similar to: A data selection problem, suggestions highly appreciated

Hi all, Is there a simple function already implemented for getting the ISO weeks of a Date object? I couldn't find one, and so wrote my own function to do it, but would appreciate a pointer to the "default" way. If a function is not yet implemented, could the code below be of interest to submit to CRAN? Best Regards, Gustaf --------------------

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 =

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

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)

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 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.

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

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 -

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 =

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

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

R 2.2 on windows XP I have a dataset with multiple columns. Some of the columns represent independent variables, some represent dependent variables. I would like to run the same analyses on a fixed set of independent variables, changing only the dependent variable, e.g. y1-y2=x1+x2+x3 y3-y4=x1+x2+x3 y5-y6=x1+x2+x3, etc. I know I can write a function to perform the analyses, however in order to

Dear help-list members, I am a student at Durham University (UK) conducting a PhD on spatial representation in baboons. Currently, I'm analysing the effect of sampling interval on home range calculations. I have followed the baboons for 234 days in the field, each day is represented by about 1000 waypoints (x,y coordinates) recorded at irregular time intervals. Consecutive waypoints in

Hi all, I have a data frame with "clustered" rows as follows: Cu1 x1 y1 z1 ... Cu1 x2 y2 z2 ... Cu1 x3 y3 z3 ... # end of first cluster Cu1 Cu2 x4 y4 z4 ... Cu2 x5 y5 z5 Cu2 ... # end of second cluster Cu2 Cu3 ... ... "cluster"-size is 3 in the example above (rows making up a cluster are always consecutive). Is there any faster way to sample n clusters (with

Hi After melt you can change levels of your factor variable. Again with the toy example. > levels(temp$variable) [1] "y1" "y2" "y3" "y4" > levels(temp$variable) <- levels(temp$variable)[c(2,4,1,3)] > levels(temp$variable) [1] "y2" "y4" "y1" "y3" > And you will get graphs with this new levels ordering.

Petr, there was a thinko in your response. tmp <- data.frame(m=factor(letters[1:4]), n=1:4) tmp tmp$m <- factor(tmp$m, levels=c("c","b","a","d")) ## right tmp[order(tmp$m),] tmp <- data.frame(m=factor(letters[1:4]), n=1:4) levels(tmp$m) <- c("c","b","a","d") ## wrong tmp[order(tmp$m),] changing levels

Hi all, I'm extracting the name of the term in a regression model that dropterm specifies as the least significant one, and I'm assigning this name to an object. However, when I use update(), it ignores this object. Is there a way I can make it not ignore it? A reproducible example is below: > lm(x1~1+y1*y2+y3+y4,data=anscombe)->my.lm >

Hi Dear all; I would like to create a plot for regression coefficients with each independent variable (x) along the side and the phenotypes (y) across the top (as given below). For each data point, direction and magnitude of effect could be color and significance could be the size of the circle? Is this possible? I would greatly be appreciated your help. Thanks, Greg y1 y2 y3 y4 y5 y6 x1

Hi Petr and Richard; Thanks for your responses and supports. I just faced a different problem. I have the following R codes and work well. p <- ggplot(a, aes(x=Phenotypes, y=Metabolites, size=abs(Beta), colour=factor(sign(Beta)))) + theme(axis.text=element_text(size = 5)) p1<-p+geom_point() p2<-p1+theme(panel.grid.major = element_blank(), panel.grid.minor = element_blank(),

I am trying to do a surface profile plot. data is X                  Y(1)             Z(1) 1-jan-02       2002        number 2-jan-02       2002        number . . . 1-jan-03       2003 (Y2)     number Z(2) 2-jan-03       2003 (Y2)     number Z(2) . . . until dec 31 2007.   I used the plot3d funtions to build a scatter point plot. Call rinterface.rrun("library(rgl)") Call