similar to: Using package amelia

Hello R-sig-debian and (hopefully) Dirk: On Debian wheezy, I have the R packaging that CRAN (you) provide. I run into a little trouble while trying to fiddle with alternative BLAS. I know you and I went around on this last year and I think perhaps I've found something wrong in the framework, or I've just done something wrong. I installed the packages openblas-base and openblas-dev, and

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 all. First of all, my english isn't verry good, but I hope I can convey my concern. I've a general question about the Amelia algorithm. I'm no mathematician or statistician, but I had to use R and impute and analyse some data, and Amelia showed results that fitted my expectations. I'll have to defend my choice soon, but I haven't totally grasped what Amelia does. I'm

I am fairly new at using R/programming in general so I apologize if I am leaving crucial parts of the puzzle out, but here goes. First and foremost this is the error I am receiving: Error in muPriors[priors[, 1:2]] <- priors[, 3] : NAs are not allowed in subscripted assignments This occurs only when I am using observational priors and some number of nominal variables, it does not

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 <-

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

Hi, I have the following problem- I want to access a list whose elements are imp1, imp2, imp3 etc I tried theusing the paste comand in a for loop see the last for loop below. But I keep calling it df but df = imp1 (for the first run). Any ideas on how I can access the elements of the list? Isaac require(Amelia) library(Amelia) data.use <- read.csv("multiplecarol.CSV", header=T)

Hi everybody, I am quite new to data imputation, but I would like to use the R package ' Amelia II: A Program for Missing Data '. However, its unclear to me how the input for amelia should look like: I have a data frame consisting of numerous coulmns, which represent different experimental conditions, whereby each column has 3 replicates. I want amelia to perform an imputation across

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()

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 <-

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

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

[Apologies for the slightly-off-topic posting.] BizConf is a one-of-a-kind event that I am hosting about 3 months from now here in northern Florida. It''s a 2-day conference specifically crafted for independent consultants and owners/managers of small to mid-sized web consultancies. Because of who I am and the audience I can reach, I expect the majority of the attendees to be involved

On 2019-10-28 4:10 p.m., Jason Gunthorpe wrote: > From: Jason Gunthorpe <jgg at mellanox.com> > > Remove the interval tree in the driver and rely on the tree maintained by > the mmu_notifier for delivering mmu_notifier invalidation callbacks. > > For some reason amdgpu has a very complicated arrangement where it tries > to prevent duplicate entries in the interval_tree,

Am 28.10.19 um 21:10 schrieb Jason Gunthorpe: > From: Jason Gunthorpe <jgg at mellanox.com> > > Remove the interval tree in the driver and rely on the tree maintained by > the mmu_notifier for delivering mmu_notifier invalidation callbacks. > > For some reason amdgpu has a very complicated arrangement where it tries > to prevent duplicate entries in the interval_tree,

From: Jason Gunthorpe <jgg at mellanox.com> Remove the interval tree in the driver and rely on the tree maintained by the mmu_notifier for delivering mmu_notifier invalidation callbacks. For some reason amdgpu has a very complicated arrangement where it tries to prevent duplicate entries in the interval_tree, this is not necessary, each amdgpu_bo can be its own stand alone entry.

Hello, I am trying to make a data frame from many elements after running a function which creates many elements, some of which may not end up being real elements due to errors or missing data. For example, I have the following three elements p1s, p2s, and p3s. p9s did not generate the same data as there was an error in the function for some reason. I currently have to delete p9s from the

I''m not really sure the problem is a Plugin problem!! Note than a puppet client was installed, i change the setting of ip/hosname and try to re inscription the node to puppetmaster. I would like to understand what happen. The errors/warnings messages are not very easy to understand and sometime i''m lost. thank you for you advice. Eric Puppet version: 0.25.4-2ubuntu6

Hi Jason, I did quick test after merging amd-staging-drm-next with the mmu_notifier branch, which includes this set changes. The test result has different failures, app stuck intermittently, GUI no display etc. I am understanding the changes and will try to figure out the cause. Regards, Philip On 2019-10-28 4:10 p.m., Jason Gunthorpe wrote: > From: Jason Gunthorpe <jgg at

From: Jason Gunthorpe <jgg at mellanox.com> Convert the collision-retry lock around hmm_range_fault to use the one now provided by the mmu_range notifier. Although this driver does not seem to use the collision retry lock that hmm provides correctly, it can still be converted over to use the mmu_range_notifier api instead of hmm_mirror without too much trouble. This also deletes another