similar to: R process size growing in time...

I have a factor (with "n" observations and "k" levels), with only "nobs" < n of the observations not missing. I would like to produce a (n x k) model matrix with treatment contrasts for this factor, with rows of NAs placeholding the missing observations. If I use model.matrix() I get back a (nobs x k) matrix. Is there an easy way to get the (n x k) without

Hello, I have a simulated data structure in which students are nested within teachers, and with each student are associated two test scores. There are 20 classrooms and 25 students per classroom, for a total of 500 students and two scores per student. Here are the first 10 lines of my dataframe "d": studid tchid Y time 1 1 1 -1.0833222 0 2 1 1

Greetings, I have a meta-analysis problem in which I have fixed effects regression coefficients (and estimated standard errors) from identical models fit to different data sets. I would like to use these results to create pooled estimated regression coefficients and estimated standard errors for these pooled coefficients. In particular, I would like to estimate the model \beta_{i} = \mu +

Greetings, This seems too rudimentary to ask but for the life of me I cannot locate a readily easy method to compute the univariate mode. I know "mode" is not correct and "table" provides a reasonable count but I figured there would be an easy way to extract the value from the table after I do something like: max(table(mydadat$myvar)) unfortunately it only returns the max

Can a single random number be generated in R? I have an exercise that wants to simulate coin tosses, and I cannot seem to find a good example of the use of random number generation in R. Any help? Joshua Gramlich Chicago, IL

Hi all; This is my first message to the list, and I've got three "basic" questions: How could I insert comments in a file with commands to be used as source in R? Is it possible to quickly display a window with all the colors available in colors()? How? I'm displaying points, but they overlap, wether points() uses triangles, bullets or whatever. Is it possible to change

I want to subset the dataframe based on certain values in a row. for each row in my dataframe if ANY one value of a particular set of columns satisfies cond append a logical value true at the end of the row else append a false at the end of the row in the end I want to be able to subset the whole data based on the appended true or false value. I could literally code like this, but I think

without having to check the vector element by element? Thanks a lot! Jason ===== Jason G. Liao, Ph.D. Division of Biometrics University of Medicine and Dentistry of New Jersey 335 George Street, Suite 2200 New Brunswick, NJ 08903-2688 phone (732) 235-8611, fax (732) 235-9777 http://www.geocities.com/jg_liao

Full_Name: Laurent Gautier Version: 1.3.0-patched OS: IRIX 6.5 Submission from: (NULL) (130.225.67.199) Hello, The function La.eigen, called by cmdscale in the package mva behaves an unexplicable way (for me). The following lines show what happened. I tried the very same on linux, and it worked fine. >a <- matrix(c(1,2,3,2),3,3) >a [,1] [,2] [,3] [1,] 1 2 3 [2,]

If you found my subject heading to be confusing then I'm sure you'll enjoy the example I've included below. I find the apply type functions to be wonderful for avoiding loops but when I use them with existing functions, I end up using loops anyway to extract the vectors I want. I would appreciate it if someone could show me how to avoid these loops. Thanks. EXAMPLE:

In general this is what "apply" does. In your example you could use rowMeans(ar) as well, I think. Reid Huntsinger -----Original Message----- From: Olivier Martin [mailto:olivier.martin at inrialpes.fr] Sent: Tuesday, July 02, 2002 10:55 AM To: r-help Subject: [R] mean and array Hi all, I have an array, one say ar, with 3 dimensions. dim(ar) >200 3 4 I would like to

Hi Helpers: I have a factor object that has 314k entries of 39 land cover types. (This object can be coerced to characters neatly should that be easier to work with.) > length(foo) [1] 314482 > foo[1:10] [1] Montane Chaparral Barren Red Fir Red Fir [5] Red Fir Red Fir Red Fir Red Fir [9] Red Fir Red Fir 39 Levels:

Dear listers, I can't find the variance or se of the coefficients in a multilevel model using lme. I want to calculate a Chi square test statistics for the variability of the coefficients across levels. I have a simple 2-level problem, where I want to check weather a certain covariate varies across level 2 units. Pinheiro Bates suggest just looking at the intervals or doing a rather

Dear all, Sorry to bother you with one more newbie question. I have a dataobject with several hundreds of columns. I want to remove columns with a mean of the column values below a certain value: > a<- c(1,2,3,4,5,6) > b<-c(2,4,6,8,10,12) > c<- c(3,6,9,12,15,18) > test<- as.matrix(cbind(a, b, c)) > mean(a) [1] 3.5 > mean(b) [1] 7 > mean(c) [1] 10.5 Say the

kalish at psy.uwa.edu.au wrote: > > I'm a newbie at R, and can't get libraries to really work. > I did this: > > library(help = mva) > cancor Canonical Correlations > cmdscale Classical (Metric) Multidimensional Scaling > dist Distance Matrix Computation > hclust Hierarchical Clustering

Hello R-users, I need to create a vector inserting an 1 after each value of another vector. For example: vec1<-c(2,3,4) I need to create a vector with the values 2,1,3,1,4 Does anyone know how create this vector without loops (vec1 could have 1000 elements) Thank you, Juan -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Hi there, I want to create plots with some kind of 'complex' axis labelling of the form $\dot{V}$ and integrate those plots into a LaTeX document. What is the best way to go? I've figured out, that the 'plotmath' commands are somewhat limited (at least I wasn't able to get the $\dot{V}$ generated) and that plots with 'plotmath'-axes wouldn't export

Dear R user, I am a biochemist/bioinformatician, at the moment working on protein clusterings by conformation similarity. I only started seriously working with R about a couple of months ago. I have been able so far to read my way through tutorials and set-up my hierarchical clusterings. My problem is that I cannot find a way to obtain information on the rooting of specific nodes, i.e. of

Hello, I have a dilemma that I'm hoping the R gurus will be able to help resolve. For background: My data is in the form of a (dis)similarity matrix created from taking the inverse of normalized reaction times. That is, each cell of the matrix represents how long it took to distinguish two stimuli from one another-- a square matrix of 45X45 where the diagonal values are all zero (since this

Hi all, The function heatmap uses the functions dist and hclust with default parameters. How to change these parameters? For example, i want to use the ward criterion for hierarchical clustering with binary distance. Best regards, Olivier.