similar to: Missing data augmentation

I am desperately trying to impute missing data using 'imp.mix' but always run into this yucky error message to which I cannot find the solution. It's the first time I am using mix and I'm trying really hard to understand, but there's just this one step I don't get...perhaps someone knows the answer? Thanks! Jens My code runs:

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.

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 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

Hello all, When I ran my R program in R version 2.1.1 in windows XP and 2000, and I downloaded a package call "MIX", I got an application error: RGui:Rgui.exe - Application Error: The instruction at "0x1009d8a1" referenced memory at "0xbde48f58". The memory could not be "read". Click on ok to terminate the program click on cancel to debug the program

Hi all, When using package MIX, I often get the error: NA/NaN/Inf in foreign function call (arg 1). For example, > s<-prelim.mix(Y,6) Error in prelim.mix(Y, 6) : NA/NaN/Inf in foreign function call (arg 1) or when I ran: MI<-vector("list",5) #<--vector of complete data after MI fit.model.mi<-vector("list",5) rngseed(1234567) #<-- set random number

Hello, We use the mix package and we have a problem with the DA function. We aren't sure, but it's maybbe a memory problem. We have done: > Ent<--read.table("C:/.../File.txt") > attach(Ent) > Ent V1 V2 V3 V4 ... V16 V17 1 1 1 2 6 18 18 2 1 1 1 NA 14 17 3 1 1 2 1 16 14 .... 199 2 1 NA 7 19 18 200

Dear Professor Schaefer I am experiencing a technical difficulty with your mix package. I would appreciate it if you could help me with this problem. When I run the following code, R 2.5.1 and R 2.6.0 crashes. It's been tested on at least 2 windows machine and it is consistent. Execution code it's self was coped from the help file of imp.mix. Only thing I supplied was a fake dataset.

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

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, >

Dear list, I'd like to use multiple imputations to try and save a somewhat badly mangled dataset (lousy data collection, worse than lousy monitoring, you know that drill... especially when I am consulted for the first time about one year *after* data collection). My dataset has 231 observations of 53 variables, of which only a very few has no missing data. Most variables have 5-10% of

Dear R-users I need to calibrate kappa, rho, eta, theta, v0 in the following code, see below. However when I run it, I get: y <- function(kappahat, rhohat, etahat, thetahat, v0hat) {sum(difference(k, t, S0, X, r, implvol, q, kappahat, rhohat, etahat, thetahat, v0hat)^2)} > nlminb(start=list(kappa, rho, eta, theta, v0), objective = y, lower =lb, > upper =ub) Error in dots[[1L]][[1L]] :

Hi all, I'm currently working with a dataset that has quite a few missing values and after some investigation I figured that multiple imputation is probably the best solution to handle the missing data in my case. I found several references to functions in S-Plus that perform multiple imputation (NORM, CAT, MIX, PAN). Does R have corresponding functions? I searched the archives but was not

Hi all, I am running a series of experiments where after manipulating my data I run several clustering algorithms (agnes, diana and a clustering method of my own) on the data. I wanted to determine which clustering method did the best job, so therefore I had defined my own quality measure using two criteria: compactness of the data within the clusters themselves and the amount of seperation

Hi all, I was wondering whether it is possible to plot math functions, for example sin, cos or a Gaussian type function, in R, and if so, how to do it. I have been searching through the archives and the R manual but had no luck in finding any hints on how to go about this. Any help is much appreciated! Thanks, Jonck

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

Hi all, I have (yet another) question about a function in R. What I would like to do is test for the presence of a certain value in a vector, and have the positions that this value is at returned to me. For example, let's say I have a vector: x <- c(1,1,2,2,3,3,4,4) Now I would like a function that would return positions 3 and 4 should I test for the value "2". Or 5 and 6

Hello everyone, I'm new to this list, so let me introduce myself: my name is Jonck van der Kogel and I am a graduate student at the Erasmus University of Rotterdam. I am currently working on my thesis which is on the use of artificial intelligence for large data-sets. To do an analysis of a certain data-set I want to use Kohonen's SOM algorithm. However, as I understand it, the SOM

Hi all, I am having a bit of trouble with the array structure of R. What I want to do is dynamically add/remove elements to an array. For example: Let's say I have created an array: > myArray <- array(c(3,8), dim=c(1,2)) > myArray [,1] [,2] [1,] 3 8 And I now want to, for example, push an element (5,6) on to this array so it will read: [,1] [,2] [1,] 3 8

Hi all, I have a question about the SOM routine. You can either supply the initial representatives for the lattice yourself or else they are chosen randomly from the dataset. Is it possible to pass the random-seed as an argument somehow, when choosing the random initialisation of the lattice? As it is now, each time I run a SOM on a dataset with the same settings the resulting SOM will still