similar to: MI help

Hi all, I am hardly an expert, so I expect that this code is not the easiest/ most efficient way of getting where I want. Any suggestions in that direction would also be helpful. I am working on panel analysis with five imputed datasets, generated by Amelia. To do panel analysis, it seemed that the plm package was the best, providing a convenient wrapper for fixed and random effects

Hi, There seems to be a problem with setGroupGeneric() from package 'methods'. The symptoms are somewhat erratic, in the sense that small changes may lead to any of the following behaviours. 1.Package works without problems on Windows and installs on Linux but gives error when loaded with library(). 2.Package installs on both systems and gives error when loaded on any of them. 3.

Hi, I am having some trouble using R 2.13.1 for generating a pmml object of of class "c('randomForest.formula', 'randomForest')" I see that these methods are available: > methods(pmml) [1] pmml.coxph* pmml.hclust* pmml.itemsets* pmml.kmeans* pmml.ksvm* pmml.lm* pmml.multinom* pmml.nnet* pmml.rpart* [10] pmml.rsf* pmml.rules* pmml.survreg*

From: <david_foreman at doctors.org.uk> Subject: [R] Re: extracting datasets from aregImpute objects To: <r-help at stat.math.ethz.ch> Message-ID: <1092391719_117440 at drn10msi01> Content-Type: text/plain; charset="us-ascii" I've tried doing this by specifying x=TRUE, which provides me with a single imputation, that has been useful. However, the help file

Hi I have used the amelia command from the Amelia R package. this gives me a number of imputed datasets. This may be a silly question, but i am not a statistician, but I am not sure how to combine these results to obtain the imputed dataset to usse for further statistical analysis. I have looked through the amelia and zelig manuals but still can not find the answer. This maybe because I dont

Hi R experts, I have been playing with library(XML) recently and found out that readHTMLTable workls flawlessly for some website, but it does give me an error like below ... Error in function (classes, fdef, mtable) : unable to find an inherited method for function "readHTMLTable", for signature "NULL" let's say..for example, this code works fine a

R-users & helpers: I am using Amelia, mitools and cmprsk to fit cumulative incidence curves to multiply imputed datasets. The error message that I get "Error in eval(expr, envir, enclos) : invalid 'envir' argument" occurs when I try to fit models to the 50 imputed datasets using the "with.imputationList" function of mitools. The problem seems to occur

Dear forum,   I am working in R 2.9.1 and I am trying to sample locations from a network file. Reading in nor plotting is a problem, however when I am trying to sample from the file I get the following message:   nwlim<-readShapeLines("C:/Limburg_nwshape", proj4string=CRS("+init=epsg:31300")) plot(nwlim)   randacc<-spsample(nwlim,n=1000,"random")

Hi, I want to impute a data set multiple times with Amelia, but the data set is large so it takes a long time. As a result, I'm trying to run the multiple imputation with parallel processors in Windows, but am having trouble. Here is a quick example: ###### library(foreach) library(doSNOW) registerDoSNOW(makeCluster(4, type = "SOCK")) getDoParWorkers() getDoParName()

Hello all, I am trying to impute some missing data using the mice package. The data set I am working with contains 125 variables (190 observations), involving both categorical and continuous data. Some of these variables are missing up to 30% of their data. I am running into a peculiar problem which is illustrated by the following example showing both the original data (blue) and the imputed

Dear R-group, Could somebody recommend a package that can deal with a multinomial response variable (choice of breeding tactic in mice, which has four unordered levels), multiply-imputed data (generated using the Amelia package) and two non-nested random effects: individual identity (133 individuals made up to four choices each) and year (for which there are six levels and sample size varies

Hello Everyone, I am writing programs in R from 7 months and I am able to solve most of the errors/issues except for this current post. My Task is to read a Microsoft Excel file(textE_to_affy.csv) which contains the Microarray Expression Values collected from the Illumina Microarray experiment. These collected intensity values need to be normalized(Rank Invariant Normalization) by using the R

I've been trying to get some linear classifiers (LiblineaR, kernlab, e1071) to work with a sparse matrix of feature data. In the case of LiblineaR and kernlab, it seems I have to coerce my data into a dense matrix in order to train a model. I've done a number of searches, read through the manuals and vignettes, but I can't seem to see how to use either of these packages with sparse

Due to missing data with some of my predictor variables I first do multiple imputation as follows: library(foreign) library(Amelia) library(norm) set.seed(666) M=10 impdat <-

Hi, We've observed rather strange behavior related to as(). When as() is used to make a conversion to a super class, an invalid entry is inserted into the table of methods. > setClass("A", contains="list") > get(".MTable", environment(coerce))[["list#A"]] NULL > as(list(), "A") > get(".MTable",

Hello, I haven't been able to find an example for the second case below -- or perhaps I didn't recognize it when I saw it. Is there a value for x such that svalue(x) will return "bbb", either by itself or as part of an array? Or do I need to do something else entirely? (R2.5.1; Windows XP) > #### gWidgets test > options("guiToolkit"="tcltk") >

R-helpers: I am using R 2.5 on Windows XP, packages all up to date. I have run into an issue with the MIcombine function of the mitools package that I hoped some of you might be able to help with. I will work through a reproducible example to demonstrate the issue. First, make a dataset from the pbc dataset in the survival package --------------- # Make a dataset library(survival) d <-

List, Last week with the help of Uwe and some other folks I was able to get RMySQL 0.5-7 compiled against R 2.4.1 and MySQL 5.0.27. It was working fine--I was able to send select queries to the db, put the results in a data frame, and so forth. Today, dbDriver() threw an error: > dbDriver(MySQL) Error in function (classes, fdef, mtable) : unable to find an inherited method for

I am extending a DBI connection by setClass("TSPostgreSQLConnection", contains=c("PostgreSQLConnection","TSdbOptions")) but the first time I use this I am getting a warning when it tries to coerce the TSPostgreSQLConnection to a PostgreSQLConnection. After the first use the warning stops, but the first warning is causing me problems when I do automatic checks

Colleagues, I have started working with Amelia, with the aim of imputing missing data for time-series data. Although I have succeeded in getting Amelia to perform the imputation, I have not found any documentation describing how Amelia imputes time-series data. I have read the basic Amelia documentation, but it does not address how time-series data are imputed. The documentation describes