similar to: xyplot: Plotting two variables, one as points - the other as line. Can that be done without explicitly using panel functions

Hi, I would like to create a plot of y1,y2,y3,y4 against x for several subjects such that y1 and y2 are plotted against x in one panel and y3 and y4 against x in another panel. Thus if there are 3 subjects I should end up with 6 panels. Is there a simple way of doing so (i.e. without calling xyplot() several times, and then padding the results together)?? Regards S?ren

In xyplot, I would like to get the "data into the panel function" in the following sense: Consider xyplot(scc~time|cowidp, data=cow.s,type=c("l"), panel=function(x,y,subscripts,...){ panel.xyplot(x,y,...) vvv<-cow.s[which(!is.na(cow.s[subscripts,"mastreat"])),"time"] panel.abline(v=vvv,col="red",lwd=2) } ) If I want to use a

Thanks. I wonder if there is a general way of extracting var(u) and var(e), which would be needed to simulate u and e. Clearly, one can get the estimated parameters, but is there a clever way of 'setting up' the matrices?? Best S??ren On 6/19/05, S??ren H??jsgaard <Soren.Hojsgaard at agrsci.dk> wrote: > I would like to draw a sample from a linear mixed model y=Xb+Zu+e which has

# The result I am after is the result after a substitution in an expression, such as substitute(expression(a+b+c), list(a=1)) expression(1 + b + c) # However, the way I want to do it is for a an expression "stored as a variable" as (expr <- expression(a+b+c)) expression(a + b + c) # a) The following does not work (expr2 <- substitute(expr, list(a=1))) expr # b) - whereas this

Dear all; I would like to draw a graph with vertices and edges, and I guess tcl/tk would be appropriate. I don't know tcl/tk but have googled for a 10-page (or so) introduction to 'getting started with tcl/tk in R' but without any luck. - Does anyone know of the existence of such a document or any other web-based material on the subject? - Does anyone have an (informative) piece of

>From time to time people request symbolic computations beyond what D() and deriv() etc can provide. A brief look at the internet shows that there are many more or less developed computer algebra packages freely available. Therefore, I wondered if it would be an idea to try to 'integrate' one of these packages in R, which I guess can be done in more or less elegant ways... I do not know

I would like to draw a sample from a linear mixed model y=Xb+Zu+e which has been fitted with lme(), i.e. a model y ~ N(Xb, C), where C=Z cov(u) Z' + cov(e). I've tried to figure out how to extract C from an lme object, because that would solve my problem when also using the predict() function, but without any luck. Can anyone help on that?

Dear list I have a function and a vector, say f <- function(a,b){a+b} x <- c(2,3) I want to "evaluate f on x" in the sense of computing f(x[1],x[2]). I would like it to be so that I can write f(x). (I know I can write a wrapper function g <- function(x){f(x[1],x[2])}, but this is not really what I am looking for). Is there a general way doing this (programmatically)?

I would like to use lattice graphics to plot multiple functions (or groups or subpopulations) on the same plot region, using different line types "lty" or colors "col" to distinguish the functions (or groups). In traditional graphics, this seems straightforward: First plot all the data using 'type="n"', and subsequently execute a series of "points"

Dear List In a package I want to import the mApply function from the Hmisc package, and I would like to import only that function. 1) If I write "Depends: Hmisc" in the DESCRIPTION file I get the whole Hmisc package, so that is not the way to go ahead. 2) According to "Writing R extensions", sec 1.6.1 "Specifying imports and exports" I can (as I read it) simply

Hi, when I apply a glm() model in two ways, first with the response in a two column matrix specification with successes and failures y <- matrix(c( 5, 1, 3, 3, 2, 2, 0, 4), ncol=2, byrow=TRUE) X <- data.frame(x1 = factor(c(1,1,0,0)), x2 = factor(c(0,1,0,1))) glm(y ~ x1 + x2, data = X, family="binomial") second with a model matrix that

I am trying to plot two 3-dimensional time series in one window (such that there will be 3 rows and 2 columns). For zoo and ts objects the par(mfrow...) option does not work. I can get xyplot to make the plots, but data are on widely different scales in the three dimensions, and xyplot uses the same scale on all y-axis which means that in some dimensions the curves will be almost horizontal lines.

I am writing a package which uses the Rgraphviz package which in turn uses the graph package, but my question does not (I believe) pertain specifically to the these packages so therefore I dare to post the question here: I my package I have a function "edges" which works on some graphs I have defined. However, there is also a function "edges" (or rather a generic method) in

I'm having trouble creating a looping variable and i can't see wher ethe problem arises from any hep gratfully appreciated First create a table x<-table(SURVEY$n_0,exposed) > x exposed False True Under 16 24 1 16-19 68 9 20-24 190 37 25-34 555 204 35-44 330 87 45-54 198 65 55-64 67 35 65+

I would like to see how the matrix multiplication operator %*% is implemented (because I want to see which external Fortran/C routines are used). How can I do so? Best S??ren

Dear R-List, I?m new in R, so I hope my question is not to primitive, but I haven?t found a solution in the R-help. I?ve got a datatframe with 3 factors, called xf (9 levels), yf (9 levels), zf (3 levels) and one variable (rt): > xf yf zf rt > 1 1 1 67 > 1 1 1 56 > 1 1 1 60 [...] > 1 1 2 58 > 1 1 2 61 [...] > 9 1

Dear all, I need to calculate tr(A B), tr(A B A B) and similar quantities **fast** where the matrices A, B are symmetrical. I've searched for built-in functions for that purpose, but without luck. Can anyone help? Thanks in advance Søren [[alternative HTML version deleted]]

I believe there is a memory leak in isoreg in the current version of R, as I believe the following shows > gc() used (Mb) gc trigger (Mb) max used (Mb) Ncells 120405 3.3 350000 9.4 350000 9.4 Vcells 78639 0.6 786432 6.0 392463 3.0 > for(k in 1:100) { + + y <- runif(10000) + isoreg(x,y) + } > rm(x) > rm(y) > gc() used (Mb) gc

Dear all, I wonder if it is "bad style" (or something worse) to create an "update" function which does not work on model objects of the lm, glm etc. type. Specifically, I have some graph objects (graphs as mathematical objects, not as displays) which I want to alter and for that purpose I thought of writing an update function. Would doing so violate a "deeper

I write a package foo which requires a package bar (from CRAN) to work. So in the DESCRIPTION file I write Depends: bar. I would like it to be so that when one installs foo, then it is automatically checked whether bar is installed, and if not then bar is also installed at the same time. I remember having seen packages which do so, but I can not figure out the mechanism 'Depends: bar' in