similar to: cut and re-factor data

Hello Everyone, My name is Thomas and I have been using R for one week. I recently found your site and have been able to search the archives of posts. This has given me some great information that has allowed me to craft an initial design to an inquiry I would like to make into the breakdown of McNemar's test. I have read an intro to R manual and the posting guides and hope I am not violating

Dear r user, please find my attached sample of the dataset i? am using to create a crosstable and eventually plot a histogram from the output. I am using? the cut2 function to create bins, about 7 of them using the code after reading the data: cluster <- cut2(cross_val$value, g=7) I get the warning: Warning message: In min(xx[xx > upper]) : no non-missing arguments to min; returning Inf

I am trying to run a confirmatory factor analysis using the SEM package. My data are ordinal. I have read http://socserv.mcmaster.ca/jfox/Misc/sem/SEM-paper.pdf. When I apply the hetcor function, I receive the following error: Error in checkmvArgs(lower = lower, upper = upper, mean = mean, corr = corr, : at least one element of 'lower' is larger than 'upper' Example:

Hi, I've been running some simulations for a while and the performance of R has been great. However, I've recently changed the code to perform a sort of chi-square goodness-of-fit test. To get the observed values for each cell I've been using table() - specifically I've been using cut2 from Hmisc to divide up the range into a specified number of cells and then using

To R users, I am trying to use cut2 function from the 'Hmisc' library. However, when I try and run the function on the following variable, I get an error message (displayed below). I suspect it is because of the NA but I have no idea how to address the error. Many thanks to any insights. structure(list(var1 = c(97, 97, 98, 98, 97, 99, 97, 98, 99, 98, 99, 98, 98, 97, 97, 98, 99, 98,

Greetings R users, My goal is to generate quartile groups of each variable in my data set. I would like each experiment to have its designated group added as a subsequent column. I can accomplish this individually with the following code: brks <- with(data_variables, cut2(var2, g=4)) #I don't want the actual numbers, I need a numbered group data$test1=factor(brks,

Hello, I'm using the Hmisc cut2 function to bin a set of data. It produces bins that I like with results like this: [96,270]:171 [69, 96): 54 [49, 69): 40 [35, 49): 28 [28, 35): 14 [24, 28): 8 (Other) : 48 I would like to take a second set of data, and assign it to bins based on factors defined by my call to cut 2. Does anyone know how I can do this? Thank you, -S -- View this message

Hello, I have a set of data with two columns: "Target" and "Actual". A http://n4.nabble.com/file/n1584647/Sample_table.txt Sample_table.txt is attached but the data looks like this: Actual Target -0.125 0.016124906 0.135 0.120799865 ... ... ... ... I want to be able to break the data into tables based on quantiles in the "Target" column. I can see (using

Dear all, I would like to aggregate a data frame (consisting of 2 columns - one for the bins, say factors, and one for the values) along bins and quantiles within the bins. I have tried aggregate(data.frame$values, list(bin = data.frame $bin,Quantile=cut2(data.frame$bin,g=10)),sum) but then the quantiles apply to the population as a whole and not the individual bins. Upon this

Hi, I have produced a dendrogram of categorical data in R using the hclust function, although the input was a dissimilarity matrix produced in SAS, as I have defined my own distances. The dendrogram is fine and I can view and use this. However, I was wondering if there is a method by which I can find out the optimal place to place groups, rather than relying on my visual analysis? I don't

Hi all, I have a vector of proportions (post_op_prw) such that >summary(amb$post_op_prw) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0.0000 0.0000 0.0000 0.3985 0.9134 0.9962 1.0000 > summary(cut2(amb$post_op_prw,0.0001)) [0.0000,0.0001) [0.0001,0.9962] NA's 1904 1672 1

Hi, Design isn't strictly an R base package, but maybe someone can explain the following. When lrm is called within a function, it can't find the dataset dd: > library(Design) > age <- rnorm(30, 50, 10) > cholesterol <- rnorm(30, 200, 25) > ch <- cut2(cholesterol, g=5, levels.mean=TRUE) > fit <- function(ch, age) + { + d <- data.frame(ch, age) +

Dear R-users: I can not reproduce figure 4 of *Statistical Tables and Plots using S and LATEX* by Prof. Frank Harrell with the following code: rm(list=ls()) library(Hmisc) getHdata(pbc) attach(pbc) age.groups <- cut2(age, c(45,60)) g <- function(y) apply(y, 2, quantile, c(.25,.5,.75)) y <- with(pbc, cbind(Chol=chol,Bili=bili)) # You can give new column names that are not legal S names

Full_Name: Chris Hane Version: 2.10.1 OS: Windows Submission from: (NULL) (198.203.181.181) When using barchart in the flexcust package, setting mcol=NULL to avoid the lollipops causes an error. Each panel shows the text message "Error using packet n replacement has length zero." where n is the panel number. > data(iris) > cl <- cclust(iris[,-5], k=3) > barplot(cl,

Dear list I try to run a bootstrap with lmer. I often, but not always, get the error message: Error in objective(.par, ...) : Leading minor of order 6 in downdated X'X is not positive definite (with the number (here 6) varying) In R-archives I came across some threads that treated this problem, nevertheless they refer to lmer when using it with family = "binomial", so the

What is the best way to create a drop down where the viewable text in a concatenation of 2 or more columns? For instance, I hane a lookup table with these columns. Model FOO columns: id , name, phone In my drop select tag, I''d like the user to see: "name1 phone1" "name2 phone2" etc.. I know I can do this using find_by_sql . .. But, isn''t there a more

I have a xen server setup that I want to install a lot of vms on if possible. The vms will have no utilization for the most part; and brief utilization when active. The server has 2GB of RAM. We were running into a problem were the dom0 would not let us add anymore vms because we were out of physical memory. I have started to read about memory ballooning and hoping someone could point me

Hello, I'm trying to bin a quantity into 2-3 bins for calculating entropy and mutual information. One of the approaches I'm exploring is the cut() function, which is what the mutualInfo function in binDist uses. When it's called in the format cut(data, breaks=n), it somehow splits the data into n distinct bins. Can anyone tell me how cut() decides where to cut? Thanks, Melissa

Hello, I am trying to "paste" together a formula to use in the mob function of party. This means the formula will be of the form y ~ x1+ ...+xM | z1+..zN. I am doing some preliminary fits of y ~ x1+ ...+xM, then want to add the conditional part of the equation using update(). Here's the test code: var1 <- 1:78 x1 <- paste("x", var1, sep="") f1 <-

Hello, What is the best way to get ranks for a vector of values, limit the range of rank values and create equal count in each group? I call this uniform ranking...uniform count/number in each group. Here is an example using three groups: Say I have values: x = c(3, 2, -3, 1, 0, 5, 10, 30, -1, 4) names(x) = letters[1:10] > x a b c d e f g h i j 3 2 -3 1 0 5 10 30 -1 4 I