similar to: Exclude when sd=0

I know that I can get a count of histogram bins in base R with plot=FALSE. However, I'd like to do the same thing with lattice. The problem is that I've set up shingles, and I'd like to get the count within each bin within each shingle. plot=FALSE doesn't seem to do it. [[alternative HTML version deleted]]

Hi All, I am trying to creat a simple example byusing ipf function in R, but i could not get it succefully...I am very new to R, does anyone could help, to instruct me about this ipf fucntion? Actually, this is what I mean 50 | 50 ---------------------- 33.4| 28.57 | 14.29 33.3| 23.81 | 4.762 33.3| 9.523 | 19.05

Dear all, someone can find what I doing wrong with the following function. It is for winsorisation mean. At my eyes it is ok, but for reason I sometimes it is changing the results when I change the k value. wmean <- function (x, na.rm = FALSE, k = 1) { if (any(i.na <- is.na(x))) { if (na.rm) x <- x[!i.na] else return(NA) } n

Dear R users, I want to generating random samples from Inverse Gaussian distribution . How can I do? and what package should I install? Thanks. Shirin [[alternative HTML version deleted]]

Hi, I have to construct an ellipse interval region on a PCAbiplot, I have my parameters "a" and "b" and I would apply the formula: draw.ellipse(x, y, a = , b = ) I have done a PCA on my data so I have my scores and loading for the first and second component, but my answer is what I have to choose as X and Y into the formula? if "a" and "b" are scalars or

In the manual page for prcomp(), it says that sdev is "the standard deviations of the principal components (i.e., the square roots of the eigenvalues of the covariance/correlation matrix, though the calculation is actually done with the singular values of the data matrix)." ?However, this is not what I'm finding. ?The values appear to be the standard deviations of a reprojection of

Dear all, I want to extract rows from a data frame shown here as "test". For example: rows with with sorting PKB123 PKB22 PKB23 PKB32 CTV19 CTV20 PKB11 PKB11 > dput(test) structure(list(Name. = structure(c(1L, 2L, 3L, 4L, 5L, 6L, 7L, 8L, 9L, 10L, 11L, 12L, 12L, 13L, 14L, 15L, 16L, 17L, 18L, 19L, 19L), .Label = c("CTV10", "CTV11", "CTV12",

I'm trying to read in a tab separated table with read.delim(). I don't particularly care what the row names are. My data file looks like this: start stop Symbol Insert sequence Clone End Pair FISH 203048 67173930 ABC8-43024000D23 TI:993812543 TI:993834585 255176 87869359 ABC8-43034700N15 TI:995224581 TI:995237913 1022033 1060472

Dear all, I have a 2 by 2 matrix and I would like to do a barplot with it. (so 2 bars with each having 2 stacks.). I would like to have one colors per stack, so 4 different colors total. The problem is that R is only given me 2 colors (the same two for the bottom stack and the same two for the top stack). Any idea how I can do to have 4 colors? (without using ggplot2 preferably) Here is my

Hi,all: I want to perform multiple correspondance analysis via MCA{FactoMineR}. The data is in the attachment. My code: dat<-read.delim("e:\\mydata.txt",header=T) MCA(dat,quanti.sup=7,quali.sup=1:6) Error in `[.data.frame`(tab, , i) : undefined columns selected My question: Why does the error happen? Many thanks. Best. -------------- next part -------------- An embedded and

The rbind on empty and nonempty data frames behaves inconsistently. I am not sure if by design. In the first example, first row is deleted, which may or may not be on purpose: df1 <- data.frame() df2 <- data.frame(foo=c(1, 2), bar=c("a", "b")) rbind(df1, df2) foo bar 2 2 b Now if we continue: df1 <- data.frame(matrix(0, 0, 2)) names(df1) <- names(df2)

Hello, Though Bert's and David's answers are what you should do, note that some R functions that need factors will coerce their input variables when necessary. Have you tried to run the code you haven't posted without coercing to factor? It might run... Hope this helps, Rui Barradas On 4/9/2018 6:11 PM, David L Carlson wrote: > Try the help files: > > ?factor >

Dear all, I have a question concerning the ks.test() function. I tryed to calculate the example given on the German wikipedia page. xi <- c(9.41,9.92,11.55,11.6,11.73,12,12.06,13.3) I get the right results when I calculate: ks.test(xi,pnorm,11,1) Now the question: shouldn't I obtain the same or a very similar result if I commpare the sample and a calculated sample from the distribution?

I'm trying to find duplicate values in a column of a data frame. For example, dataframe (a) below has two 3's. I would like to mark each value of each row as either not being a duplicate of the one before (0), or as a duplicate (1) - for example, as in dataframe (b). In SPSS, I would simply compare each value to it's "lagged" value, but I can't figure out

I have Windows XP Professional Version 2002 and the R-Version 2.1.1. I did cluster analysis with the cluster package and the agnes (method = ?ward?). The results are satisfactory. But the dendrogram of agnes is confused to work with the results. Is there a tool, I can get a clear arrangement of the results for the cluster analysis. For example a matrix with different numbers for each group.

Hi, I would like to cut a vector of values in parts. Each part should have an equal number of elements. for example: x <- (rnorm(500)^2) now I want 5 vectors each with 100 elements. The first vector should include the 100 lowest values of x and so on (so that the fifth vector contains the 100 highest values of x). thanks for any help!

Or add the type column first and then rbind: x <- list(A=data.frame(x=1:2, y=3:4),B=data.frame(x=5:6,y=7:8)) x2 <- do.call(rbind, lapply(names(x), function(z) data.frame(type=z, dat[[z]]))) ---------------------------------------- David L Carlson Department of Anthropology Texas A&M University College Station, TX 77843-4352 -----Original Message----- From: R-help

Dear R experts, I have 2 matix: A& B. I am trying to index B against A - (1) find out B rows that fall between the col 1 and 2 of A& put them into a new vector SNP.I made code as below, but I cannot think of a right way to do it. Could anyone help me with the code? Thanks,Jiang---- A <-

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Hi For first question, maybe I am completely wrong but cor(swiss[,-1], swiss[,1]) should give you what you want in one step. Second question Without an example it is hard to say but maybe aggregate is the way forward. > aggregate(iris[,1:4], list(iris$Species), function (x) c(mean=mean(x), sd=sd(x))) Group.1 Sepal.Length.mean Sepal.Length.sd Sepal.Width.mean Sepal.Width.sd 1