similar to: function ms

Hi the list, I am writing a package in S4 and I do not manage to understand a bug. The "R CMD check" and the "R CMD build" both work. Here is links to the package (not on CRAN yet for the raison that I explain bellow): http://christophe.genolini.free.fr/aTelecharger/kml_0.5.zip http://christophe.genolini.free.fr/aTelecharger/kml_0.5.tar.gz Then I install the package and I

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

Hello, I have a general question about combining imputations as well as a question specific to the rms and Hmisc packages. The situation is multiple regression on a data set where multiple imputation has been used to give M imputed data sets. I know how to get the combined estimate of the covariance matrix of the estimated coefficients (average the M covariance matrices from the individual

Hello colleagues, This is a follow up to a question I posed in November regarding an analysis I was working on. Thank you to Dr. Brian Ripley and Dr. John Fox for helping me out during that time. I am conducting logistic regression on data set on psi (ESP) ganzfeld trials. The response variable is binary (correct/incorrect), with a 25% guessing base rate. Dr. Ripley suggested that I

Hello, # Full disclosure. I am not sure if my problem is a bug(s) in the code, or a fundamental misunderstanding on my part about what I am trying to do with these statistics. I am not familiar with maximum likelihood tests. # I currently have two vectors Aequipecten<-c(0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0,

Dear list, Is there any one use MICE package deal with multilevel missing values here? I have a question about the 2lonly.pmm() and 2lonly.norm(), I get the following error quite often. Here is the code the error, could you give me some advice please? Am I using it in the right way? > ini=mice(bhrm,maxit=0) > pred=ini$pred > pred V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12 V13 V14 V15

Hello, I am looking for a routine to do a logistic regression. In the book "Modern Applied Statistics with S-PLUS" a function is described which uses the 'ms' command. Is there an analogue for R, or an alternative approach that can accomplish the same thing? Thanks, John. -- ========================================== John Janmaat Department of Economics Acadia

Hi, temp3<- read.table(text=" ID CTIME WEIGHT HM001 1223 24.0 HM001 1224 25.2 HM001 1225 23.1 HM001 1226 NA HM001 1227 32.1 HM001 1228 32.4 HM001 1229 1323.2 HM001 1230 27.4 HM001 1231 22.4236 #changed here to test the previous solution ",sep="",header=TRUE,stringsAsFactors=FALSE) ?tempnew<- na.omit(temp3) ?grep("\\d{4}",temp3$WEIGHT) #[1] 7 9 #not correct

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 r-users,   I would like to use Kolmogorov smirnov test but in my observed data(xobs) there are ties.  I got the warning message.  My question is can I do something about it?   ks.test(xobs, xsyn)           Two-sample Kolmogorov-Smirnov test data:  xobs and xsyn D = 0.0502, p-value = 0.924 alternative hypothesis: two-sided Warning message: In ks.test(xobs, xsyn) : cannot compute correct

Hi R-users, I would like to find the goodness of fit using Chi-suare test for my data below: xobs=observed data, xtwe=predicted data using tweedie, xgam=predicted data using gamma > xobs <- c(223,46,12,5,7,17) > xtwe <- c(217.33,39,14,18.33,6.67,14.67) > xgam <- c(224.67,37.33,12.33,15.33,5.33,15) > chisq.test(xobs, xtwe = xtwe, rescale.p = TRUE) Error in chisq.test(xobs,

Hi Everybody I use R2.8.0 on Mac OS X. I set up LyX 1.6.1 to use Sweave today. I can compile the test file I found on CRAN ( http://cran.r-project.org/contrib/extra/lyx/) without a problem and the output looks very nice. In the test file the following R code is used. <<myFirstChunkInLyX>>= xObs <- 100; xMean <- 10; xVar <- 9 x <- rnorm(n=xObs, mean=xMean, sd=sqrt(xVar))

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

Can anyone tell me how to calculate a mid-p value for a chi-squared test in R? Many thanks, Andrew Wilson

Hello everyone!I have a data set with missing observations that I am trying to impute. I am using MICE and I would like the imputed values to all be positive. I have two types of variables: prices (P1 to P136) and quantities (Q1 to Q136) and I also want the range of these two types to be different. Besides these variables. I am using the squeeze function but I am unable to set it such that I

Dear list, Here is a small example code that use optim and optimize in order to fit two functions. Is it possible to fit two functions (like those two for example) at the same time using optim ... or another function in R ? Thanks Arnaud ###################################################################### ## function 1 x1 <- 1:100 y1 <- 5.468 * x + 3 # + rnorm(100,0, 10) dfxy <-

I dare the conjecture that if you had written the code, you would know how to do this. This suggests that you are asking us to do your homework, which is not the purpose of this list. A simple inclusion of the code in a for or while loop and storing the estimated parameters with the index of the iteration at which the loop is at should be no problem if you have programmed the code you provided.

Hello, I am using logistic discriminant analysis to check whether a known classification Yobs can be predicted by few continuous variables X. What I do is to predict class probabilities with multinom() in nnet(), obtaining a predicted classification Ypred and then compute the percentage P(obs) of objects classified the same in Yobs and Ypred. My problem now is to figure out whether P(obs) is

Hello, I'm a graduate student in Genetics, who has just started working with R. I have been trying to do a k-means clustering of an expression data compilation, which has lots of NA values in it. As suggested in a couple of earlier posts, I tried using na.omit() and the MICE imputation algorithm to take care of the NA, but they dont seem to work that well. na.omit() deletes the entries,

Hi all, I am trying to run the mice package (for multiple imputation) on a data frame that is 5174 x 100. When I run mice(frame), I get the following response: Error in solve.default(t(xobs) %*% xobs) : Lapack routine dgesv: system is exactly singular and execution stops. I'm no expert at matrix algebra, so if someone could explain this to me and what I can do to get around it,