similar to: correlated data

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

Dear R experts, I am trying to simulate correlated binary data and have stumbled upon the following problem: With the help of "binarySimCLF" or "mvpBinaryEp" I have been able to simulate correlating binary vectors given certain mean values and a desired correlation. My problem is that these procedures do not allow you to specify the exact vector for which you want to generate

Hi everyone. Based on a dependent variable (y), I'm trying to generate some independent variables with a specified correlation. For this there's no problems. However, I would like that have all my "regressors" to be orthogonal (i.e. no correlation among them. For example, y = x1 + x2 + x3 where the correlation between y x1 = 0.7, x2 = 0.4 and x3 = 0.8. However, x1, x2 and x3

Dear R experts: I have following problem: # myfunction mfun1 <- function(x) { if ( x == 2){ xv <- sample(c(2,1,0),100, replace = T, prob = c(0.6, 0.2, 0.2)) } if ( x == 1){ xv <- sample(c(1,0),100, replace = T, prob = c(0.6, 0.4)) } if ( x == 0) { xv <- sample(c(0,0),100, replace = T, prob = c(0.5, 0.5)) } return(xv) } # applying the function x = mfun1(1) # just what I

The problem remain unsolved. If you have any idea please do suggest .................... thank you; Ram H On Wed, Aug 31, 2011 at 12:06 PM, Ram H. Sharma <sharma.ram.h@gmail.com>wrote: > Dear R experts: > > I have following problem: > > # myfunction > mfun1 <- function(x) { > if ( x == 2){ > xv <- sample(c(2,1,0),100, replace = T, prob = c(0.6, 0.2,

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

Hi, how can I produce random data which lies around a straight line with angle 45 degree. Similar to this image: http://zoonek2.free.fr/UNIX/48_R/g134.png Cheers -- View this message in context: http://old.nabble.com/Random-data-tp26513822p26513822.html Sent from the R help mailing list archive at Nabble.com.

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

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

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

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

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

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

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

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

I have a table like this: Date TIME Q A a 1 A b 2 A c 3 B a 4 B b 5 B c 6 C a 7 C b 8 C c 9 I want use R language to turn it to a matrix like : a b c A 1 2 3 B 4 5 6 C 7 8 9 I am new to R , anyone can help? Thanks in advance! have a table like this: Date TIME Q A a 1 A b 2 A c 3 B a

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 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

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

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