similar to: problem (bug?) with prelim.norm (package norm)

R-experts: I am trying to reproduce some of Paul Allison's results in his little green book on missing data (Sage 2002). The dataset for which I am having problems, "usnews", can be found at: http://www.ats.ucla.edu/stat/books/md/default.htm. I am working on a Windows machine with R 2.5 installed, all packages up-to-date. The problem has to do with the prelim.norm() function of the

Hey eveyone! I hope someone can help wiht this question. I have a matirux of all zeros and ones and I would like to indentify all unique patterns in the rows andthe number of times the pattern occurs. I changed all zeros to NA tried to use prelim.norm to identify all patterns of missing data in the rows. I got the message Warning message: NAs introduced by coercion Any ideas of how

Hi everyone, I'm trying to use prelim.norm with a "big" matrix (36 columns by 10000 or so rows). I found that prelim.norm has a built-in limit of 30 columns, but I'd still really like to use it for my data. Does anyone know of a different way to do the same thing? Or, would it be easier to try to modify the source code? Thanks! Josh

Dear alltogether, I experience very strange behavior of imputation of NA's with the NORM library. I use R 2.2.0, win32. The code is below and the same dataset was also tried with MICE and aregImpute() from HMISC _without_ any problem. The problem is as follows: (1) using the whole dataset results in very strange imputations - values far beyond the maximum of the respective column, >

Greetings! I am bootstrapping and I am using EM in the norm package to fill in missing data for a financial time series with each step of the loop. For the most part EM works fine for me, but the following error message is guaranteed before I hit the 200th scenario: Iterations of EM: 1...2...3........348...349...Error: NA/NaN/Inf in foreign function call (arg 2) The following code should

'sodexquan' is an data frame of numeric variables with some missing values. I would like to approximate these missing values using some algorithm. I thereby chose the mix package. But when trying to run the 'prelim.mix' function (aka the function that will prepare the data for further calculations), R says: prelim.mix(truc,0) Error in as.integer.default(list(c(32, 52, 32, 27, 34,

Hi Folks, I'm using the 'norm' package (based on Shafer's NORM) on some data. In outline, (X,Y) are bivariate normal, var(X)=0.29, var(Y)=24.4, cov(X,Y)=-0.277, there are some 900 cases, and some 170 values of Y have been set "missing" (NA). The puzzle is that, repeating the multiple imputation starting from the same random seed, I get different answers from the repeats

I am conducting a simulation study generating multivariate normal data, deleting observations to create a data set with missing values and then using multiple imputation via da.norm in Schafer's norm package. >From da.norm, I get the following error message: "Error: NA/NaN/Inf in foreign function call (arg 2)" The frequency of the error message seems to depend on the ratio of n

Greetings, I'm getting this error message using Joe Shafer's "NORM" package. Error in storage.mode(x) <- "double" : (list) object cannot be coerced to type 'double' I'm not sure what this means. I get this message when running s <- prelim.norm(filename) prelim.norm is used to develop some summary statistics, etc. before implementing the EM

Here is a problem that perhaps someone out here has an idea about. It vaguely reminds me of something I've seen before, but can't place. Can anyone help? For multiple imputation, there are simpler methods available if the patterns of missing data are 'monotone' --- if Vj is missing then all variables Vk, k>j are also missing, vs. more complex methods required when the

Hi all, A short while ago I asked a question about multiple imputation and I got several helpful replies, thanks! I have untill now tried to use the packages mice and norm but both give me errors however. mice does not even run to start with and gives me the following error right away: iter imp variable 1 1 Liquidity.ratioError in chol((v + t(v))/2) : the leading minor of order 1 is not

Dear R-help, I am trying to impute missing data for the first time using R. The norm package seems to work for me, but the missing values that it returns seem odd at times -- for example it returns negative values for a variable that should only be positive. Does this matter in data analysis, and/or is there a way to limit the imputed values to be within the minimum and maximum of the actual

I have a data matrix X (n x k, say) each row of which constitutes an observation of a k-dimensional random variable which I am willing, if not happy, to assume to be Gaussian, with mean ``mu'' and covariance matrix ``Sigma''. Distinct rows of X may be assumed to correspond to independent realizations of this random variable. Most rows of X (all but 240 out of 6000+ rows)

There is a problem when importing an spss-file containing explicitly declared missing values in R using the read.spss function from the foreign package. I'm not sure these problems are the same in every version of spss, I am using the latest version 16.0.2. I included http://www.nabble.com/file/p18776776/missingdata.sav missingdata.sav and

Dear All, Trying to install package 'norm' under linux-mandrake8.2 I've got the following messages: R CMD INSTALL norm_1.0-9.tar.gz * Installing *source* package 'norm' ... ** libs g77 -mieee-fp -O3 -fomit-frame-pointer -pipe -mcpu=pentiumpro -march=i586 -fno-fast-math -fno-strength-reduce -O3 -fomit-frame-pointer -pipe -mcpu=pentiumpro -march=i586 -fno-fast-math

Hello, I apologize if an answer to my questions is available, or if I submitted this question incorrectly. I have read the mailing lists, as well as the R Project and CRAN homepages. However, I may have missed something. I noticed the package 'norm' has been removed. Its page http://cran.r-project.org/web/packages/norm/index.html now reads: "Package ?norm? was removed from the CRAN

Hello all I'm running da.norm function in R for climate data rngseed(1234567) theta1=da.norm(mydata, thetahat, steps=1000,showits=T) param1=getparam.norm(mydata,theta1) As I understand the 1000 steps represent the markov chain values. Is there a way to plot them? Something like plot(1:1000, param1$mu[]). I just can't find a way to extract them out of my theta1. Thank you, Andrey.

Hello and apologies if this is a stupid question (just rejoined the list): Has anything changed with the norm() function with the latest update of the Matrix library? My old code seems not to be working properly even for very simple tests of the norm function. I get too many "No direct or inherited method for function "norm" for this call" messages. I am using windows, R

Have you used Tinn-R and what landmines await the inexperienced? I could not understand why a script that used to work stopped working. Look at these two scenarios I opened an excel spreadsheet and copied several cells to the clipboard Then Scenario 1 Executed from Tinn-R > prelim<-read.delim("clipboard") > str(prelim) 'data.frame': 0 obs. of 1 variable: $

Hi in matlab I defined a function (double gamma, parameters at the end of this mail) as h(i)=((t/d1)^a1)*exp(-(t-d1)/b1)-c*((t/d2)^a2)*exp(-(t-d2)/b2); h=h/norm(h); I do know that norm() in matlab is equal to: sqrt(sum(x^2)) in R so in R I do it like: #function (double gamama) h <- expression((t/d1)^a1*exp(-(t-d1)/b1)-c*(t/d2)^a2*exp(-(t-d2)/b2)) # plot it t <- seq(0, 20000,