similar to: dissimilarity matrices

Hello, I am working with a matrix of multilocus genotypes for ~180 individual snail samples, with substantial missing data. I am trying to calculate the pairwise genetic distance between individuals using the stats package 'dist' function, using euclidean distance. I took a subset of this dataset (3 samples x 3 loci) to test how euclidean distance is calculated: 3x3 subset used

Hi, I have a dataset that looks like the one below. data plot plantno. species H 31 ABC D 2 DEF Y 54 GFE E 12 ERF Y 98 FVD H 4 JKU J 7 JFG A 55 EGD . . . . . . .

Hi I needed some help with ANOVA I have a problem with My ANOVA analysis. I have a dataset with a known ANOVA p-value, however I can not seem to re-create it in R. I have created a list (zzzanova) which contains 1)Intensity Values 2)Group Number (6 Different Groups) 3)Sample Number (54 different samples) this is created by the script in Appendix 1 I then conduct ANOVA with the command >

> 3x3 subset used > Locus1 Locus2 Locus3 > Samp1 GG <NA> GG > Samp2 AG CA GA > Samp3 AG CA GG > > The euclidean distance function is defined as: sqrt(sum((x_i - y_i)^2)) My > assumption was that the difference between

I'm writing R code to calculate Hierarchical Social Entropy, a diversity index that Tucker Balch proposed. One article on this was published in Autonomous Robots in 2000. You can find that and others through his web page at Georgia Tech. http://www.cc.gatech.edu/~tucker/index2.html While I work on this, I realize (again) that I'm a C programmer masquerading in R, and its really

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R,

you could try mapply mydata2<-mapply("[", mydata, lapply(mydata, function(x) !x %in% A)) mydata2[[1]]<-A #to replace the obviously deleted elements of "A" mydata2 mydata2[[1]] mydata2[[2]] mydata2[[3]] mydata2[[4]] Stefano -----Messaggio originale----- Da: r-help-bounces at stat.math.ethz.ch [mailto:r-help-bounces at stat.math.ethz.ch]Per conto di jastar

Hello, does anyone know of a quick way to create a data frame "like" another, but with more rows? What I'd like to do is this: if mydata is a data.frame like a b c 1 TRUE yes 2 FALSE no 3 TRUE yes I'd like to get mydata2 with the same column names and column types, but without the values and with more rows. All I could think of was to manually do

R helpers I am getting to grips with R but came across a small problem today that I could not fix by myself. I have 3 text files, each with a single column of data. I read them in using: myData1<-scan("C:/Program Files/R/myData1.txt") myData2<-scan("C:/Program Files/R/myData2.txt") myData3<-scan("C:/Program Files/R/myData3.txt") I wanted to produce a

Dear all, I have problem when reading a table into R. The total row of read in table has is much less than the original saved table. I built a 1,273,230 by 6 data set named "mydata2", it was saved in the following command, write.table(mydata2, "mydata2.txt", row.name=F,col.name=T,quote=F,sep="\t") The next day I read in above saved text file into R,

Hello I have dataframes. mydata1 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 07:00:00 ","2005-05-25 19:00:00","2005-06-25 07:00:00","2005-06-25 19:00:00 ","2005-07-25 07:00:00","2005-8-25 19:00:00")) or mydata2 <-data.frame(value=c(15,20,25,30,45,50),dates=c("2005-05-25 00:00:00 ","2005-05-25

I'm trying to convert data from character to numeric. I've imported data as a csv file, I'm assuming that the import is a database - are all the columns in a database considered "vectors" and that they can be operated on individually Therefore I've tried the following mydata <- as.numeric(mydata$apples) when i then look at mydata again the named column is still

I can run one-sample t-test on an array, for example a matrix myData1, with the following apply(myData1, 2, t.test) Is there a similar fashion using apply() or something else to run 2-sample t-test with datasets from two groups, myData1 and myData2, without looping? TIA, Gang

Dear All, a long time ago I ran a cluster analysis where the dissimilarity matrix used consisted of Dmax (or Kolmogorov-Smirnov distance) values. In other words the maximum difference between two cumulative proportion curves. This all worked very well indeed. The matrix was calculated using Dbase III+ and took a day and a half and the clustering was done using MV-ARCH, with the resultant

Dear users, I have a double for loop that does exactly what I want, but is quite slow. It is not so much with this simplified example, but IRL it is slow. Can anyone help me improve it? The data and code for foo_reg() are available at the end of the email; I preferred going directly into the problematic part. Here is the code (I tried to simplify it but I cannot do it too much or else it

Hi, It works for me to import spss datasets via library(foreign) with read.spss or via library Hmisc by (spss.get). But no matter which way I do import the data, user-defined missings from Spss are always lost. (it makes no difference if there are a single value, a range, or any combination of them. They are always ignored). Is there any way in R to find out if any value was user-defined missing

Hello fellow R's, I?ve been learning to use the ggplot2 library, and after a full day of work I still have a couple of basic questions. Here is an example: mydata=data.frame(x=runif(20),y=runif(20),n=runif(20)) mydata2=data.frame(x=c(0.4,0.6,0.5),y=c(0.4,0.4,0.6)) ggplot(mydata, aes(x, y)) + geom_point(aes(size = n)) + geom_polygon(data=mydata2,aes(x,y,alpha=0.5)) In this plot, the

hello everybody I use the following code for my programming & it runs with the error as specified below.Any help that would disolve the error will be highly appreciated. Thanks in advance my code looks like this #### R programme for simulating the power of the two sample t test vs various #### non-parametric alternatives sim.size <- 200 sample.size <- 10 set.seed(231) mu1 <- 0 delta

Dear R-users, I need some  assistance. I am running some interactive variables for categorical variables. I have dgen(2 levels converted to dummy variables)  and dtoe(4-levels also converted to  dummy variables). So I have worked with them in two ways: i created a variable X1 = dgen*dtoe  and I get an error "Error in dgen * dtoe : non-conformable arrays"then i run a glm, binomial

Hi all, I wanted to run the hclust (or any other clustering algorithm) on a distance matrix. I have formed the distance matrix as: distmat: a b c d e a 0.00 0.96 1.60 1.60 1.68 b 0.96 0.00 0.96 1.80 2.64 c 1.60 0.96 0.00 0.84 1.80 d 1.60 1.80 0.84 0.00 0.96 e 1.68 2.64 1.80 0.96 0.00