NMDS on some fish abundance data, and am also working on correlating environmental data to the NMDS coordinates. I'm fairly new to metaMDS and NMDS in general, so I have what are probably some very basic questions. My fish abundance data consists of 66 sites for which up to 20 species of fish were identified and counted. I ran metaMDS on this data

Hi, I've been using R for a while now but I've got a problem with metaMDS (in the vegan package) that I can't quite figure out. I have a set of proportion data (from 0-1, rows sum to 1) that I apply metaMDS to using the command: nMDS.set=metaMDS(sqrt(test.set),distance="euclidean",k=3,zerodist="add",autotransform=FALSE) I am using a squared-chord distance

Dear List, This is Elaine, a postgraduate studying in bird distributions in East Asia. I want to calculate Simpson dissimilarity index, based on a presence/absence matrix of bird species in islands in East Asia. (matrix row: 36 islands/matrix column: species ID) (R package vegan to make NMDS and R package betapart) In most papers using vegan for NMDS and betapart for dissimilarity

Hi, I am stuck in one problem when doing nonmetric multidimensional scaling. I use the function 'metaMDS' in the package 'vegan' to work on the presence/absence community data. The problem is when two samples are identical (dissimilarity = 0), metaMDS cannot work with zero dissimilarity. I don't want to delete the duplicates as they are true samples from different locations.

Hi I have just (finally) started to poke around in R and wanted to analyse a stream fish dataset with 28 sites and 18 species. When trying to follow the Vegan manual to run nmds from distance measures calculated by the vegdist function it turns out that I have two sites (streams) with the exactly the same four species (I have used pres-abs data in this case). When I try to run isoMDS I get an

Hello everyone! metaMDS(cm, distance = "euclidean", k = 2, trymax = 50, autotransform =TRUE, trace = 1, plot = T) (cm is a similarity matrix, in which values are positive integers or 0) I use this command to run NMDS on my matrix "cm". But the stress is very high after analysis. About 14. Actually, there is no improvment comparing with using isoMDS.

Hi, First I should note I am relatively new to R so I would appreciate answers that take this into account. I am trying to perform an MDS ordination using the function ?metaMDS? of the ?vegan? package. I want to ordinate species according to a set of functional traits. ?Species? here refers to ?sites? in traditional vegetation analyses while ?traits? here correspond to ?species? in such

Hello all, I recently used the Vegan library quite extensively (in the context of text similarity assessment) on an Ubuntu 6.06 LTS system with R version 2.2.1 (2005-12-20 r36812). The Vegan lib is version 1.6-10. I hit on a problem yesterday, though, when trying to install R and Vegan on two further computers - one Windows XP and one further Ubuntu 6.06 machine, taking either R version 2.4.0

Hi R-experts, I am using the envfit function over an ordination of floristic data. The problem is that every time that I run it changes the results. Sometimes dramatically, selecting variables that the first time were not significant. I do not get what could be the problem or if is normal given the permutations are different. # the NMDS ordination gap_flor_NMDS_chord <- metaMDS(gaps_flor,

Dear R-community, dear Jari Oksanen! I use metaMDS (package vegan) to calculate NMDS. In a lot of papers I read that it is recommended to use previous best solutions as a new starting configuration to get better results and to avoid local minima. On the help page I found that a previous.best-command is already implemented in metaMDS: metaMDS(comm, distance = "bray", ...,plot = FALSE,

Hello R-user community, I am applying the function metaMDS. However, I would like to know if there is any option to export the data I got from the axis as a data frame. I have tried as.data.frame.list but is not working. Any suggestion? Thank you in advance for your help, Lineth [[alternative HTML version deleted]]

Dear r-helpers! How can I integrate other distances (in the form of a dist object) into function metaMDS? The problem: metaMDS needs the original data.frame for the calculation and only the default distances of function vegdist are allowed. Any suggestions are greatly appreciated! Thank you, Kim -- Jetzt kostenlos herunterladen: Internet Explorer 8 und Mozilla Firefox 3.5 - sicherer, schneller