search for: mydatas

Dear R-ers, my task is to simple: to assign cases to desired groupings based on the combined values on 2 variables. I can think of 3 methods of doing it. Method 1 seems to me pretty r-like, but it requires a lot of lines of code - onerous. Method 2 is a loop, so not very good - as it loops through all rows of mydata. Method 3 is a loop but loops through fewer lines, so it seems to me more

Is there a function that will allow me to run all model iterations if I specify a full model? I am using information criteria to choose between possible candidate models. I have been writing out all possible model combinations by hand, and I am always worried that I am missing models or have made a mistake somewhere. It is also difficult to alter models if I want to change a term. For example,

Greetings, I'm learning R and I'm stuck on a basic concept: how to specify a logical condition once and then perform multiple transformations under that condition. The program below is simplified to demonstrate the goal. Its results are exactly what I want, but I would like to check the logical state of gender only once and create both (or any number of) scores at once.

Hi, I am using R 1.9.1 on on i686 PC with SuSE Linux 9.0. I have a data.frame, e.g.: > myData <- data.frame( var1 = c( 1:4 ), var2 = c (5:8 ) ) If I add a new column by > myData$var3 <- myData[ , "var1" ] + myData[ , "var2" ] everything is fine, but if I omit the commas: > myData$var4 <- myData[ "var1" ] + myData[ "var2" ] the name

Greetings, Can anyone suggest me if we can vectorize the following problem effectively? I have two datasets, one dataset is portfolio of stocks returns on a historical basis and another dataset consist of a bunch of factors (again on a historical basis). I intend to compute a rolling n-day sensitivitiesfor each stock for each factor, so the output will be a data frame with

#I wish to find the "next non-NA" value within each row of a data-frame. #e.g. I have a data frame mydata. Rows 1, 2 & 3 have soem NA values. mydata <- data.frame(matrix(seq(20*6), 20, 6)) mydata[1,3:5] <-  NA mydata[2,2:3] <-  NA mydata[2,5] <-  NA mydata[3,6] <-  NA mydata[1:3,] #this loop accomplishes the task; I am tryign toi learn a "better" way for(i

I am trying to plot where data points from a give subject are connected by a line. Each subject is represented by a single row of data. Each subject can have up to five observations. The first five columns of mydata give the time of observation, columns 6-10 give the values at each time point. Some subjects have all data, some are missing values. The code I wrote to draw the plot is listed below.

Dear list, I have a problem with defining a function (see below) to read my testfile (see testfile). My function only returns mydata I wish to work with attr(mydata, 'fc') as well (for labelling a plot). Principally it works if I do not insist on this function but it would be much easer if it is possible to return mydata AND attr(mydata, 'fc') by using a function. 1) testfile:

Hi, A error message arose while I was trying to fit a ordinal model with lrm() I am using R 2.8 with Design package. Here is a small set of mydata: RC RS Sex CovA CovB CovC CovD CovE 2 1 0 1 1 0 -0.005575280 2 2 1 0 1 0 1 -0.001959580 2 3 0 0 0 1 0 -0.004725880 2 0 0 0 1 0 0 -0.005504850 2 2 1 1 0 0 0 -0.003880170 1 2 1 0 0 1 0 -0.006074230 2 2 1 0 0 1 1 -0.003963920 2 2 1 0 0 1 0

Is it possible for S4 to (continue) dispatch to a class created during dispatching? The code below doesn't work; is this not possible or have I ommitted something? Concept was to create a SEXP with R_AllocatePtr, give it a class attribute, and continue dispatch. Example code below omits multiple parameters that can be different types. Essentially, any parameter would be converted to an

Please see example code below. I have a vector ("mydata") of length 10. "mydata" can have various formats (e.g. numeric, text, POSIXct, etc) I use the matrix and data.frame functions to convert "mydata" to a dataframe ("mydf") of 2 columns and 5 rows. What is a "good" way to ensure that the format is retained when I create the

Dear Developers, I've been struggling through writing R extension in C. I've been using an external pointer to store my data (please see sample below). I encountered a very weird erroneous behaviour: when I tried to use my external pointer to a structure holding several types of data, including SEXPs, I discovered that SEXPs change their types between returning from initialization

Philipp Benner reported a Debian bug report against r-cran-rpart aka rpart. In short, the issue has to do with how rpart evaluates a formula and supporting arguments, in particular 'weights'. A simple contrived example is ----------------------------------------------------------------------------- library(rpart) ## using data from help(rpart), set up simple example myformula <-

I have stumbled across something in the Lattice package that is vexing me. Consider the code below: __________________________________________________________ library(lattice) myData <- expand.grid(sub = factor(1:16), time = 1:10) myData$observed <- rnorm(nrow(myData)) myData$fitted <- with(myData, ave(observed, sub, FUN = mean)) myData$event.time <- with(myData, ave(observed, sub,

Hello, I am having trouble getting the output from the tapply function formatted so that it can be made into a nice table. Below is my question written in R code. Does anyone have any suggestions? Thank you. Geoff #Input the data; name <- c('Tom', 'Tom', 'Jane', 'Jane', 'Enzo', 'Enzo', 'Mary', 'Mary'); year <- c(2008, 2009,

Hello R users, Problem.......I do not understand how to use "aggregate","by", or the appropriate "apply" to perform a function on data with more than one factor on unbalanced data... I have a data frame in the long format that does not contain balanced data. The ID is a unique identifier corresponding to the experimental unit that will later be examined by ANOVA,

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Dear all Why isn'it possible to calculate Mahalanobis distances with R for a matrix with 1 row (observations) more than the number of columns (variables)? > mydata <- matrix(runif(12,-5,5), 4, 3) > mahalanobis(x=mydata, center=apply(mydata,2,mean), cov=var(mydata)) [1] 2.25 2.25 2.25 2.25 > mydata <- matrix(runif(420,-5,5), 21, 20) > mahalanobis(x=mydata,

Dear R users, today I've got the following problem. Here you are a dataframe as example. There are some SAMPLES for which a CONCentration was recorded through TIME. The time during which the concentration was recorded is not always the same, 10 points for Sample A, 7 points for Sample B and 11 for sample C Also the initial concentration was not the same for the three samples. I would like

Dear list Getting very frustrated with this simple-looking problem > m1 <- lm(x~y, data=mydata) > outliers <- abs(stdres(m1))>2 > plot(x~y, data=mydata) I would like to plot a simple x,y scatter plot with labels giving custom information displayed for the outliers only, i.e. I would like to define a column mydata$labels for the mydata dataframe so that the command >