similar to: da.norm function

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:

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

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

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

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

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

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

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.

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

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

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]] :

Dear all, I have a function to optimize for a set of parameters and want to set a constraint on only one parameter. Here is my function. What I want to do is estimate the parameters of a bivariate normal distribution where the correlation has to be between -1 and 1. Would you please advise how to revise it? ex=function(s,prob,theta1,theta,xa,xb,xc,xd,t,delta) { expo1=

Dear list I am calling the functiton bugs() provided by R2WinBugs to performs an IRT analysis. The function returns a set of estimated parameters over n replications/iterations. For each replication, two sets of person measures (theta1 and theta2) and two sets of item difficulty parameters (diff1 and diff2) are returned. The code used to obtain these estimates is as follows: sim <-

Can any one help me to solve problem in my code? I am actually trying to find the stopping index N. So first I generate random numbers from normals. There is no problem in finding the first stopping index. Now I want to find the second stopping index using obeservation starting from the one after the first stopping index. E.g. If my first stopping index was 5. I want to set 6th observation from

Dear Bert, Thank you so much for your kind and valuable feedback. I tried finding the starting values using the approach you mentioned, then did the following to fit the nonlinear regression model: nlregmod2 <- nls(y ~ theta1 - theta2*exp(-theta3*x), start = list(theta1 = 0.37, theta2 = exp(-1.8), theta3 =

Oh, sorry; I changed signs in the model, fitting theta0 + theta1*exp(theta2*x) So for theta0 - theta1*exp(-theta2*x) use theta1= -.exp(-1.8) and theta2 = +.055 as starting values. -- Bert On Sun, Aug 20, 2023 at 11:50?AM Paul Bernal <paulbernal07 at gmail.com> wrote: > Dear Bert, > > Thank you so much for your kind and valuable feedback. I tried finding the > starting

Hi everybody: I?m trying to rewrite some routines originally written for SAS?s PROC NLMIXED into LME4's glmer. These examples came from a paper by Nelson et al. (Use of the Probability Integral Transformation to Fit Nonlinear Mixed-Models with Nonnormal Random Effects - 2006). Firstly the authors fit a Poisson model with canonical link and a single normal random effect bi ~ N(0;Sigma^2).The

Dear Bert, Thank you for your extremely valuable feedback. Now, I just want to understand why the signs for those starting values, given the following: > #Fiting intermediate model to get starting values > intermediatemod <- lm(log(y - .37) ~ x, data=mod14data2_random) > summary(intermediatemod) Call: lm(formula = log(y - 0.37) ~ x, data = mod14data2_random) Residuals: Min

Basic algebra and exponentials/logs. I leave those details to you or another HelpeR. -- Bert On Sun, Aug 20, 2023 at 12:17?PM Paul Bernal <paulbernal07 at gmail.com> wrote: > Dear Bert, > > Thank you for your extremely valuable feedback. Now, I just want to > understand why the signs for those starting values, given the following: > > #Fiting intermediate model to get