similar to: sort time

Hello, I have got the following problem: > times <- c("02.07.2007", "03.07.2007","03.09.2007", "04.07.2007","05.07.2007") > mode(times) [1] "numeric" > tim <- as.character(times) > mode(tim) [1] "character" > sort(times) [1] "02.07.2007" "03.07.2007" "03.09.2007"

Hello, I have 12 sample each sample has got 1000 observation, i.e I have a matrix X with 1000 rows and 12 columns! m <- svm(t(X)) p <- predict (m) Can anyone tell me how to use svmtrain() in R! Many Yhanks, Samuel [[alternative HTML version deleted]]

Hello, if we suppose that times <- c("2006-05-14", "2006-06-12", "2006-06-12", "2006-05-14", "2006-05-14", "2006-06-12") value <- c(2,3,1,4,3,1) then with plot(times, value) we have two boxplots in one graph for 2006-05-14 and 2006-06-12 respectively! Is it possible to have them in a scatterplot? and

Hello, I have got the following problem: > setwd("C:/temp") > library(xlsReadWrite) > MyData <- read.xls(file="Mappe1.xls", colNames = TRUE,dateTimeAs = "isodatetime") > attach(MyData) > MyData name value times 1 A1 2 2006-05-12 2 A2 3 2006-05-16 3 A3 1 2006-05-12 4 A4 4 2006-05-12 5 A5 2

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Hello, I am trying to read the SAS file MyData.sa7bdat in R! This file is saved under D:\data! I therefore wrote > path <-"D:/SasData" > sashome <- "C/Progra, Files/SAS Institute/9_1/SAS" > sascmd <- file.path(sashome, "sas.exe") > MyData <- read.ssd(path, "MyData", sascmd=sascmd) The results what I get:

Hi, I am using the NLSY79 data (longitudinal data from the Bureau of labour stats in the US). The extractor exctracts this data in a "wide" format and I need to reshape it into a long format. What I am doing right now is to do it in chuncks for each and evry variable that is varying and then I merge the data together. This is taking a long time. my question is: How do I specify that

Hello, I am interested in Figure 2 in http://www-stat.stanford.edu/~tibs/ftp/cus.pdf Can anyone tell please how to create this plot? Many thanks Samuel [[alternative HTML version deleted]]

Hi, I have the following data data1 <- data.frame(count = c(0,1,1,2,4,5,13,16,14), weeks = 1:9,                     treat=c(rep("1mg",3),rep("5mg",3),rep("10mg",3))) and I am using library(splines) to fit glm.m <- glm(count~bs(weeks)+as.factor(treat),family=poisson,data=data1) and I am interested in predicting the count variale for the weeks 10, 11 and

Hello, suppose one has the following values x1 <- rnorm(10,5,1) x2 <- rgamma(10,5,1) y <- rnorm(10,4,1) mydat <- data.frame(y,x1,x2) then one can use glm like mod <- glm(y~x1+x2, data=mydat, family=gaussian) But how could I estimate y_hat? Thanks alot! Sam --------------------------------- [[alternative HTML version deleted]]

Say you have a POSIX object that is in UTC. How do you change the values to another timezone? If I do this: times <- strptime(times, "%H:%M:%S") times1 <- as.POSIXct(times, tz="UTC") times2 <- as.POSIXct(times, tz="CDT6CST") times1 id UTC, but times2 is still UTC, not CTD. Why? Is the only was to change time zones to add seconds to POSIX objects?

Dear all, I am trying to evaluate the optimisation behaviour of a function. Originally I have optimised a model with real data and got a set of parameters. Now I am creating simulated data sets based on these estimates. With these simulations I am estimating the parameters again to see how variable the estimation is. To this end I have written a loop which should generate a new simulated data

Hello,   Could you please help me in the following question: I have 16 persons 6 take 0.5 mg, 6 take 0.75 mg and 4 take placebo! Can I use the ANCOVA and t-test in this case? Is it possible in R?   Thank you in advance, Samuel [[alternative HTML version deleted]]

Hello, Is there any R function which does power calculation for unbalanced groups (n1 neq n2)? Since power.t.test has n Number of observations (per group). Many thanks, Samuel [[alternative HTML version deleted]]

Hello, Is there is any R function computes the AUC for paired data? Many thanks, Samuel [[alternative HTML version deleted]]

Dear all, I am using glm with quasibinomial. What does the following error message mean: Error in eval(expr, envir, enclos) : y values must be 0 <= y <= 1 Does it mean that the predictor variable should only have zero and one or it is also possible to have continuous values between zero and one? Many thanks, Samuel [[alternative HTML version deleted]]

Hello, I have the fellowing problem and I am thankful for any advice! Regards, Samuel ################################################################ >   source("http://bioconductor.org/biocLite.R") BioC_mirror = http://www.bioconductor.org Change using chooseBioCmirror(). >     biocLite("SSPA") Using R version 2.11.0, biocinstall version 2.6.7. Installing

Dear all, I am trying to shove a number of cmdscale() results into a single plot (k=1 so I'm trying to get multiple columns in the plot). From ?par I learned that I can/should set new=TRUE in either par() or the plot function itself. However with the following reduced code, I get only a plot with a column of data points with x==2. plot(1,10, xlim=range(0,3), ylim=range(0,10),

I want to try to get a result of element wise addition between a vector and a list. It can be done with "for statement." In order to reducing computing time, I have tried to avoid "for state." If anybody give me an idea, I would apprecite it much. for example, with a & b as below lines, a<- list(c(1,3),c(1,2),c(2,3)) b<-c(10,20,30) I would like to have a list (like

Hi, I would like to know whether anybody knows a simple way to combine textual and graphical output in R. A typical analysis produces textual output (e.g. model fits) and plots in R. I would like to know whether R has the possibility of combining these into a single 'report' or output. An example of a program that does this is SPSS. After running the analysis you have a combination