similar to: Quickly generate all possible combinations of 2 groups

This is the first time that I've posted to this list, so if I'm doing something wrong, please let me know. Also, if there is a searchable forum where I can find help, that would be good too. I'm doing a card sorting experiment, and I'm having problems imputing my data into R for later analysis. This is what I get from each sorter: Category Name Card numbers

Dear all, I have two sets of data (say set1 and set2) as follow: set1 x1 x2 x3 0.30 0.43 3.88 0.38 0.59 3.53 0.30 0.42 2.12 0.33 0.53 2.12 0.30 0.47 3.76 set2 y1 y2 y3 0.32 0.47 5.18 0.23 0.26 1.06 0.42 0.65 3.88 0.28 0.38 3.76 0.35 0.47 1.41 The "pairs" function (such as pairs(~x1+x2+x3 data=set1, main="Simple Scatterplot Matrix") ) is

Hello! I need to compare 2 datasets whether they come from the same distribution. I use function ks.boot{Matching}. And what is the confidence level of the p-value, returned by ks.boot function? The code is: set=read.table("http://stella.sai.msu.ru:8080/~gala/data/testsets.csv", header=T,sep=',') set1=set[!is.na(set$set1),'set1']

Dear R users, I am working on allocating the rows within a dataframe into some factor levels.Consider the following dataframe: Start.action Start.time 1 Start.setting 2010-12-30 17:58:00 2 Start.setting 2010-12-30 18:40:00 3 Start.setting 2010-12-31 22:39:00 4 Start.setting 2010-12-31 23:24:00 5

Good evening I often have as output from simulations a list of various values, vectors and matrices. Supposing that I then run said simulation several times, I often want to extract a particular result from each simulation for plotting and, ideally, put it in a matrix. A simple example v1 <- 1:5 v2 <- 6:10 other1 <- "stuff" other2 <- "stuff" set1 <-

Dear developeRs, I encounter the following problem: in the current version of my package FrF2, certain calls to a functioni do not work when package combinat is loaded, because function combn from combinat masks the function from utils that my package uses. I tried to solve this issue by importing function combn into the namespace of FrF2; I don't need to export it, I just want to use it

Colleagues, (R: 2.13.0; OS X) I often receive sequential datasets in which there are new rows interposed between existing rows. For example: SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4, 6:10))) SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10)) > SET1 LETTERS NUMBERS 1 A 1 2 B 2 3 C 3 4 D 4 5

On 03/09/2017 12:28 PM, Krzysztof Parzyszek via llvm-dev wrote: > We could add intrinsics to extract/insert a bitfield, which would > simplify a lot of that bitwise logic. But then you need to teach a bunch of places about how to simply them, fold using bitwise logic and other things that reduce demanded bits into them, etc. This seems like a difficult tradeoff. -Hal > >

Dear friends, I have a data set with 23 columns and 38000 rows. It is a panel running from the years 1991 through 2005. I want to aggregate the data and get the medians of each of the 23 columns for each of the years. In other words my output should be like this Year Median 1991 123 1992 145 1993 132 etc. The sample lines of code to do this operation is set1 <-

Hello, I am plotting data as a venn diagram but would like to be able to control how it is plotted like a lattice object. Right now, it plots right away. I would like to name it and then plot at will. I thought to convert the whole thing to a PostScript file then get it back into R via grImport, but surely (please!) there must be a less roundabout way to do this. Any help is appreciated. Here

I have encountered this problem on several occasions and am not sure how to handle it. I use for-loops to cycle through datasets. When each dataset is of equal length, it works fine as I can combine the datasets and have each loop pick up a different column, but when the datasets are differing lengths, I am struggling. Here is an example: A<-1:10 B<-1:15 C<-1:18

In http://lists.llvm.org/pipermail/cfe-commits/Week-of-Mon-20120827/063200.html, consecutive bitfields are wrapped as a group and represented as a large integer and emits loads stores and bit operations appropriate for extracting bits from within it. It fixes the problem of violating C++11 memory model that original widen load/store of bitfield was facing. It also brings more coalescing

Hi all, Suppose that I've two data frames, a and b say, both containing a column 'id'. While data frame 'a' contains multiple rows sharing the same id, data frame 'b' contains just one entry per id (i.e. a 1 to n relationship). For the ease of modeling I now want to generate a new data frame c, which is basically a copy of data frame 'a' augmented by the values

Hello all, I am trying to create a matrix of 1s and -1s without any repetitions for a specified number of columns. e.g. 1s and -1s for 3 columns can be done uniquely in 2^3 ways. -1 -1 -1 -1 -1 1 -1 1 -1 -1 1 1 1 -1 -1 1 -1 1 1 1 -1 1 1 1 and for 4 columns in 2^4 ways and so on. I finally used the function combn([0 1],3) that I found at the following link

Hello, I've been clustering my data using hclust and cutting the resulting tree with cutree. Separately, I visualize the clusterings with heatmap. Is it possible to have the dendrogram on the heatmap reflect the cutree results? That is, instead of having one large dendrogram, it would have 4 or 25 in the example below. Any guidance on if that's possible or not, and what kinds of

On Thu, Mar 9, 2017 at 10:54 AM, Hal Finkel <hfinkel at anl.gov> wrote: > On 03/09/2017 12:14 PM, Wei Mi via llvm-dev wrote: >> >> In >> http://lists.llvm.org/pipermail/cfe-commits/Week-of-Mon-20120827/063200.html, >> consecutive bitfields are wrapped as a group and represented as a >> large integer and emits loads stores and bit operations appropriate

Hi The message occurred from R, when I was selected of "optimization > block diagonal Fhiser matrix" and used the attached file on PFIM. Could you please advise me about the following message? ***************************** Loading required pakage: combinat Attaching package:'combinat' The following object(s) are masked from 'package:utils':combn

Hi all, I'm curious if anyone has coded an Expectation-Maximization algorithm that could help me model some circular data I have. I'd like to model it as a mixture of uniform and Von Mises centered on 0, so the only free parameters is the mixing proportion and the kappa of the Von Mises. I couldn't find anything in the contributed packages that seemed to suit this purpose. Any

It seems people are reinventing the wheel here: The goal is to generate all combinations of 1:n of size k. This (typically) results in a matrix of size k * choose(n,k) i.e. needs O(n ^ k) space, hence is only applicable to relatively small k. Then alternatives have been devised to generate the combinations "one by one", and I think I remember there has been a quiz/challenge about 20

Dear Sirs I can't try the package sets because I have a old mac system. Package sets needs R = 2.6. I need to group some variables into a set of new variables defined by a particular modality: Example: my.df = data.frame(var1=c(1,2,2,1,2,2,1,2), var2=c(2,2,1,1,2,2,1,1), var3=c(1,2,2,1,1,1,1,2), var4=c(1,1,1,1,2,1,2,1)) I'm looking for a way to compute set1 and set2? set1 = c(5,4) %