Hello, Thank you for your help. I have tried to perform the analysis I wanted with data of example, I mean not real data because I can't provide it here. So, what I have tried is this,
> matrix [,1] [,2] [,3] [1,] 0.00 0.13 0.59 [2,] 0.13 0.00 0.55 [3,] 0.59 0.55 0.00 > dist_mat 1 2 2 0.13 3 0.59 0.55 # here, distance matrix is calculated from percentaje of different nucleic acids between two sequences and R is not used to perform it. The original data would be like this: n1 n2 n3 n4 n5 n6 n7 n8 n9 n10 n11 n12 m1 A C G T A G C T A C T A m2 G C T A T G C T A C T A m3 G A G T A G C T A C T A > factors_frame time region city 1 2006 europe london 2 2005 africa nairobi 3 2005 europe paris > my.cap <- capscale(dist_mat ~ time + region + time:region + region:city + time:region:city, factors_frame) > my.cap Call: capscale(formula = dist_mat ~ time + region + time:region + region:city + time:region:city, data = factors_frame) Inertia Rank Total 0.445 Constrained 0.445 2 Inertia is squared distance Some constraints were aliased because they were collinear (redundant) Eigenvalues for constrained axes: CAP1 CAP2 0.42978 0.01522 > anova(my.cap) Erro en `names<-.default`(`*tmp*`, value = "Residual") : se intenta especificar un atributo en un NULL Then, I am still concerned about 'comm' argument since I don't understand how important could it be for my type of data and I don't understand to what it referes in my data. Another thing, is that what I am really interested in is to perform a factorial anova with another factor nested (the model I have provided above), and as you can see R gives an error that I don't understand either. Thank you for your help in advance. Regards, Alicia > On Thu, 2006-11-16 at 17:25 +0100, Alicia Amadoz wrote: > > Hello, > > > > I am interested in using the capscale function of vegan package of R. I > > already have a dissimilarity matrix and I am intended to use it as > > 'distance' argument. But then, I don't know what kind of data must be in > > 'comm' argument. I don't understand what type of data must be referred > > as 'species scores' and 'community data frame' since my data refer to > > nucleic distances between different sequences. > > No, that is all wrong. Read ?capscale more closely! It says that you > need to use the formula to describe the model. "distance" is used to > tell capscale which distance coefficient to use if the LHS of the model > formula is a community matrix. > > Argument "comm" is used to tell capscale where to find the species > matrix that will be used to determine species scores in the analysis, > *if* the LHS of the formula is a distance matrix. "comm" isn't used if > the LHS is a data frame, and "distance" is ignored if the LHS is a > distance matrix. > > As you don't provide a reproducible example of your problem, I will use > the inbuilt example from ?capscale > > ## load some data > data(varespec) > data(varechem) > > Now if you want to fit a capscale model using the raw species data, then > you would describe the model as so: > > vare.cap <- capscale(varespec ~ N + P + K + Condition(Al), > data = varechem, > distance = "bray") > vare.cap > > In the above, LHS of formula is a data frame so capscale looks to > argument "distance" for the name of the coefficient to turn it into a > distance matrix. The terms on the RHS of the formula are variables > looked up in the object assigned to the "data" argument. > > Now lets alter this to start with a dissimilarity/distance matrix > instead. The exact complement of the above would be: > > dist.mat <- vegdist(varespec, method = "bray") > vare.cap2 <- capscale(dist.mat ~ N + P + K + Condition(Al), > data = varechem, > comm = varespec) > vare.cap2 > > To explain the above example; first create the Bray Curtis distance > matrix (dist.mat). Then use this on the LHS of the formula. When > capscale now wants to calculate the species scores of the analysis it > will look to argument "comm" to use in the calculation; which in this > case we specify is the original species matrix varespec. > > As for what are species scores, well this is a throw back to the origins > of the package and the methods included - all of this is related to > ecology and mainly vegetation analysis (hence vegan). > > For species scores, read variable scores. The distance matrix (however > calculated) describes how similar your individual sites (read samples) > are to one another. You can also display information about the variables > used to determine those distances/similarities, and this is what is > meant by species scores. Whatever you used to generate the distance > matrix, the columns represent the info used to generate the "species > scores". > > If some of this still isn't clear, email the list with the commands used > to generate your distance matrix in R and I'll have a go at explaining > this with reference to your data/example. > > > > > I would be very grateful if you could help me with this fact in any > > manner. Thank you in advance for your help. > > > > Regards, > > Alicia > > HTH > > G > > -- > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > Gavin Simpson [t] +44 (0)20 7679 0522 > ECRC & ENSIS, UCL Geography, [f] +44 (0)20 7679 0565 > Pearson Building, [e] gavin.simpsonATNOSPAMucl.ac.uk > Gower Street, London [w] http://www.ucl.ac.uk/~ucfagls/ > UK. WC1E 6BT. [w] http://www.freshwaters.org.uk > %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% > > > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.