similar to: Need some help in R : value more than equals to a row.

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

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).

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, I have a contingency table showing relation between two datasets. I tried to see association among them with the assocplot, but it shows error. mosaicplot of the same data worked perfectly. Can anyone please help me. Con.table=as.matrix(Con.table) > dim(Con.table) [1] 27 27 > assocplot(Con.table,space = 0.3, + main = NULL, xlab = NULL, ylab = NULL) Error in

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 <-

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

Dear All, I would like to ask a couple of questions on a LME model. I tested 4 selection lines at 4 food concentrations against a standard competitor stock. I had 3 replicate cages per selection line. In each cage I have 10 vials. I counted the number of wild type flies and competitor stock emerging in each vial. My main question is: is there any difference between selection lines? I did fit

Arrrrr, I think I've found a bug in the behavior of the stats::cor function when NAs are present, but in case I'm missing something, could you look over this example and let me know what you think: > a = c(1,3,NA,1,2) > b = c(1,2,1,1,4) > cor(a,b,method="spearman", use="complete.obs") [1] 0.8164966 > cor(a,b,method="spearman",

Dear all, I am new to R and to it's programming philosophy. The following function is supposed to work on a vector, but I can't figure out how to do that without looping through every element of it. Is there a more elegant way? Note: I have shortened it, so it is NOT correct from the pipe hydraulics point of view # Calculate wall friction factor # reynolds: Reynolds number # dk:

Dear list, Im trying to do the following operation but im not able to do it This is my table: 1 2 3 1 0 7 4 2 0 2 0 3 0 1 3 4 0 3 4 what i would like to do is divide each row values with the corresponding column' sum,namely: 1 2 3 1 0 0.54 0.36 2 0 0.15 0 3 0 0.08

Hi, I posted this message earlier in "Rmetrics" and I don't know whether I posted in the wrong place, so I'm posting it again in Rhelp. I have a function in x and y and let's call it f(x,y). I need to get the Hessian matrix. i.e I need (d^2f/dx^2), (d^2f/dxdy), (d^2f/dydx), (d^2f/dy^2).I can get these using the D function. now I need to evaluste the hessian matrix for

Problem: Based on a n x 2 data matrix i want a kernel estimate of the bivariate density. However, i also wish to specify wich points the density should be calculated at. I can offcourse just write the full kernel density estimate as a R-code, but surely there must already exist some package for this operation? The package density(), seems to create a new matrix (depending on n), where the

Dear All, I am analysing some data for a colleague (not my data, gotta be published so I cannot divulge). My response variable is the number of matings observed per day for some fruitlies. My factors are: Day: the observations were taken on 9 days Regime: 3 selection regimes Line: 3 replicates per selection regime. I have 81 observations in total The lines are coded A to I, so I do not need

Dear Mailing-List, I think this is a newbie question. However, i would like to integrate a loop in the function below. So that the script calculates for each variable within the dataframe df1 the connecting data in df2. Actually it takes only the first row. I hope that's clear. My goal is to apply the function for each data in df1. Many thanks in advance. An example is as follows: df1

I am having trouble printing a table out to the GUI display when the table is created and printed within a loop. I get a "Error: syntax error message" If I comment out the print statement, the loop runs fine and I can print out the last iteration of the table. ...[multiple loops and calculations ending with.....]... +

In package fOptions, there are functions that generate Halton sequences. The van der Corput sequence for base 2 is a particular case of the Halton sequence generated by: n <- 8 # anything here... x <- runif.halton(n, 1) In fact, x <- runif.halton(n, dim) will generate the van der Corput sequences for the base b as the i-th prime number in x[,i]. (in other words, if I want the van der

Hi, I sometimes play around with extreme parameters for distributions and found that qbeta is not always monotone as the following example shows. I don't know whether this is serious enough to submit a bug report (as this example is near to the limitations of floating point arithmetic). Josef > x <- qbeta((0:100)/100,0.01,5) > x [1] 0.000000e+00 1.253990e-201 1.589622e-171

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Hello R users, Can any one please help me to find a way to build phylogenetic tree by R program from any distance matrix. Suppose I have a data like : MATRIX [1] '1' 0.0 [2] '2' 0.071 0.0 [3] '3' 0.036 0.286 0.0 [4] '4' 0.429 0.75 0.714 0.0 [5] '5' 0.679 0.179 0.214 0.536 0.0 [6] '6' 0.893 0.929 0.964 0.464 0.357 0.0 [7]