similar to: Estimate "between-axes" vs "within-axes heterogeneity of multivariate matrices

Dear All My data consists in 96 groups, each one with 10 observations. Levene's test suggests that the variances are not equal, and therefore I have tried to apply the classical transformations to have homocedasticity in order to be able to use ANOVA. Unfortunately, no transformation that I have used transforms my data into data with homocedasticity. The histogram of variances is at

Hello, I'm looking for a R function proceeding MRPP (Multi-Response Permutation Procedures). Is it available? Thanking you in anticipation, Jeanne Vallet, PhD student [[alternative HTML version deleted]]

Hi I've built a dll using Fortran code and can call it by either R or Fortran. Calling by the former gives me the wrong answer and the later gives the correct answer. >From what I've read, it looks like I should use the subroutines DBLEPR, INTPR and REALPR to print to the R console rather than using Fortran standard I/O and that if I use the command R CMD SHLIB source.f that these

#Hi, I am trying to run an MRPP with community data (spp-site-matrix). I use the following code: mzbtaxa_mrpp <- mrpp(mzbdist,mzbsites$Site) #mzbdist being a distance object (Bray-Curtis similarity matrix) derived from my sqrt transformed community data set, created with function 'vegdist', mzbsites$Site refers to factors structuring my community. #when I run this code, I get the

I have been trying to find a way to do a blocked MRPP (MRBP) and blocked ISA in R but have not found anything (in fact I found some things that say it is not possible). Does anyone know of a package, or written a script, that can do either of these? Thank you for any help.

Greets to the list! I am aware that this topic has been discussed several times. And I've read quite some related posts [1]. Yet, can't seem to give a solution to my problem. I have 6 data frames consisting of 6 rows x 7 columns put together from other data.frames. Something like: a b c d e f g v1 # # # # # # # v2 # # # # # # # v3 # # # # # # # v4 # # # # # # # v5 # # # # # # # v6

Hi list! I have prepared a custom function (below) in order to calculate separability indices (Divergence, Bhattacharyya, Jeffries-Matusita, Transformed divergene) between two samples of (spectral land cover) classes. I need help to cross-compare results to verify that it works as expected (since I don't know of any other foss-tool that will give me quickly some results). Does anybody

Dear R-list, Among the (R-)tools, I've seen on the net, for (bivariate) Principal Component scatter plots (+histograms), "plotpc" [1] is the one I like most. By default it performs PCA on a bivariate dataset based on R's "princomp()" (which is the eigenvector-based algebraic solution to PCA). I would like to modify "plotpc()" in order be able, as an

Hi R-list. This is my first post. I'll try to be as precise as possible with the difficulty I have to "get things done". I have a hard time trying to construct a double "for" loop and create within the inner loop new objects (in this case vectors). I posted this question in a non-directly related with pure R-problems list (in grass-stats). In addition, I think I

Dear vegan team, Vegan development happens now completely in github. R-Forge repository is no more in sync with github. I tried to commit all github changes to R-Forge, but a week ago I got a conflict in file and I haven't had time to resolve that conflict. You can follow vegan development and vegan discussion also without signing to github. The system seems to be completely open and does not

I am perfectly aware that this question is not an R question, at least not yet, but I have not succeeded in finding what I want in other ways, so ... What I am looking for are two algorithms, preferabley in Pascal, but other languages may do. For (a) systematic (complete) permutations for grouped data with unequal group sizes, and (b) random permutations for the same kind of data. I know

My data have heterogeneity of variance (in a categorical variable), do I need to specify a variance structure accounting for this in my model or do GLMMs by their nature account for such heterogeneity (as a result of using deviances rather than variances)? And if I do need to do this, how do I do it (e.g. using something like the VarIdent function in nlme) and in what package? This is my first

Hi all, I have major heterogeneity in variances across labs (100-fold). There is no apparent variance heterogeneity across y-hat. By using lme4 in the following way, am I accounting for the variance differences in labs?: lmer(y ~ fixed1 + covariates + (fixed1|labs)) I'm not sure that it is - I think it is only allowing the means (slopes [conditional means] & intercepts) to differ

Dear list members, I am looking for an alternative function for a two-way ANOVA in the case of variance heterogeneity. For one-way ANOVA, I found oneway.test(), but I didn't find anything alike for two-way ANOVA. Does anyone have a suggestion? Thank you! Maike Luhmann Freie Universit?t Berlin

dear R-help: one of my students is struggling to test an ordered alternative hypothesis on a set of groups (e.g., mu_a <= mu_b <= mu_c). There has been some literature on this topic -- a lot of this goes back to Bartholomew (1961); Gaines and Rice (see refs below) are the ones who've popularized it in the ecology community. The topic is closely related to isotonic regression, but

Hi, I am trying to add multiple variance structures such as the first example below: vf1 <- varComb(varIdent(form = ~1|Sex), varPower()) However my code below will not work can anybody please advise me? VFcomb<-varComb(varExp(form=~depcptwithextybf),varFixed(form=~FebNAO)) also if you have two variables with the same weights function would you write that as:

Dear colleagues, has anyone an idea how to carry out a nonparametric manova for comparing K groups? has anyone a good package of non-parametric stats? Thank you for your help. -- José David Gómez Químico Farmacéutico Universidad Nacional [[alternative HTML version deleted]]

Classification: UNCLASSIFIED Caveats: NONE A similar question has been posted in the past but never answered. My question is this: for probit analysis, how do you program a 95% confidence interval for the LD50 (or LC50, ec50, etc.), including a heterogeneity factor as written about in "Probit Analysis" by Finney(1971)? The heterogeneity factor comes into play through the chi-squared

I have numerous replicated goodness-of-fit experiments (observed compared to expected counts in categories) and these replicates are nested within a factor. The expected counts in each cell are external (from a scientific model being tested). The calculations I need within each level of the nesting factor are a heterogeneity G test, with the total G and the pooled G across replicates. Then I

Hola queridos usuarios de R-HELP-ES Primero que nada, muchas gracias a todo aquellos que me prestaron ayuda en mi anterior pregunta, fue de gran utilidad. A lo siguiente, tengo ahora otras preguntas, que bajo mis conocimientos las considero complejas, espero que me puedan ayudar, se los agradezco de antemano. Necesito realizar las siguientes operaciones (#Operación general) a un conjunto de 18