similar to: image() with color key?

When using read.spss (library: 'foreign') I get the following warning message: Warning message: E:/R4win/mesamri.sav: Unrecognized record type 7, subtype 13 encountered in system file. I don't see anything wrong with record #7 in the database I am trying to read in, but I suspect that the warning message does not refer to a specific record, but a "variable" type. Is this

Let me modify my question about user-defined covariance structures for LME models: Can somebody tell me how I can see the code for the definition of the correlation structures that come with the NLME package. Specifically I like to see the code for the functions coef, corMatrix, and intialize for any of the pre-defined correlation structures, and use this as a template to define a new correlation

I have data for several rings of a left heart chamber, and which I would like to display in concentric rings, with color-encoding of the values. Each ring corresponds to one slice through the heart, and the rings correspond to positions from the base to the apex of the heart as you move from the outermost ring to the innermost one. The data have a circular pattern. These types of displays are

I am using the latest version of R on a Windows machine and get the following error when I try to initialize a correlation structure with the function corAR1 in NLME. This example is taken from the book of Pinheiro and Bates, so it should work. What is going wrong? > library(nlme) > data(Orthodont) > cs1AR1 <- corAR1(0.8, form= ~1 | Subject) > cs1AR1 <- initialize(cs1AR1, data =

Dear R-Users, Is it possible to get the covariance matrix from an lme model that did not converge ? I am doing a simulation which entails fitting linear mixed models, using a "for loop". Within each loop, i generate a new data set and analyze it using a mixed model. The loop stops When the "lme function" does not converge for a simulated dataset. I want to

Could somebody help with the definition of new correlation structure for use with a linear mixed-effects model (package nlme). Specifically, I want to define a Toeplitz type correlation structure, but due to my inexperience with programming in R, I feel a bit overwhelmed with the task at hand. I understand that you can start with a function like corAR1 as template, but I have no idea how I would

I am using lmList, which takes 'Data' partitioned according to the levels of a grouping factor (gf) and individual 'lm' fits are obtained for each 'data'partition, using a model defined as in "lm". So my call to lmList looks something like: > mg.lis <- lmList(strmbf ~ age1c + gender1 + sysbp.clinic + + diabp.clinic + ldl1 + mets.total + bmi1c |

After installation of the latest version of R (2.6.0) I have a problem with loading the nlme library. When I use RGui under Windows XP, and try to install the nlme package, I get a warning that installation was unsuccessful due to a previously installed version of nlme. But the nlme library does not appear on the list of libraries that are available for loading under RGui. This happens after a

I have been looking at a draft of Doug Bate's book on mixed effects models (http://lme4.r-forge.r-project.org/book), and in chapter one (section "1.4.2 Matrices and Vectors in the Fitted Model Object", to be exact) he refers to the function env() for checking the environment of a fitted lmer object. This function does not appear under help, and I have not been able to find

I see that feature freeze for a better than ever R has been announced. May I ask if there will be or could be "merge" function for data frames? I believe it would be very nice if this were "centrally" implemented (with regard to my humble steps to writing such a function and the related error and other precautions). I know from VR2R.pdf (courtesy Profs. Venables and Ripley)

Dear R user, I have a question on using R to analyze data with repeated measurements. I have 2 species with several strains (12) per species, each of which has been measured twice with for a given trait. No particular covariance, just two measures. Now I want to analyze the data with an ANOVA (aov) considering these repeated measures to get the MSq and SSq for the species and strain level. I

Hello Experts, how do I reformat a data frame in the way described below: df1: ID desc resist thick temp 1 4711 100 5 20 2 4712 101 4 21 3 4711 99 3 19 4 4712 98 7 22 TO df2: id desc Param Value 1 4711 resist 100 1 4711 Thick 5 1 4711 temp 20 2 4712 resist 101 2 4712 Thick 4 2 4712 temp 21 3

Hi all, I have a very high dimensional data and apparently there are several columns that contain similar information (some columns are equal). I want to form a matrix/data frame consisting of unique columns. Does anyone have an efficient way of getting out these columns. A small section of the data frame is given below. Thanks for helping. Stephen. > newdata [,1] [,2] [,3] [,4] [,5]

http://bugzilla.mindrot.org/show_bug.cgi?id=917 Summary: ssh_exchange_identification: Connection closed by remote host Product: Portable OpenSSH Version: 3.6.1p2 Platform: ix86 OS/Version: Linux Status: NEW Severity: normal Priority: P3 Component: sshd AssignedTo: openssh-bugs

Hello, could You please help: I am looking for a way to formulate test accuracy measures such as test sensitivity, specificity, predictive values, and correct classification rate using p/d/qnorm. The tests' primary values follow a bimodal distribution, which is modelled by a mixture of two normal distributions: p * dnorm ((x - u1) / s1) / s1 + (1 - p) * dnorm ((x - u2) / s2) / s2)

Dear R communities May I seek your advices on how to change color the default in levelplot(), e.g. from the default of pink and light blue, to e.g. red and green ? The levelplot function has 1 of the arguments being panel (which is actually panel.levelplot), but I am not sure where the commands to alter the color. For example, I type: p1<-levelplot(my.mat,colorkey=FALSE), how could I

Hi guys, I have a matrix with values varying from approximately -0.7 to 0.33 that I want to create a heatmap/levelplot with. When I execute the levelplot function for my matrix, I end up getting colors that are adjusted to the max and min rather than around 0. In other words, ideally I would like to have a color ramp that goes from red (negative number), to white (0), to blue (positive);

I can't find a way to change just the panel background color in lattice. I would like NA regions in levelplot() to appear black. I've tried the trellis.par.set() stuff, but it it makes the background of the whole graphic black. Thanks, Scott Waichler Pacific Northwest National Laboratory scott.waichler _at _ pnl.gov

Hi! Would like to plot two image plots with color scale (like levelplot (lattice) implements) in one graphic device. Tried to plot 2 levelplot's (lattice) (the data has not much in common) in one graphics device by setting par(mfrwo=c(2,1)) which does not work. Is there a way to force levelplot to use only a half of the graphic device? Is there a function like image which provides the color

Hello, I am searching for the best method to plot two variables with points whose output color depends on the size of a third variable. For example, the darkness of the x-y point would increase incrementally based on the size of the z value, similar to the colramp parameter in geneplotter. This would be analagous to symbols(), except changing the selection from the color gradient rather than the