similar to: Finding a single unique item in duplicated vectors

I was starting to write a note to a prospective R-user and came to the point of explaining how to get useful introductory information on R. After mentioning the Into and the FAQs I went on to try to explain how to use a lot of the contributed information. However I realised that there seems to be no direct way to get to Other Publications or Contributed Documenation. The best I have seen is

Dear everyone I'm dealing with a problem related to Poisson Ridge Regression. If anyone can help me in this regard by telling if any changes in the source code of "glm.fit" may help -- Regards Umesh Khatri

Dear R family, Suppose I have two series. order value 1 0.52 2 0.23 3 0.43 4 0.21 5 0.32 6 0.32 7 0.32 8 0.32 9 0.32 10 0.12 11 0.46 12 0.09 13 0.32 14 0.25 For these two series, I figured out the way to detect the locations of duplicate values. The next thing to do is remove the repeated values except for a value that would not be next to each other. In other words, while keeping the

Using R version 2.4.1 (2006-12-18) on Windows, I have a dataset which resembles this: id att1 att2 att3 1 1 1 0 2 1 0 0 3 0 1 1 4 1 1 1 ratings <- data.frame(id = c(1,2,3,4), att1 = c(1,1,0,1), att2 = c(1,0,0,1), att3 = c(0,1,1,1)) I would like to get a cross tab of counts of co-ocurrence, which might resemble this:

I have hundreds of humans who have undergone SNP genotyping at hundreds of loci. Some have even undergone the procedure twice or thrice (kind of an internal control). So obviously I need to find those replications, and confirm that the results are the same. If there is discordance then I need to address it. I tried to use the aggregate function nr.attempts

Dear R family, I have a question about how to detect some duplicate numeric observations. Suppose that I have two variables dataset. order value 1 0.52 2 0.23 3 0.43 4 0.21 5 0.32 6 0.32 7 0.32 8 0.32 9 0.32 10 0.12 11 0.46 12 0.09 13 0.32 14 0.25 ; Could you help me indicate where the duplicate observations in a row (e.g., 0.32) are? best, moohwan

I have a data frame with two factors (sampling 'unit', 'species'). I want to calculate the number of unique 'species' per 'unit.' I can calculate the number of unique values for each variable separately, but can't get a count for each ?unit?. > data=read.csv("C:/Desktop/sr_sort_practice.csv") > attach(data) > data[1:10,] unit species 1

Can anyone explain the results from switch below when a single charachter "E" is entered? It seems to work with letter S or N... > switch("East",West=1,East=2) # Correct [1] 2 > switch("E",W=1,E=2) # Not so correct [1] 1 > switch("E",E=1,W=2) # Even stranger [1] "E" > switch("S",N=1,S=-1) # Correct [1] -1 Kind regards,

On Tuesday 06 February 2001 12:36, Dr. Jens Oehlschlägel wrote: > I like the idea. Why don't you call duplicated.matrix() directly in > unique.matrix() and duplicated.data.frame() in unique.data.frame() ? > > Jens Oehlschlägel Good point. I guess I got carried away with using methods (having just gotten the hang of the concept). :-) Anyway, here's a corrected version:

Hello all, I manually created an hclust object. Now I am looking to reorder the leafs so they won't intersect with each other, and would be happy for advises on how to do that. Here is an example code: #------------------------------------- a <- list() # initialize empty object # define merging pattern: # negative numbers are leaves, # positive are merged clusters (defined by row

Hi all, I'm using a certain  procedure to calculate the value of some variable(Bayes risk),B. So I got the values B1, B2, ........, B1000, each under certain input values and using a long procedure. Now, I want to put the values I got in a nummerical vector and find their minimum value. I think c( ) should work.For example if I have only 10 values I could have used

Hi fellow users I have a new R problem i am hoping to get some pointers on. I have a dataset that is approximately normally distributed but with a fat left tail. I am interested in a good measurement on how much fatter the left tail is than can be expected from a normal distribution. One thing I'll tried was fitting a two component mixture model with the Rmix package but i am also interested

Hello R users, I have gene expression data of two groups of genes (large and small). Gene expression intensities of those genes are classified into 1 to 10 levels. What I want is to make a random set of genes that have the same levels as the small group from large group using sample(). I used smallvec to hold the number of genes in each levels (1 to 10) for small group, largevec for large group.

Hi, I am trying to simultaneously remove duplicate variables from two or more variables in a small R data.frame. I am trying to reproduce the SAS statements from a Proc Sort with Nodupkey for those familiar with SAS. Here's my example data : test <- read.csv("test.csv", sep=",", as.is=TRUE) > test date var1 var2 num1 num2 1 28/01/11 a 1 213 71 2

Dear list, I have a data frame of survey respondents, a little like this: set.seed(20081215) n <- 100 dat <- data.frame(id=1:100, addr1=sample(LETTERS, n, replace=TRUE), addr2=sample(LETTERS, n, replace=TRUE), addr3=sample(LETTERS, n, replace=TRUE)) head(dat) id addr1 addr2 addr3 1 1 R H Q 2 2 H C K 3 3

Yesterday I spend the whole day struggling on how to get the maximum value of "y" for every unique value of "x" from the dataframe "test". In the R Book (Crawley, 2007) an example of this can be found on page 121. I tried to do it this way, but I failed. In the end, I figured out how to get it working (first order, and afterwards use !duplicated()). My question

Hi everybody I have found something (for me at least) strange with duplicated(). I will first provide a replicable example of a certain kind of behaviour that I find odd and then give a sample of unexpected results from my own data. I hope someone can help me understand this. Consider the following # this works as expected ex=sample(1:20, replace=TRUE) ex duplicated(ex) ex=sort(ex) ex

I was playing around a bit to see how I could find the two points in a set of points (or ordered pairs) furthest from each other. Here's what I did: 1) created a Nrow by 2col matrix, so each row contains an x,y coordinate pair. 2) fed the matrix to a nested mapply (cv is my matrix): mapply(function(k,l) mapply(function(x,y,a,b) +

I was posed the following problem/teaser: given two matrices, come up with an "elegant" (=fast & short) function that returns a matrix with all and only the non-duplicated columns of both matrices; the column order does not matter. In essence, a matrix equivalent of union(x,y), where x and y are vectors. I could not come with anything nice. Any ideas? Giuseppe -- Giuseppe A.

I have this maximum liklihood estimate problem i need to find the roots of the following: [sum (from i=1 to n) ] ((2(x[i]-parameter)/(1+(x[i]-parameter)^2))=0 given to me is the x vector which has length 100 how would I find the roots using R? I have 2 thoughts...... 1 is using a grid search ... eg. brute force, just choosing a whole bunch of different values for my parameter .... such as