similar to: from table to matrix

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

I wish to generate a vector of uniformly distributed data with a defined correlation to another vector The only function I have been able to find doing something similar is corgen from the library ecodist. The following code generates data with the desired correlation to the vector x but the resulting vector y is normal and not uniform distributed library(ecodist) x <- runif(10^5) y

I am using the function metaMDS with jaccard distances to ordinate a set of constituent by site matrix. I can post this data if it would be helpful, but it is large to include in an email. I can also provide reproducable code if necessary. I would like to get an R^2 value for the axes of the ordination configuration that I get with metaMDS in the vegan package is there a way to do this- is it

I would like to put confidence intervals on a mantel corellogram they are already calculated in the pmgram object but I am unsure how I get the x value in order to plot them? package(ecodist) X<-1:100 Y<-rnorm(1:100) Z<-rnorm(1:100) XY<-dist(data.frame(X,Y)) YX<-dist(data.frame(Y,X)) my.mgram<-mgram(XY,XZ) plot(my.mgram) print(my.mgram) > print(my.mgram) $mgram

Hi!! I am trying to generate data with specific correlation using corgen method from the ecodist package. It does not seem to generate the data properly. I am listing the code below. Secondly, when I put the code given below all in one file and source it, it is unable to complete the task. But when I execute it one at a time it is able to complete it. Can someone point out any mistake that I may

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Hi there, I would like to find a more efficient way of permuting the rows and columns of a symmetrical matrix that represents ecological or actual distances between objects in space. The permutation is of the type used in a Mantel test. Specifically, the permutation has to accomplish something like this: Original matrix addresses: a11 a12 a13 a21 a22 a23 a31 a32 a33 Example

What is the size of the boostrapped subsample in ecodist mantel() thanks [[alternative HTML version deleted]]

Hi, I'm interested in incorporating some interaction terms between my explanatory variables (distance matrices in this case) when I'm using the function MRM of the package ecodist. The function is doing a multiple regression on distance matrices. I can get the function to work perfectly on my explanatory matrices by adding a (+) sign as known. However, when I try to use the (*) sign or

Hi all, I'm searching for a little clarification on partial mantel tests (ecodist package) I've a distance matrix (x,y), and several others containing environmental/chemical variables. Based on the help file, and the package instructions I've managed to implement the tests as; var1 ~ env1 + space to partial out the effect of space and test the relationship between the

Hi, forgive me if someone has already posted about this but I have had a look and cannot find the answer, also I am very new to R and been getting the grips with this. I have been trying to use Adonis to find out if there are significant difference between groups on data that I have analyses with NMDS, and have been struggling with getting this to work and understanding what is going on. I am

I need to create artificial datasets with specific correlation coefficients (i.e. a dataset that returns r = 0.30, etc.) as examples for a lab I am teaching this summer. Is there a way to do that in R? Thanks. Jim Milks Graduate Student Environmental Sciences Ph.D. Program 136 Biological Sciences Wright State University 3640 Colonel Glenn Hwy Dayton, OH 45435 [[alternative HTML version

I have data on current and previous location of individuals. I would like to have a matrix with bilateral movement between locations. I would like the final output to look like the second table below. I have tried using crosstab() from the ecodist but I do not have another variable to measure the flow. Ultimately I would like to compute the probability of movement between cities (movement to

HI, You can also try this: d<-1:25 A<-sample(combn(20:30,2)) B<-sample(combn(20:30,2)) lapply(d,function(x) matrix(c(1,A[x],B[x],1),2,2)) [[1]] [,1] [,2] [1,] 1 23 [2,] 27 1 [[2]] [,1] [,2] [1,] 1 21 [2,] 21 1 [[3]] [,1] [,2] [1,] 1 29 [2,] 23 1 [[4]] [,1] [,2] [1,] 1 25 [2,] 20 1 [[5]] [,1] [,2] [1,] 1 23 [2,]

Dear all, Has anyone written R code for partial Mantel Tests- as described for instance in Legtendre & Legendre (1998) ? In other words, in a community ecology analysis, I would like to calculate the correlation between two dissimilarity matrices, controlling for a third distance matrix representing geographical distances between sites. Thanks! Christophe Bouget Biodiversité et gestion des

Let's suppose I have userids and associated attributes... columns a and b a <- c(1,1,1,2,2,3,3,3,3) b <- c("a","b","c","a","d","a", "b", "e", "f") so a unique list of a would be id <- unique(a) I want a matrix like this... [,1] [,2] [,3] [1,] 3 1 2 [2,] 1 2 1 [3,]

I have a presence/absence matrix for which I create a distance matrix and then perform pco analysis on. /library(ecodist) table <- read.table("matrix.pa") dist <- dist(table, method = "euclidean", diag = FALSE, upper = FALSE) dist.pco <- pco(dist)/ When I plot the pco analysis of the distance matrix I want to be able to distinguish between certain characters, for

or in base R : ?xtabs ?? as in: xtabs(~previous_location + current_location,data=x) (You can convert the 0s to NA's if you like) Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Tue, May 8, 2018 at 9:21 AM, Huzefa

Dear Bert and Huzefa, Apologies for the late reply, my account got hacked and I have just managed to recover it. Thank you very much for your replies and the solutions. Both work well. I was wondering if there was any way to ensure (force) that all possible combinations show up in the output. The full dataset has 25 cities but of course people have not moved from Boston to all the other 24

Dear Miluji, If I understand correctly, this should get you what you need. temp1 <- structure(list(id = 101:115, current_location = structure(c(2L, 8L, 8L, 3L, 6L, 5L, 1L, 2L, 7L, 4L, 2L, 8L, 8L, 3L, 6L), .Label = c("Austin", "Boston", "Cambridge", "Durham", "Houston", "Lynn", "New Orleans", "New York"), class =