similar to: In is.euclid(m2) : Zero distance(s)

Dear UseRs, i want to apply mantel test by comparing a list of 124 distance matrices with a reference distance matrix "q". The list of distance matrices was created by the following command.. u<-lapply(el, function(x) dist(x)) where "el" is a data frame of 75 columns and 124 rows. Therefore, the list of distances matrices, made out of it should have 75 elements each

I'm trying to perform a mantel test that ignores specific pairs in my distance matrices. The reasoning is that some geographic distances below a certain threshold suffer from spatial autocorrelation, or perhaps ecological relationships become less relevant that stochastic processes above a certain threshold. The problem is that I can't find a way to do it. If I replace values in either or

Dear useRs, i want to open an excel file having 59 sheets in r and GOD knows the number of command i tried. unfortunately none worked, obviously error will be on my part. All the sheets contain 1 kind of data and the data starts from A12:M12 (which contains the header of the data), the line immediately under the header is blank. The number of columns of data in each sheet are same while the

Dear useRs,Is there a command or package in R to do heirarchical clustering by "modified ward method"??regardseliza [[alternative HTML version deleted]]

Dear useRs, I have a very basic question. I have a distance matrix and i skipped the upper part of it deliberately. The distance matrix is 1000*1000. Then i used "min" command to extract the lowest value from that matrix. Now i want to know what is the location of that lowest element? More precisely, the row and column number of that lowest element. Thanks in advance elisa

dear useRs, i created a distance matrix, of certain voltage values. unfortunately, i lost the original values. i am only left with the distance matrix that i created from those values. i wanted to ask that is there a way in R to reverse distance matrix for the original values? thanks in advance eliza [[alternative HTML version deleted]]

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

Dear Sir/ Madam, I would like to ask you about mantel test in R. In ade4 package, if I want to use mantel.rtest, I get error massage "Object of class to "dist" expected". As I already have two dissimilarity matrices, shall I again compute distance measure using this function? If not, could you please let me know which function/command I can use to do? Thank you very much in

Dear useRs,while trying to plot the yearly curves of 1000 stations and overlapping each set of curves with mean curve and then saving it automatically in a pdf file, i tried the following commands >Path = "C:\\R\\003.pdf">pdf(file=Path) for (i in seq(1:1000) >a<-lapply(seq_along(tcp), function(x) tcp[[x]][,-1]) >b<-lapply(seq_along(a), function(a)

Dear all, I'm calculating matrix correlations with permutation tests and I got this funny result. All correlation coefficients are the same with mantel.test {ncf} and pcol {simba} but the two functions yield dramatically different p-values (using the same number of permutations). Could anyone please enlighten me what is causing the difference and which result I can trust? (My matrices

Dear UseRs, MY PROBLEM IS A SMALL PIECE OF A REAL BIG AND A COMPLICATED PROBLEM. IF I DELIBERATE IN A VERY SIMPLE WAY THEN ALL I WANT IS TO PUT ALL THE POSSIBLE COMBINATIONS OF 75 DISTANCE MATRICES (BY TAKING 4 MATRICES, MORE COMMONLY 75C4), in the following equation. t<-as.matrix((MAT1)^2+(MAT2)^2+(MAT3)^2+(MAT4)^2+,upper=T,diag=T)) Then "1215450" values of "t"(one for

Hi useRs, I am trying to compare several distance matrices obtained from subsets of variables from the same experiment. I put all the subsets in a list and then calculated the distance matrices with lapply. In order to do a mantel test between them I wrote a function the returns a list with the output of single tests. I would like to include the name of the tests, so I know what each element

Hi, I'm very new to R. I want to know if there is any way to write only the lower half of a distance matrix created in R to a csv file for example. I get the 'cannot coerce class "dist" into a data.frame' message when I try. I have used as.matrix and can write to a file this way, but as a full matrix. The reason I only want the lower half is that I've been doing some

Hi Elisa, I hope this is what you wanted. dat1<-read.csv("peaks.csv",sep=",") #Subset dat2<-dat1[1:5,] res1<-do.call(cbind,lapply(seq_len(nrow(dat2)),function(i) do.call(rbind,lapply(split(rbind(dat2[i,],dat2[-i,]),1:nrow(rbind(dat2[i,],dat2[-i,]))), function(x) {x1<-rbind(dat2[i,],x);

Hi, Try this: el<- read.csv("el.csv",header=TRUE,sep="\t",stringsAsFactors=FALSE) ?elsplit<- split(el,el$st) ? datetrial<-data.frame(date1=seq.Date(as.Date("1930.1.1",format="%Y.%m.%d"),as.Date("2010.12.31",format="%Y.%m.%d"),by="day")) elsplit1<- lapply(elsplit,function(x)

HI Elisa, You could use ?cut() vec1<-c(33,18,13,47,30,10,6,21,39,25,40,29,14,16,44,1,41,4,15,20,46,32,38,5,31,12,48,27,36,24,34,2,35,11,42,9,8,7,26,22,43,17,19,28,23,3,49,37,50,45) label1<-unlist(lapply(mapply(c,lapply(seq(0,45,5),function(x) x),lapply(seq(5,50,5),function(x) x),SIMPLIFY=FALSE),function(i) paste(i[1],"<x<=",i[2],sep="")))

No, you do not necessarily need the XY coordinates. You can also use polygon (field, in your case) adjacency information. See Rogerson, Peter A. 2001. _Statistical methods for geography_. Thousand Oaks: Sage. You might also look at GeoDA, a free and soon-to-be open source spatial analysis package. For your application, it might be easier to use than R. Go to https://www.geoda.uiuc.edu/.

Dear useRs, i want to split a matrix having 1116rows and 12 columns. i want to split that matrix into 36 small matrices each having 12 columns and 31 rows. The big matrix should be splitted row wise. which means that the first small matrix should copy values which are in first 31 rows and 12 columns of the big matrix. similarly 2nd small matrix should contain values from 32nd to 63rd row of the

Hi, I have the following function that I want to apply to a list of 14 matrices (1536 x 170) of binary data: DRes <- function(x, nr = 10000, metric = "mixed", ...) { require(analogue) require(ade4) m <- c() for (i in 1:nr) { set.seed(i) x1 <- x[, sample(dimnames(x)[[2]], length(x[1,])/2)] x2 <- x[, !dimnames(x)[[2]] %in% dimnames(x1)[[2]]] d1 <-

Dear UseRs,Extremely sorry for a basic question. I have a matrix of 19 rows and 365 columns. what i want to do is the following...First i want to leave out column number 1 and want to calculate the row wise mean of the remaining columns, which will obviously give me 365 values in one column, and then subtracting these values from the column i left out i.e. col=1 then i want to leave out column 2