similar to: Error is assocplot

Hallo, I was trying some code, but couldn't make one step of the code properly. Can anybody please help me? I have one matrix like this > values [,1] [,2] [,3] [,4] [,5] [1,] 0.7777778 0.36111111 0.22222222 0.1388889 0.0000000 [2,] 1.0000000 0.00000000 0.53846154 0.0000000 0.5384615 [3,] 0.5200000 0.48000000 0.64000000 0.0000000 0.8800000 [4,] 0.8928571

Hello, How can I create a symmetric contingency table from two categorical vectors having different length of levels? For example one vector has 98 levels TotalData1$Taxa.1 [1] "Aconoidasida" "Actinobacteria (class)" "Actinopterygii" "Alphaproteobacteria" [5] "Amoebozoa"

Hello R experts, I am having an wired problem to save my RPlot after I use "identify" option. Points are identified properly, but when I try to save that image I get error as: " Error: first argument must be a string (of length 1) or native symbol reference" and the image without identified points are saved. I am having this problem after I upgraded to R version 3.0.0. (Mac).

Dear all, I have one problem to handle a large dataset... It looks like: "read" "no" "length" 2 2 144 7 7 47490 9 9 310944 11 11 10089 14 14 13152 17 17 27363 and so on There are 130000 rows >From this table I need to make a table like 2_1 2 100 2_2 2 44 7_1 7 100 7_2 7 100 ... ... 7_474 7 100 7_475 7 90 9_1 9 100 9_2 9 100 and so on... In words: I want to

Hello R experts, I am trying to plot ordiellipse for my data but the col according to factors. Metabolites_raw= read.csv(file.choose(), head = TRUE) #file 21Metabolites.csv Metabolites_t=t(Metabolites_raw[,2:82]) ord <- metaMDS(Metabolites_t, distance="bray") symbol=as.numeric(Metab_metadata$LandType) col.list <-

Hallo R Users, Please help I have some distance matrix data like > M[1:10,] [,1] [,2] [,3] [,4] [,5] [,6] [1,] 0.8750000 0.5000000 0.5000000 0.3750000 0.6250000 0.00000000 [2,] 0.8928571 1.0000000 0.0000000 0.8928571 0.1071429 0.00000000 [3,] 0.8928571 1.0000000 0.0000000 0.8928571 0.1071429 0.00000000 [4,] 0.8928571 1.0000000 0.0000000 0.8928571

Dear All, I am having some problem in apply function. I have some data like below. I want to get a range vector (which is max-min value for each row , ignoring NA values.) > Species.all[1:10,] V2 V3 V4 V5 V6 V7 V8 V9 1 57543 55938 47175 54922 36032 5785 29497 7286 2 42364 40472 29887 40107 19723 2691 14445 3258 3 19461 19646 18538 22392 6744 794

I have been tinkering with mosaicplot() and friends as a way of learning R. As part of this, I've written a pair.table() method for mosaic matrices, and would like to extend mosaicplot to work with loglin and logln (MASS) objects. I'm using R 1.4.0 on Win 98. I've been trying to figure out the formula interface, and think there's a bug, but not sure how to find it, yet alone fix

Thank for your help I obtained profiles and I found mosaicplot as an interesting alternative. I don't like my solution about legend in profiles graphics: I inserted empty extra columns in order to avoid tue superimposed of legend. #Data N <- matrix(0,3,6) N[1,] <- c(7,7,5,0,4,4) N[2,] <- c(0,0,0,5,5,5) N[3,] <- c(4,4,0,0,3,0) rownames(N) <-

Hi I have a large dataset, containing a wide range of binary variables. I would like first of all to compute a jaccard matrix, then do a PCA on this matrix, so that I finally can do a hierarchical clustering on the principal components. My problem is, that I don't know how to compute the jaccard dissimilarity matrix in R? Which package to use, and so on... Can anybody help me? Alternatively

This may sound crazy but... I have data like this... > results.matrix [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [1,] 949 93 2 11 26 20 7 6 10 5 0 3 [2,] 1233 124 24 35 58 57 17 21 31 19 11 21 Which is the result of binning (summing) the response variables of an underlying (nearly) continious range of predictor

Good morning, I am analyzing a dataset composed by 364 subjects and 13 binary variables (0,1 = absence,presence). I am testing possible association (co-presence) of my variables. To do this, I was trying with cluster analysis. My main interest is to check for the significance of the obtained clusters. First, I tried with the pvclust() function, by using method.hclust="ward" and

Hi, Can someone set me straight as to how to write formulas in R to indicate: complete independence [A][B][C] joint independence [AB][C] conditional independence [AC][BC] nway interaction [AB][AC][BC] ? For example, if I have 4 factors: hair colour, eye colour, age, sex does > mosaicplot( frequency ~ hair + eye + age + sex) mean that the model fitted is of complete independence of

Hello. I've been using R for a couple of months and enjoying it a lot. This is my first post to R-help. I'm using the vcd package to make mosaic plots with labels on the tiles indicating the number of items in each cell. For example, I've made this plot: > allmorph<-structure(c(10, 26, 17, 100, 70, 97, 253, 430, 185, 177, > 25, 1), .Dim = as.integer(c(6, 2)), .Dimnames

Dear All, I would like to use the simprof function (clustsig package) but the available distances do not include Jaccard distance, which is the most appropriate for pres/abs community data. Here is the core of the function: > simprof function (data, num.expected = 1000, num.simulated = 999, method.cluster = "average", method.distance = "euclidean", method.transform =

I'm pretty sure that I did everything right, but my R is just not drawing the mosaicplot that I want, and there is also no error messege, looks like this right now: > mosaicplot(arthritis) > mosaicplot(~ sex + treatment + improved, data = arthritis, color = TRUE) > -- View this message in context: http://r.789695.n4.nabble.com/problems-with-mosaic-plot-tp3090128p3090128.html Sent

Hello Pardon for the elementary question, I did try searching the archives with various terms, but to no avail. I am using R1.9.1 on a windows machine One of the great advantages of R (to me, anyway) is being able to see the code for a function , e.g. by typing sd one sees the code for getting a standard deviation. However, for many functions this only provides info. including UseMethod, eg.

I tried this : > mosaicplot(stoc ~ q9r + segca,data=tmp2,color=T) : works fine. And now, this : > mosaicplot(stoc ~ q9r + segca, data=tmp2, color=T, main="Big title") Error in model.frame(formula, rownames, variables, varnames, extras, extranames, : invalid variable type I'm probably stupid and missed something simple in the manual (and wouldn't like to be

Two proposals for mosaicplot(): - The argument "sub" should not be ignored. Example: mosaicplot( HairEyeColor, sub = 'test of sub' ) - To be able to discern also longer axis labels the argument "las" or par(las=2) should not be ignored. Example: mosaicplot( HairEyeColor, las=2 ) Thanks Wolfram

This dataset below is one sample answer the questioner from our customer. > testbank <- read.table("testbank.txt", header=T) > testbank age married income gender ownhouse class 1 20-30 no high female yes 1st 2 30-40 no high female yes 1st 3 40-50 no low female yes 1st 4 50-60 no high female yes 1st 5 60-70