similar to: PCA biplot question

Dear all: Subjects were measured two times (t1 and t2) on different variables (v1 ... vn). Between t1 and t2 there was an experimental manipulation. I computed two PCAs for time-points t1 and t2. Is it possible to combine both PCAs in order to get only one set of eigenvectors? Due to the experimental manipulation measurement values on time points t1 and t2 changed for each subject. Many

Hi all, I am trying to compare two distance matrices with R. I would like to create a XY plot of these matrices and do some linear regression on it. But, I am a bit new to R, so i have a few questions (I searched in the documentation with no success). The first problem is loading a distance matrix into R. This matrix is the output of a the Phylip program Protdist and lookes like this: 5

Hi all, I am doing bootstrap on a distance matrix, in which samples have been drawn with replacement. After that I do PCA on a resulted matrix, and these 2 steps are repeated 1000 times. pca(x) is a vector where I wanted to store all 1000 PCAs; and x is from 1 to 1000 SampleD is a new matrix after resampling; I am getting the following error message, which I don't understand: ....

Dear r-helpers, I just read in an article by Virtanen et al. (2006) where vegetation-environment relationships are studied by fitting smoothed surfaces on an NMDS ordination using GAMs (Wood 2000). The authors describe, that they used R? as goodness-of-fit statistic, which they compare to the R? of fitted vectors. Calculations were carried out using the package vegan (Oksanen). I know that I can

I'm getting lots of grief from reviewers about figures generated with the envfit function in the Vegan package. Has anyone else struggled to effectively explain this analysis? If so, can you share any helpful tips? The most recent comment I've gotten back: "What this shows is which NMDS axis separates the communities, not the relationship between the edaphic factor and the

I have a general question about using thin plate splines in the surf and ordisurf routines. My rudimentary knowledge of a gam is that with each predictive variable there is a different smooth for each one and then they are added together with no real interaction term (because they don't handle this well?). Now, If I have two variables that have a high D^2 score and a low GCV score (I am

Hi! Is there a way to get biplot and identify to work togheter. Having the output of prcomp I would like to draw a biplot that. Instead of plotting the sample (row-names) names plots some "pch" symbols. (thats easy with xlabs) But now I would like to add using identify the names to only some of the points. I have noticed that both biplot.prcomp and biplot.default does a lot of

Hi all, I'm new to PCA in R, so this might be a basical thing, but I cannot find anything on the net about it. I need to make a PCA plot with two response variables (df$resp1 and df$resp2) against eight metabolites (df$met1, df$met2, ...) and I don't have a clue how to do... and I've only used the simplest PCAs before, like this: pcaObj=prcomp(t(df[idx, c(40:47)]))

I'm having trouble with the ordisurf function in the vegan package. I have created an ordination plot (cmdscale) of 60 samples based on Bray-Curtis dissimilarities, and would like to overlay various soil edaphic characteristics as possible clues to the clustering I observe in my plot. However, I find that ordisurf creates a surface on the plot that is a perfect, even gradient - and

Dear R-helpers, I have two data frames, op and em4: > str(op) 'data.frame': 37 obs. of 5 variables: $ m : num 0.202 0.336 0.122 0.139 0.14 ... $ lln : num 0.798 0.643 0.863 0.835 0.823 ... $ rrn : num 0.789 0.702 0.894 0.895 0.923 ... $ asym2: num 0.177 0.304 0.108 0.187 0.274 ... $ asym3: num 0.0755 0.0975 0.0818 0.0651 0.13 ... > str(rownames(op)) chr

Dear r-Community, Step1: I would like to calculate a NMDS (package vegan, function metaMDS) with species data. Step2: Then I want to plot environmental variables over it, using function envfit. The Problem: One of these environmental variables is cos(EXPOSURE). But for flat releves there is no exposure. The value is missing and I can't call it 0 as 0 stands for east and west. Therefore I

Hi Now a more theoretical question. I have two correlation matrices - one of a set of variables under a particular condition, the other of the same set of variables under a different condition. Is there a statistical test I can use to see if these correlation matrices are "different"? Thanks Mick

Dear all, I didn't find any graphical solution in the package "mva" to plot the canonical scores from a CCA (canonical correlation analysis). Does anybody knows how to plot or has anybody already programmed : - the map of the canonical scores, - the graph of the canonical weights, - the correlation circle i.e. the canonical loadings ? Thank you for help ...

Hi there, I am plotting relative warp scores (equivalent to pca scores) and I want to label (color code and shape) the points by group. I can't figure out how to do this beyond simple plotting. plot(RW1, RW2); Do I need to make vectors of each group and then plot them separately onto the same plot? How do I go about this? Thanks! -- View this message in context:

I'm pretty new to R and would appreciate some help interpreting the output of a function that was recommended to me. I've used the *envfit *function in the vegan package to plot vectors of four climate variables onto a species matrix ordination. The output indicates that only a single variable (mean_temp) is significant: ***VECTORS NMDS1 NMDS2 r2

What does Generalized Cross Validation score mean. I preform and ordisurf on an ordination (nmds) with an environmental variable. I am trying to figure out "how well" the environmental varibles predict/explain the sites placements in species space. Any help would be greatly appreciated. Any pointers to literature... would be welcome. thanks in advance, -- Stephen Sefick Research

Hello Sir/Mam I am Nitish Kumar Mishra from IMTECH, Chandigarh, India. I want to calculate the Principal Component Analysis(PCA), PLS of the input file and find top 30 PCAs of this file using PLS in R. I am asking regarding Linux(Red Hat 9) operating system. I have downloaded PLS from Crains site and try to installed it, but don't installed it. How I can download and installed PLS(for PCA and

Hi, I would like to know if people have found the package made4 to load! I would like the .zip If you have the @ on internet to load it please give me it! Thanks a lot, Sabine --------------------------------- [[alternative HTML version deleted]]

Hi! I am trying to know which habitat variables most affect bird counts in a radius of 100m. I obtained bird counts in 2751 spatial points, and measured percentage of 21 habitat variables in these points. I applied a mixed model using the "lmer" function to these data, but I do not know how to select the best model using AIC here. Is there a way to do this automatically with R?

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