similar to: make check reg-tests-3

Dear ReXperts, I have the below text file output. I need to extract the T, QC, QO, QO-QC and WT columns for the data between T = 10 and T=150. Any ideas? Thanks in advance. ======================================================================================== 1 D C ---CAT-- T THETA QC QO QO-QC QC/QO WT FSD 8 1 0 1.0000E+01

Dear Listers, can anyone help me, please. Since several days i try to figure out, how to assign values, vectors, functions etc to variables with dynamically generated names inside of functions. Sometimes I succeed, but the success is rather arbitrary, it seems. up to now i don't fully understand, why things like get, assign, <<- etc do sometimes work, and sometimes not. here's one

Dear R helpers: Sorry to bother for a basic question about model.matrix. Basically, I want to apply the dummy coding rule in a dataframe with complete factor levels to another dataframe with incomplete factor levels. I used model.matrix, but could not get what I want. The following is an example. #Suppose I have two dataframe A and B

Hi, I like the formatting and the appearance of lattice plots. But I have not succeeded in gettting the right format in my plots with the lattice package in one of my applications. In?the code shown below, I start by constructing a general data frame and show my attempts with the lattice package commands. After that, I use the graphics package and show the kind of plot that I want to get. I would

Hi, I'm running into a problem subsetting a data frame that I have never encountered before: > dim(chkPd) [1] 3213 6 > df = head(chkPd) > df PN WB Sire Dam MG SEX 601 1001 715349 61710 61702 67 F 969 1001_1 511092 616253 615037 168 F 986 1002_1 511082 616253 623905 168 F 667 1003 715617 61817 61441 67 F

Hola Ruben, Sí precisamente es lo que comentas, en matemáticas no se suele llamar bucketización (este término se emplea más en informática) sino datos agrupados. Pero la idea es la que tu mismo dices. Respecto a las gráficas que has puesto, me han aclarado mucho sobre el tema, gracias. Si realizo lo mismo, por ejemplo con nbucket=1000 sigo obteniendo un p-valor de 1. Es decir, que casi le

I am a novice R user, and I am having difficulty understanding R's influence plots. I am trying to remove outliers from a particular variable, "sib." I am able to generate influence plots and further outlier information such as below (which is a shortened example). For my analyses, I end up excluding the points R refers to, 7, 18, 26, and 105. However, my question is, how can I

I?m working on an R-implementation of the simulation-based finite-sample null-distribution of (R)LR-Test in Mixed Models (i.e. testing for Var(RandomEffect)=0) derived by C. M. Crainiceanu and D. Ruppert. I'm in the beginning stages of this project and while comparing quick and dirty grid-search-methods and more exact optim()/optimize()-based methods to find the maximum of a part of the

Please help to solve that problem: filter and merge 2 big Df's by=t_chr in sec. require(zoo) t1="2012-03-25 17:00:00.0" t2="2012-03-25 17:00:05.0" t1_POSIXlt<-strptime(t1, "%Y-%m-%d %H:%M:%OS")# t2_POSIXlt<-strptime(t2, "%Y-%m-%d %H:%M:%OS")# # ts_t1t2_POSIXlt<-seq(t1_POSIXlt,t2_POSIXlt,length.out

Because all drivers currently use gem objects for framebuffer planes, the virtual create_handle() is not required. This change adds a struct drm_gem_object *gems[4] field to drm_framebuffer and removes create_handle() function pointer from drm_framebuffer_funcs. The corresponding *_create_handle() function is removed from each driver. In many cases this change eliminates a struct *_framebuffer

Because all drivers currently use gem objects for framebuffer planes, the virtual create_handle() is not required. This change adds a struct drm_gem_object *gems[4] field to drm_framebuffer and removes create_handle() function pointer from drm_framebuffer_funcs. The corresponding *_create_handle() function is removed from each driver. In many cases this change eliminates a struct *_framebuffer

Because all drivers currently use gem objects for framebuffer planes, the virtual create_handle() is not required. This change adds a struct drm_gem_object *gems[4] field to drm_framebuffer and removes create_handle() function pointer from drm_framebuffer_funcs. The corresponding *_create_handle() function is removed from each driver. In many cases this change eliminates a struct *_framebuffer

I have used merge regularly and thought I understood how it worked, but I must not. I have two dataframes with identical colnames from two different experiments, TL01 and LC01. Each dataframe has a column named "Entrez.Gene", which I have converted to "as.character" just to make sure merge is not looking at factor levels. Because I have done some filtering, the Entrez.Gene

System info: Linux slackware R Version 1.5.1 (2002-06-17) ESS 5.1.21 Emacs 21.2.1 ------------------- Colleagues I have some text files in a certain directory and want to process them sequentially. So I want to pass the filename identifier into a function and loop through the processing of each file in turn.I've called the file identifier f in this code segment: image.dvm <- function

Hey, As some people might know, I've been contacted to make Swfdec run, and preferrably run fast, as a default UI on an STLinux[1] board. (For everyone not aware of it, this is an embedded ARM architecture (266MHz I think?) that uses DirectFB[2] for graphic output.) This mail is intended as a status report, it contains what I've learned and done about this in the last week. I've

Good morning, I am merging two datasets and I would like to save the non-matching rows in a separate file. The problem is how to retrieve the non-matching rows in R. Example: DATASET A code nomi A1 Franco A2 Mario A3 Andrea A4 Sandro A5 Luca DATASET B code book A1 Guerra e Pace A1 Storia di Roma A2 La coscienza di Zeno A4

I am using rw0641 with Windows 98. To list just the influential repetitiones that result from "influence.measures", I am using the input result <- lm(y~x) and the code from the example in the help for "influence.measures" INFLM <- function(result){ inflm <- influence.measures(result) which(apply(inflm$is.inf,1,any)) } It works fine up to now with the

Greetings, I implemented BRugs to run the EWOC model with a cohort size N=1. I output the simulation data using bugsdata(data), where data is the following list. > data $Dose [1] 140 $Y [1] 0 bugsdata(data) puts out the file data.txt as follows. list(Dose=1.40000E+02, Y=0.00000E+00) after I type the following line modelData("data.txt")

Hi R user, I am new to R, and I have a very simple question for you. I have two matrix A and B, with internally redundant rownames (but variables are different). Some, but not all the rownames are shared among the two matrix. I want to create a greater matrix that combines the previuos two, and has all the possible combinations of matching rownames lines among matrix A and B. looking for the

I have a data-set that is structured as follows: sp wg n v.realtime v.cputime v.tcputime v.idletime v.nswtch 9 0 1 1 28.61300 28.61 28.6039 0.00000e+00 407 1563 0 1 2 15.20270 30.38 28.5981 9.80523e-01 483 3128 0 1 4 12.50930 50.00 28.6053 1.07877e+01 489 4682 0 1 6 12.10260 72.55