search for: dumness

dum is a simple data frame transferred to Splus using the dump() command in Splus and the source() in R. All fields are numeric. There are no missing data. The data frame looks like it is should: > apply(dum,2,mode) yrcl sland s02 s234 "numeric" "numeric" "numeric" "numeric" > apply(dum,2,is.vector) yrcl sland s02 s234

Hi, All: I'm having trouble getting deparse(substitute(x)) inside print.generic to consistently I'm having trouble getting a print.something to work consistently. Consider the following toy example: # Define an object of class 'dum' k <- 1 class(k) <- 'dum' str(k) # as expected # Define print.dum print.dum <- function(x, ...)

Hi, Peter et al.: On 2017-01-09 4:24 AM, peter dalgaard wrote: > On 09 Jan 2017, at 10:53 , Spencer Graves <spencer.graves at prodsyse.com> wrote: > >> # Define an object of class 'dum' >> k <- 1 >> class(k) <- 'dum' >> str(k) # as expected >> >> # Define print.dum >> print.dum <- function(x, ...) >>

Does anyone know if there is an R function that will take a matrix like this jim 1 0 0 0 0 0 jim 0 1 0 0 0 0 jim 0 0 1 0 0 0 bob 1 0 0 0 0 0 bob 0 0 1 0 0 0 harry 0 0 1 0 0 0 harry 0 0 0 1 0 0 harry 0 0 0 0 1 0 harry 0 0 0 0 0 1 and make it like this? (that is, add together rows that have the same name?) jim 1 1 1 0 0 0 bob

Hi, Can anyone help me with the following. I have been using R for Monte Carlo simulations and got some results I couldn't explain. Therefor I performed following short test: -------------- mean.sds <- NULL sample.sizes <- 3:30 for(N in sample.sizes){ dum <- NULL for(I in 1:5000){ x <- rnorm(N,0,1) dum <- c(dum,sd(x)) } mean.sds<- c(mean.sds,mean(dum)) }

Dear all, I have a dataframe which looks like this (dummy): date<-c("jan", "feb", "mar", "apr", "may", "june", "july", "aug","sep","oct","nov","dec") col1<-c(8.2,5.4,4.3,4.1,3.1,2.5,1.1,4.5,3.2,1.9,7.8,6.5) col2<-c(3.1,2.3,4.7,6.9,7.5,1.1,3.6,8.5,7.5,2.5,4.1,2.3)

Another request for help implementing the 'apply' functions to avoid a loop structure... I am working with a data set that includes lab measurements taken at different dates for the subjects, with some subjects having more results than others. I would like to average lab results for each subject that were taken on the same day. I can do this using a for loop, but would like to know how

On 09 Jan 2017, at 10:53 , Spencer Graves <spencer.graves at prodsyse.com> wrote: > # Define an object of class 'dum' > k <- 1 > class(k) <- 'dum' > str(k) # as expected > > # Define print.dum > print.dum <- function(x, ...) > deparse(substitute(x)) > > print(k) # Prints "k" as expected > #####**** THE FOLLOWING PRINTS

Hi, I have downloaded a R script from http://www.wessa.net/rwasp_edauni.wasp#output. This script produces a densityplot graphic, amongst others, when is executed from the web page. However, when I run it in my machine the *densityplot* function produces any output, I mean a blank graphic. But, it's interesting if I run the following lines in the R interactive console: > y <-

I've tried to move objects from S to R. In S+, I use data.dump() and data.restore(). I've made a file all.dum using data.dump(ls()) in S+, but the R command load("all.dum") gives an error: > load("/jaz/all.dum") Error: restore file corrupted -- no data loaded Is there any way to pass my objects from S+ to R? Thanks Agus Dr. Agustin Lobo Instituto de Ciencias de

Dear all, I am trying to analyze some non-linear data to which I have fit a curve of the following form: dum <- nls(y~(A + (B*x)/(C+x)), start = list(A=370,B=100,C=23000)) I am wondering if there is any way to determine meaningful quality of fit statistics from the nls function? A summary yields highly significant p-values, but it is my impression that these are questionable at best given

I am trying to convert a matlab code to R. Most of the conversion statements are simple, but problem is with return. Since it's a recursive function it's a bit complicated. Anyway in matlab we can have return statment like [price, notional] = functionname() and also for the same function... notional(1) = functionname() how to do this in R? i have tried using data frame but still

I'm on mandriva 2006 I did: urpmi R-2.0.0-1mdk.i586.rpm got the message: Some asked package can't be intalled: R-2.0.0-1mdk.i586 (due to unsatified) Continue ? (Y/N) Then after I try typping R on the shell and it does work. Of course there is no R reposatory Thank Daniel ################## Daniel Sarrazin B.Sc Physics Daniel_Sarrazin at hotmail.com ##################

Hello All Have 2 tables dt1: start end kwh10min 2013-04-01 00:00:54 UTC 2013-04-01 01:00:10 UTC 0.05 2013-04-01 00:40:26 UTC 2013-04-01 00:50:00 UTC 0.1 2013-04-01 02:13:20 UTC 2013-04-01 04:53:42 UTC 0.15 2013-04-02 02:22:00 UTC 2013-04-01 04:33:12 UTC 0.2 2013-04-01 02:26:23 UTC 2013-04-01 04:05:12 UTC 0.25 2013-04-01 02:42:47 UTC 2013-04-01 04:34:33 UTC 0.3 2013-04-01 02:53:12 UTC 2013-04-03

Hi Soumya, One example, we have a common working directory dri_fleat in the gluster volume drwxrwsr-x 22 root dri_fleat 4.0K May 1 15:14 dri_fleat my user (phaley) does not own that directory but is a member of the group dri_fleat and should have write permissions. When I go to the nfs-mounted version and try to use the touch command I get the following ibfdr-compute-0-4(dri_fleat)%

> opt -load lib­dum­my­pass.so -dum­my­pass hel­lo.ll Looks like you are loading a shared library different from "LLVMHello.so". did you change the name of the compilation unit from "Hello.cpp" into "dummypass.cpp"? (As asked previously by Andrzej) did you register the dummy pass? > RegisterPass<DummyPass> X("dummypass",

Hi, I was wondering if there were any additional test we could perform to help debug the group write-permissions issue? Thanks Pat On 06/27/2017 12:29 PM, Pat Haley wrote: > > Hi Soumya, > > One example, we have a common working directory dri_fleat in the > gluster volume > > drwxrwsr-x 22 root dri_fleat 4.0K May 1 15:14 dri_fleat > > my user (phaley) does

Hi, Could you please confirm the following steps for debugging a pass? 1. copy your pass into llvm/lib/Transforms/Hello/Hello.cpp 2. name you pass Hello 3. insert debug messages like:     errs() << "Vis­iting func­tion " << F.get­Name(); 4. get LLVM bitcode:    clang -O3 -emit-llvm hello.c -c -o hello.bc5. disassemble the bitcode:     llvm-dis hel­lo.bc 6. run the pass on

Hello, i want to estimate a complex GARCH-model (see below). http://r.789695.n4.nabble.com/file/n4112396/GJR_Garch.png W stands for the Day of the Week Dummies. r stands for returns of stock market indices. I stands for the GJR-term. I need some help with three problems: 1.) implementation of the GJR-term in the variance equation 2.) compute robust covariance matrix

Case cohort function cch() is in survival package. In cch(), the prentice method is implemented like this: Prentice <- function(tenter, texit, cc, id, X, ntot,robust){ eps <- 0.00000001 cens <- as.numeric(cc>0) # Censorship indicators subcoh <- as.numeric(cc<2) # Subcohort indicators ## Calculate Prentice estimate ent2 <- tenter ent2[cc==2] <-