search for: 7.000000

UseRs, I am working on a dataset (see small example below) where individuals were followed on a specific date-time combo and multiple repeated measurements were taken (e.g., height in meters, behavior class in 2 letter code). Observation numbers varied between individual (ranging from 1 observation for each date-time combo to >50) I am trying to summarize the data into 1 row per

Dear all, When calling rlm with the following data, I get an error. (R v.1.8.1, WinXP Pro 2002 with service pack 1.) > d <- na.omit(data.frame(CPRATIO, HEIGHTZ, FAMILYID)) > c <- tapply(d$CPRATIO, d$FAMILYID, mean) > h <- tapply(d$HEIGHTZ, d$FAMILYID, mean) > c 1 2 3 6 7 9 10 11 6.000000 2.500000 3.250000

Dear List, My colleague has been having a problem with the following data and plotting commands. The example below is part of a larger set of plots, but I've isolated the problem to this example using this small dataset (below), which kills rgui consistently. My version info > version _ platform i386-pc-mingw32 arch i386 os mingw32 system i386, mingw32 status

Estimados usuarios de R: Estoy usando un programa en que utilizo la función rake: *rake(ps,list(~A,~B,~C),list(pop.A, pop.B, pop.C),control = list(maxit=1000, epsilon = 1, verbose=TRUE))* ** *Obtengo como resultado:* ** , , C = 1 B A 1 2 3 4 5 A1 0.000000 0.000000 0.000000 0.000000 0.000000 A2 3.000000 3.000000 0.000000

There's something peculiar that I do not understand here. However, did you realize that the thing you are assigning into parts of `a' is NULL? Check you're my.test.boot.ci.1: It's NULL. Be that as it may, I get: > a <- data.frame(matrix(1:4, nrow=2), X3=NA, X4=NA) > a X1 X2 X3 X4 1 1 3 NA NA 2 2 4 NA NA > a[a$X1 == 1,]$X3 <- NULL > a X1 X2 X3 X4 1 1

This 'strange behaviour' manifest itself within some quite complex code. When I created a *very* simple example the behaviour dissapeared. Here is the simplest version I have found which still causes the strange behaviour (it could be quite unrelated to the boot library, however). library(boot) ## boot statistic function my.mean.s <- function(data,subset){ mean(data[subset]) }

Given a data frame, or it could be a matrix if I choose to. The data consists of an ID, a year, and data for all 12 months. Missing values are a factor AND missing years. Id<-c(rep(67543,4),rep(12345,3),rep(89765,5)) Years<-c(seq(1989,1992,by =1),1991,1993,1994,seq(1991,1995,by=1)) Values2<-c(12,NA,34,21,NA,65,23,NA,13,NA,13,14) Values<-c(12,14,34,21,54,65,23,12,13,13,13,14)

Fellow R Users: I'm not extremely familiar with lda or R programming, but a recent editorial review of a manuscript submission has prompted a crash cousre. I am on this forum hoping I could solicit some much needed advice for deriving a classification equation. I have used three basic measurements in lda to predict two groups: male and female. I have a working model, low Wilk's lambda,

Hi everyone, I have a data.table called "data" with many columns which I want to group by column1 using data.table, given how fast it is. The problem with looping a data.table is that data.table does not like quotations to define the column names (e.g. "col2" instead of col2). I found a way around which is to use get("col2"), which works fine but the

Hi, On 20-11-15 17:07, Samuel Pitoiset wrote: > > > On 11/20/2015 11:36 AM, Hans de Goede wrote: >> Hi Samual, et al, > > Hi Hans, > >> >> In >> http://cgit.freedesktop.org/mesa/mesa/commit/src/gallium/drivers/nouveau?id=ff72440b40211326eda118232fabd53965410afd >> >> you write: "This compute support has been tested by >> Pierre

maybe it's in the data? So here it comes. > sv.growth Grouped Data: length ~ meas | box_id meas spec comp water box_id sprouts leaves length long.sprout 1 1 Sv control moist 1 8.800000 37.80 211.2000 60.6 2 1 Sv xfull moist 2 7.000000 8.00 174.8000 62.8 3 1 Sv control moist 3 9.000000

Hi, On 26-11-15 09:42, Samuel Pitoiset wrote: > Well, if you remove that assert locally, all compute tests in src/gallium/tests/trivial/compute.c pass on GK106, except the atomic ones. Do you mean the: Assertion `pres->target != PIPE_BUFFER' failed. or the: Assertion `tex->defExists(0) && tex->srcExists(0)' failed. assert? Or is the first one not present for

Well, if you remove that assert locally, all compute tests in src/gallium/tests/trivial/compute.c pass on GK106, except the atomic ones. I'm working on the fermi case btw. On 11/25/2015 03:43 PM, Hans de Goede wrote: > Hi, > > On 20-11-15 17:07, Samuel Pitoiset wrote: >> >> >> On 11/20/2015 11:36 AM, Hans de Goede wrote: >>> Hi Samual, et al, >>

On 11/26/2015 01:21 PM, Hans de Goede wrote: > Hi, > > On 26-11-15 09:42, Samuel Pitoiset wrote: >> Well, if you remove that assert locally, all compute tests in >> src/gallium/tests/trivial/compute.c pass on GK106, except the atomic >> ones. > > Do you mean the: > > Assertion `pres->target != PIPE_BUFFER' failed. > > or the: > >

On 11/25/2015 03:43 PM, Hans de Goede wrote: > Hi, > > On 20-11-15 17:07, Samuel Pitoiset wrote: >> >> >> On 11/20/2015 11:36 AM, Hans de Goede wrote: >>> Hi Samual, et al, >> >> Hi Hans, >> >>> >>> In >>>

On Thu, 18 Dec 2003 18:02:07 +0000, Gavin Simpson <gavin.simpson@ucl.ac.uk> wrote : >Dear List, > >My colleague has been having a problem with the following data and >plotting commands. The example below is part of a larger set of plots, >but I've isolated the problem to this example using this small dataset >(below), which kills rgui consistently. My version info

Dear Rusers, The default behavior in R when performing a regression model with missing values is to exclude any case that contains a missing value? How could i set the bahavior that R deal with missing values? e.g.: exclude cases listwise exclude cases pairwise replace with mean Thanks very much! -- Kind Regards, Zhi Jie,Zhang ,PHD Department of Epidemiology School of Public Health Fudan

I am using BM25 with k1=0 and min_normlen=1 to get weights unaffected by document length and term frequency in the document (min_normlen=1 isn't necessary I guess) and am expecting single-term weights to be identical for all matches. I have added a document value to steer such general search queries and it works fine, except that for some search terms, I get results like:

Dear R users, I came up to a problem by taking means (or other summary statistics) of a big dataframe. Suppose we do have a dataframe: ID V1 V2 V3 V4 ........................ V71 1 6 5 3 2 ........................ 3 2 3 2 2 1 ........................ 1 3 6 5 3 2 ........................ 3 4 12 15 3 2 ........................ 100

HI Greg, Sorry, I misunderstand your question. I am not sure whether it works with numSummary() from library(Rcmdr). You could use other ways, such as: test<-read.table(text=" ?id year incidents ?100??? 1??????? 0 ?101??? 1??????? 1 ?102??? 1??????? 21 ?100??? 1??????? 27 ?101??? 1??????? 3 ?102??? 1??????? 12 ?100??? 2??????? 5 ?101??? 2??????? 5 ?102??? 2??????? 19 ?100??? 2??????? 10