similar to: descriptive statistics

With rw2010dev I get a strange protect(): protection stack overflow error with a small data frame which otherwise is usable: If anybody wants to have a look I can provide an RData file with the problematic data frame. Doesn't seem to be necessary, the following simulated example generates the error: > testmat <- matrix(1:80, 20,4) > dim(testmat) [1] 20 4 > str(testmat) int

Hello everyone, I have a 2 x 5 matrix: say 0.2 0.3 1 -1 3 0.2. 0.4 5 0.5 -1 I want to replace all the values greater than or equal to 1 with 1 and those less than or equal to 0 with 0. So I should end up with a mtrix looking like: 0.2 0.3 1 0 1 0.2. 0.4 1 0.5 0 Any ideas how to do this? -- Thanks, Jim. [[alternative HTML version deleted]]

Hello All, I'm trying to run a maximum likelihood analysis using dmultinomial (i'm avoiding dmultinom as I'd like to run it with vectors for the ML stuff). However, I'm having a hard time getting even the simplest example running. Any help would be greatly appreciated. > library(mc2d) > dmultinomial(x=c(0,0,1),prob=c(1,1,1),size=1,log=TRUE) Error in if (ncol(x) != K)

Hi, Thanks Sarah. Unfortunately I did not get a step further. My question, perhaps a bit clearer, is how to display the case control status (or any other arbitrary point label) after clustering in a plot: With a bit of pseudo code, where dataset is a data.frame, parameters are those column names where we find numerical values (no NAs) and nclasses is the desired number of classes. fit <-

Here's the problem I'm trying to solve in R: I have a data frame that consists of about 1500 cases (rows) of data from kids who took a test of listening comprehension. The columns are their scores (1 = correct, 0 = incorrect, . = missing) on 140 test items. The items are numbered sequentially and are ordered by increasing difficulty as you go from left to right across the columns. I want

Hello, I have a question in regards to markov chains and transition probabilities. I am trying to figure out a way to calculate the "kth-step transition matrix" of a given matrix. Say for example I have a single step 2x2 matrix: 1 2 P= 1 .95 .05 2 .01. 99 If I were to convert this matrix to a 2-step transition probability matrix I would get:

Hello, I am very new to R (as my Subject probably indicates). I want to do something that should, I think, be very simple. I have five vectors in a list and I want to construct a covariance matrix out of them. Given a 5X5 matrix cvm1, and the list of vectors, cvm1_list, I thought the following would work (sorry cannot find code tags): for(i in 1:5){ for(j in 1:5){ cvm1[i,j] <-

Hi, I am not sure to get the issue, but assuming your data are arranged as in your example with dates in column x$V1 and signals as x$V2 , I think that you could use "rle" in the following way : test<-rle(x$V2) testmat<-matrix(NA,length(test$values),2) testmat[,1]<-x[c(1,cumsum(test$length)[1:(length(test$values)-1)]+1),1] testmat[,2]<-test$values And you'll get your

Hi, The Matrix package and the as.matrix method do not seem to be compatible inside of a package. Here's an example. I've created a simple package "mat" that defines an eponymous class and as.matrix method on that class. All is well, unless that package has the Matrix package in its Depends or Imports (and imports, e.g. the "Diagonal" function). Then my as.matrix

Georgi, Brilliant, thank you very much for the helpful reply and explanation! I added 'importFrom("Matrix","as.matrix")' to my NAMESPACE and all worked fine! As my 'as.matrix' method is used entirely internally to the 'testmat' function (and not "used outside the package"), I don't think I actually need to export it. In my case, testmat is

Hi, Short answer: import 'as.matrix' and export your method(s) for it. From WRE: "All S4 classes to be used outside the package need to be listed in an exportClasses directive. Alternatively, they can be specified using exportClassPattern.(46) in the same style as for exportPattern. To export methods for generics from other packages an exportMethods directive can be used."

Hi, all, I'm running multiple imputation to handle missing data and I'm running into a problem. I can generate the MI data sets in both amelia and the mi package (they look fine), but I can't figure out how to get pooled results. The examples from the mi package, zelig, etc., all seem to go right to something like a regression, though all I want are the mean and SE for all the

Hi I have four variables and the time series data for each variable consists of values for past 10 years on monthly basis. I want to get descriptive stats for these four variables separately (mean, median, sd, min, max). The data I import to R consists of different columns, where each column gives values for one month of a particular year (e.g. March 31st, 2010). Right now R gives descriptive

For mean() and sd() you need to convert the data frame to a matrix (I'm guessing here since you did not show us the structure of your data). The min() and max() functions should work on the data frame just fine. If you have other columns in the data frame, extract the monthly columns first. > set.seed(42) > x <- data.frame(matrix(rnorm(100), 20, 5)) > str(x) 'data.frame':

I have a lot (more than one hundred) of files with tables of the same kind (quadratic, same size) and I want to obtain some statistics for every position on them. Therefore, as a result I want another table. I import every table, and create an object “read.table” for it, then I have try to create a “list” or a “data frame“ and directly utilize some functions like sd( ) without success, because it

Hi all, I'm looking for a package that will give me comprehensive set of descriptive statistics, including skew and kurtosis. Also, is there a similar package that will provide multivariate descriptive statistics as well? Thanks in advance, David -- =========================================================================== David Kaplan, Ph.D. Professor Department of Educational

I am still trying to get used to R, and apparently haven't found the right place in the documentation to see how to do what I want in R. If I were to do this in C++, there'd be no problem: I'd write it all myself, but I want to learn R well enough it can save me a lot of coding time. Here is the first task I set for myself. I have a datasource (a vector of values). I want to

(I checked the archive and it seems the entire text of my post was 'scrubbed' - trying again) Hello, I'm looking for help on the best approach to get "multi-value" data fields into R for simple descriptive analysis. ------------------------------------- I am new to this list and new to R, but I really want to get over the hump and get productive with it. Some help with

I feel really dumb for having to ask this, but here I go anyway... I perform structural equation modeling on a survey, using about 25 variables that create a total of 5 latent variables (factors). Applying sem (using the sem package) was a piece of cake, even for an (SEM) layman, thanks for THE excellent work here. I have all the variable/path coefficients, A- and P-matrix etc. But now I am

when I try to make a package coping R code such as tab1, summ, titleString, setTitle from epicalc package, the following problems are found. * using log directory 'C:/Rpackage/EpiStat.Rcheck' * using R version 2.10.0 (2009-10-26) * using session charset: ISO8859-1 * checking for file 'EpiStat/DESCRIPTION' ... OK * checking extension type ... Package * this is package