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...\\\/// / \ | \\ // | ( | (.) (.) |) ------o00o--(_)--o00o------------------------------------------- ~ Millions saw the apple fall, but Newton asked why ~ ------ooo0------------------------------------------------------- ( ) 0ooo \ ( ( ) \_) ) / (_/ -------------- next part -------------- An HTML attachment was scrubbed... URL: http://lists.freedesktop.org/archives/compiz/attachments/20061025/cdcb3fa0/attachment.html

When I use barchart (with default formatting options), I get bars whose lengths/heights are not proportional to their value. For example: http://drop.io/wbagm6s/asset/capture-png Many of the values in this chart are 1; however, because the blue bars extend to the left of the "0" tick mark, those bars appear to represent higher numeric values. Is there a way to make the length of the

Hello, I look for a simple command computing multivariate group means and returning an object of class "matrix" rather than "list". Does any such function exist in standard packages? I'm beginning with R, so I'm sorry if the solution is trivial. Ondra Mikula

Hi, I was wondering: I've got a dataset where I've got student 'project's nested within 'school's, and 'division' (elementary, junior, or senior) at the student project level. (Division is at the student level and not nested within schools because some students are registered as juniors & others as seniors within the same school.) So schools are random,

Dear useRs, How could I obtain the confidence intervals for the means of my treatments, when my data was fitted to a GLM? I need the CI's for the Poisson and Negative Binomial distributions. Here's what I have: mydata1 <- data.frame('treatments'=gl(4,20), 'value'=rpois(80, 1)) model1 <- glm(value ~ treatments, data=mydata1, family=poisson) means1 <-

Hi, How can I find and download a function in R to do the LU decompostion for finding the upper and lower triangular matrix.  Thank you so much. Joe ___________________________________________________ 您的生活即時通 － 溝通、娛樂、生活、工作一次搞定！ [[alternative HTML version deleted]]

I am using levelplot() function from pkg:lattice and I want to add some points to the plot generated by levelplot() similarly as in basic R graphic sequence: plot(...); points(...), but it does not work. I was reading documentation for lattice, but so far without much success. I would very much appreciate some tips. Best regards, Ryszard

Hi, I wanted to use the predict.lm() function to compare the empirical data with the predicted values. The problem is that I have NAs in my data. I wanted to cbind my data.frame with the empirical values with the vector I get from predict.lm. But they don't have the same length because predict.lm just skip NA-predictions. Is there a way to get a vector with predicted values of the same

Hi, I'm trying to fit nonlinear mixed effects model using nlme function but getting an error message. Here is what I have: fitted_model = nlme(scores~spline(b1,b2,b3,kt,time), fixed = list(b1~1, b2~1, b3~1, kt~1), random = b1+b2+b3~1, groups= ~id, data = sdat, start = c(b1=3.5,b2=2,b3=.60,kt=3.5),verbose=T) Error: Error in

Hi, I am currently running the following negative binomial GLM: glm89.nb <- glm.nb(AvGUD ~ Year*Trt*Micro + (0 + Micro/Trt/Year)) where Year has 3 levels, Trt has 2 levels, and Micro has 3 levels. >From what I have read the above model has a 3 way interaction (Year*Trt*Micro), and Micro is nest within Trt and Trt is nested with Year (0 + Micro/Trt/Year). I was hoping someone could

Dear all, I am interested to calculate confidence interval for fitted values in general for non-linear regressions. Lets say we have y=f(x1,x2,..xN) where f() is a non-linear regression. I would like to calculate a confidence interval for new prediction f(a1,..,aN). I am aware of techniques for calculating confidence intervals for coeffiecients in specific non-linear regressions and with them

pairwise.t.test is returning NAs when one of the samples only has one entry, while TukeyHSD returns results (maybe not trustworthy or believable, but results). I stumbled on this because I did not realize one of my samples only had one entry while most of the others had several hundred, so I realize this is not a desirable situation. I'm really just curious about the difference between how

Do you know what steps I need to take to add a scale to a plot? I'm pulling my example out of "An Introduction to R: Software for StatisticalModelling & Computing" (see the R code around Figure 76). I would like to add a scale to the image produced by the following code.? I would like to the scale to list the distance?and units:? data(volcano) x <- 10*(1:nrow(volcano)) y

first, apologies for so many posts yesterday and today. I am wrestling with nls() and nls2(). I have tried to whittle it down to a simple example that still has my problem, yet can be cut-and-pasted into R. here it is: library(nls2) options(digits=12); y= c(0.4334,0.3200,0.5848,0.6214,0.3890,0.5233,0.4753,0.2104,0.3240,0.2827,0.3847,0.5571,0.5432,0.1326,0.3481) x=

Hi All, I need a small help with following code: I'm trying to convert "dashed lines" to regular ones; and changing default "blue" border color to say "black"... but I'm doing it wrong and its not working. Can anyone help please. Thanks, Code: require(lattice) ex <- data.frame(x=1:10, y=rep(c("A","B"), 5)) bwplot(y~x, data=ex,

Dears useRs, I have 2 factors, (for the sake of explanation - A and B), with 4 levels each. I've already fitted a negative binomial generalized linear model to my data, and now I need to split the factors in two distinct analysis of deviance table:  - A within B1, A within B2, A within B3 and A within B4  - B within A1, B within A2, B within A3 and B within A4 Here is a code that illustrates

Dear all, I'm attempting to use a piecewise regression to model the trajectory of reproductive traits with age in a longitudinal data set using a mixed model framework. The aim is to find three slopes and two points- the slope from low performance in early age to a point of high performance in middle age, the slope (may be 0) of the plateau from the start of high performance to the

Dear all i want to estimated the parameter of the gamma density(a,b,d) f(x) = (1/gamma(b)*(a^b)) * ((x-d)^(b-1)) * exp{-(x-d)/a)} for x>d f(x) = Age specific fertility rate x = age when i run this in R by usling nls() gamma.asfr <- formula(asfr ~ (((age-d)^(b-1))/((gamma(b))*(a^b)))* exp(-((age-d)/a))) gamma.asfr1 <- nls(gamma.asfr, data= asfr.aus, start = list(b = 28, a = 1, d= 0.5),

Hi all, I am working on a filled contour plot which shows a triangular matrix data set (as shown below). Is there a possibilty to draw a triangular filled contour in a equilateral triangle (like a ternary plot)? Thanks in advance Johannes http://n4.nabble.com/file/n1557386/Bild3.png -- View this message in context: http://n4.nabble.com/Triangular-filled-contour-plot-tp1557386p1557386.html

Hi, I have a very simple question, but I'm obviously not able to solve the problem on my own. I have a data.frame like sample(c("A","B","C"),size=20,replace = T)->type rnorm(20)->value data.frame(ty=type,val=value)->test There must be some built in functions, that will do some descriptive statistics with tabular output, in the end I like to have