similar to: arc length of noisy time series?

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Hi First post and a relative R newbie.... I am using the vioplot library to produce some violin plots. I have an input CSV with columns off irregular length that contain NAs. I want to strip the NAs out and produce a multiple violin plot automatically labelled using the headers. At the moment I do this Code:? ds1 = read.csv("http://www.lecturematerials.co.uk/data/spelling.csv")

Dear R-users; Previously I posted a question about the problem of rank deficiency in summary.manova. As somebody suggested, I'm attaching a small part of the data set. #*************************************************** "test" <- structure(.Data = list(structure(.Data = c(rep(1,3),rep(2,18),rep(3,10)), levels = c("1", "2", "3"), class =

Change the assembly code to use only relative references of symbols for the kernel to be PIE compatible. Position Independent Executable (PIE) support will allow to extended the KASLR randomization range below the -2G memory limit. Signed-off-by: Thomas Garnier <thgarnie at google.com> --- arch/x86/crypto/aes-x86_64-asm_64.S | 45 ++++++++----- arch/x86/crypto/aesni-intel_asm.S

Used for celt_pitch_xcorr on aarch64, and celt_fir and celt_iir on both armv7 and aarch64. --- celt/arm/arm_celt_map.c | 17 +++++++++++++ celt/arm/celt_neon_intr.c | 61 ++++++++++++++++++++++++++++++++++++++++++++++- celt/arm/pitch_arm.h | 31 +++++++++++++++++++++++- 3 files changed, 107 insertions(+), 2 deletions(-) diff --git a/celt/arm/arm_celt_map.c b/celt/arm/arm_celt_map.c index

loess() should be able to do robust 2D smoothing. There's no natural ordering in 2D, so defining running medians can be tricky. I seem to recall Prof. Koenker talked about some robust 2D smoothing method at useR! 2004, but can't remember if it's available in some packages. Andy From: Vladislav Petyuk > > Hi, > Are there any multidimenstional versions of runmed() and >

I am unfamiliar with R and I’m trying to do few statistical things like GLM and GAM with it. I hope my following questions will be clear enough: My datas ( y(i,j ))are run off triangles for example : J=1 J=2 J=3 I=1 1 2 3 I=2 4 5 I=3 6 My model is : E[y(i,j)] =m(i,j) Var[y(i,j)] =constant *m(i,j) Log(m(i,j)) = eta (i,j) eta (i,j) = c + alpha(i)

Dear R-users, A new version of `lavaan' (for latent variable analysis) is now available on CRAN. The current version of lavaan (0.4-8) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org To get a first impression of how the 'lavaan model syntax' looks

Dear R-users, A new version of `lavaan' (for latent variable analysis) is now available on CRAN. The current version of lavaan (0.4-8) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org To get a first impression of how the 'lavaan model syntax' looks

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

Dear R-users, A new package called `lavaan' (for latent variable analysis) has been uploaded to CRAN. The current version of lavaan (0.3-1) can be used for path analysis, confirmatory factor analysis, structural equation modeling, and growth curve modeling. More information can be found on the website: http://lavaan.org Some notable features of lavaan: - the 'lavaan model

Complete newbie to R -- struggling with something which should be pretty basic. Trying to create a simple data set (which I gather R refers to as a data.frame). So > a <- c(1,2,3,4,5); > b <- c(0.3,0.4,0.5,0,6,0.7); Stick the two together into a data frame (call test) using cbind > test <- data.frame(cbind(a,b)) Seems to do the trick: > test a b 1 1 0.3 2 2 0.4 3 3

Hi Yves lavaan looks like a very nice package. From the tutorial introduction I see you create path diagrams for some of the models you describe. How did you do this? I don't see a function for this in the package. I know there is a path.diagram function in the sem package that uses dot to draw the diagram, but I've always found the layouts from dot somewhat strange for path diagrams

I am using R 2.8 and the latest versions of RMySQL on a Windows XP 64 bit machine. I was wondering if someone could help me figure out how to use dbWriteTable without inserting \r into my table. Consider the following code snippet, which is run after I connect to my database. myDFOut = dbReadTable(conn, "myDF") print(myDFOut) myDFIn = data.frame(x=paste("x", 1:5, sep =

Dear all, I am quite new to R; facing certain problems: Say, I have a text file( named as "try"): Year C1 C2 C3 C4 C5 C6 Y1 3.5 13.8 9.5 6.8 0.4 24.2 Y2 3.8 13.9 9.9 7.6 0.7 12.8 Y3 4.5 14.5 14.2 9.2 0.6 14.5 Y4 5.9 16.2 24.6 12.7 0.2 24.3 Y5 7.2 20.4 40.6 18.2 0.8 28.2 Y6 5.9 18.6 37.4 14.5 0.3 36.9 Y7 8.0 16.1 88.6 24.1 0.1 34.6 Y8 13.6 21.1 56.3 19.0 0.7 33.3 I wish to import the

Dear members, I want to create 8 graphs and write it into one page using mfrow=c(4,2). How to make all graphs (including the titles, legends, line types) to be scale down (resized proportionally). As an illustration, below is the code: pdf("testmfrow.pdf") par(mfrow=c(4,2)) x<-seq(1:10) y1<-rnorm(10) y2<-rnorm(10,mean=2,sd=1) y3<-rnorm(10,mean=3,sd=1)

Dear R-users I have 5 dependent variables (y1 to y5) and one independent variable (x) and 3 conditioning variables (m, n, and 0). Each of the conditioning variables has 2 levels. I created 2*4 panel plots. xyplot(y1+y2+y3+y4+y5 ~ x | m*n*o,layout = c(4,2)) I would like to reorder the 8 panels. I tried to use index.cond (e.g., index.cond = list(c(1,3,2,4,5,7,6,8)) but it didn't work out.

Hi, All I get following question: A data format like following: [Day time x y] Jan1 18:56:24 x1 y1 Jan1 18:56:25 x2 y2 Jan1 18:56:27 x3 y3 Jan1 18:56:28 x4 y4 Jan1 18:56:31 x5 y5 ..................... ..................... what I wanna do is to partion the time interval by unit of 5 seconds. and pick x,y corresponding to the last time within that interval. for the example above, suppose

Hello, I have a data frame with the following variables: ID, X1,X2,X3,X4,X5,Y1,Y2,Y3,Y4,Y5 and some other that do not matter, some of the X and Y can be missing (NA). I want to compute the slope of the linear regression Y ~ X for each subject, so using apply(DF,1,FUN,ra.rm=TRUE) now How do I define FUN? The X are different for each subject. Thanks for any help R.Heberto Ghezzo Ph.D. Montreal -

Dear list, I am starting a new project in cmdscale, and I have a question regarding distance matrix and covariance matrix. Can anyone help me in this? I sent this message so many times but always bounced with no further explanation. (1) Can I use covariance as my distance matrix? (2) Any good reference in this matter? (3) is the approach that I wrote below valid? Thank you, ilham Below is what