similar to: Amelia imputation - column grouping

Dear R users and developers, I have a dataset containing 34 variables measured in a survey, which has some missing items. I would like to conduct a factor analysis of this data. I tested mi, Amelia, and MissForest as alternative packages in order to impute the missing data. I now have 5 separate datasets with the variables I am interested in factor analysing. In my reading of the package

Hi, i would like to plot a few hundred .csv files. Each file contains one curve with x,y values to plot. I have been searching for "gnu r read many files qplot" and similar words. I found for loops that use assign to generate one variable containing a dataframe. When i uesed the classic "plot' command i could add the curves with something like for... {

Hello, Is there a function in R by which one can run AR model with Bayesian Information Criteria (BIC)? To my knowledge, functions ar and ar.ols could select the order only by AIC. Thanks, Miao [[alternative HTML version deleted]]

Hi all, I want to test whether the MEAN of two different variables, (and different number of observations) are the same. I am trying to use the anova test but it doesn't seem to like that the number of observations are different: a=c(1:5) b=c(1:3) aov_test=aov(a~b) >>Error in model.frame.default(formula = a ~ b, drop.unused.levels = TRUE) : variable lengths differ (found for

Dear colleagues. I wonder if anybody knows about a procedure in R to calculate the Berger-Parker index and the Brillouin Diversity index. I searched the net but did not find anything good about it. Thanks a lot for any help Mayo, Elvira. [[alternative HTML version deleted]]

Hello, I am totally new in the field of time series analysis and forecasting and R. I read that R is a powerful tool for time series. Could anyone give me navigation what models of time series are availiable in R etc? -- View this message in context: http://r.789695.n4.nabble.com/Time-Series-Analysis-and-Forecasting-tp4646637.html Sent from the R help mailing list archive at Nabble.com.

Dear all, Is there a simple way to add reference lines in background? I am trying with abline() or grid() but the lines, since they are executed after the plot function, are draw on top. How can I draw such lines beneath the main plot? Here is an example: x<-rnorm(100) boxplot(x) abline(h=c(-1,0,1)) grid(NA, 4, lwd = 2) regards, Luigi Marongiu, MSc [[alternative HTML

Hello! I would like to make a scatterplot of my data, but the problem is that several points have the same x and y values and are represented as only one point. I wonder if there is a way to represent the data points, but with point size representing the frequency of the depicted x-y value? Thank you! -- View this message in context:

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

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

noob here trying to make boxplots of some data i would like to separate the boxplots according to conditons of various levels for example: i have group:1 and 2, each group performed tests consisting of condition A,B,C,D side: left and right time: 1 to 10 I would like separate boxplots of the results (x) of the tests (numeric) for each group under each condition on each side over time. so far i

Hello all, if I have multiple imputed data sets, is there a command or function in R in any package you know of to combine those, I know one common MI approach is rubins rules, is there a way to do this using his rules or others? I know theres ways, like using Amelia from Gary King's website to create the imputed data sets, but how to make them into one or combine them for analysis.

I'm trying to use either mice or norm to perform multiple imputation to fill in some missing values in my data. The data has some missing values because of a chemical detection limit (so they are left censored). I'd like to use MI because I have several variables that are highly correlated. In SAS's proc MI, there is an option with which you can limit the imputed values that are

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()

Hi, I am a long time SPSS user but new to R, so please bear with me if my questions seem to be too basic for you guys. I am trying to figure out how to analyze survey data using logistic regression with multiple imputation. I have a survey data of about 200,000 cases and I am trying to predict the odds ratio of a dependent variable using 6 categorical independent variables (dummy-coded).

Hello I do not think I have fully grasped how to use Amelia to deal with missing data. For instance, suppose I have a data.frame variable with 4 columns (year, mon, ssn, dev) = (year, month, measurements, standard deviation of the measurement). Of course, there are some random missing values on columns 3 and 4. The measurements are an almost periodic time-series contaminated by noise.

Hi, Many apologies for sending this twice. I accidentally hit the send button before I finished writing my mail. I am new to R and I hope someone can help me with my problem. I am trying to draw a side by side barplot. There is a main experiment and there are many sub experiments within the main experiment. I would like to draw a bar plot showing the number and type of sub_experiments done for

Hi, I've installed Samba and started up the processes; however, I do not see the Samba server in Network Neighborhood. In using the DIAGNOSIS.txt file, I cannot get past test 3: ./smbclient -U% -L localhost. The output is as follows: added interface ip=140.188.120.55 bcast=140.188.120.255 nmask=255.255.255.0 session setup failed: Call returned zero bytes (EOF) Any insight into this

[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

I'm looking for a package that has a start-of-the-art method of imputation of missing values in a data frame with both continuous and factor columns. I've found transcan() in 'Hmisc', which appears to be possibly suited to my needs, but I haven't been able to figure out how to get a new data frame with the imputed values replaced (I don't have Herrell's book). Any