similar to: Reverse order of grouping factor in grouppedData

I have a number of x, y observations (Time, Conc) for a number of Subjects (with subject number Subj) and Doses. I can plot the individual points with xyplot fine: xyplot(Conc ~ Time | Subj, Groups=Dose, data=myData, panel = function(x,y) { panel.xyplot(x, y) panel.superpose(???) # Needs more here } ) I also like to plot on

In the example R script below, horizontal gray gridlines are drawn at y coordinates where the points are drawn with the code: panel.abline(h=y, v=xScale, col.line="gray") How do I change this so that the horizontal gray gridlines are drawn at y coordinates where the y labels are drawn? The challenge is that each panel has different y-ranges (in my real example the y-ranges and

Greetings, I have a groupedData (nmGroupedData) object created with the following syntax: Soil <- groupedData( ksat ~ conc | soil_id/sar/rep, data=soil.data, labels=list(x='Solution Concentration', y='Saturated Hydraulic Conductivity'), units=list(x='(cmol_c)', y='(cm/s)') ) the original data represents longitudinal observations in the form of:

This should be simple but I am struggling. I like to easily switch in xyplot between a linear or logarithmic y-axis by setting a logical flag logY to False or True. This switch changes the scales argument of xyplot. I found out that the original two-dimentional data (Conc vs Time in my case) are converted to log10(Conc) if log=TRUE in scales, but it appears that functions like panel.curve need to

Dear useRs? I have the following problem! I have a function that calls one or more functions, depending on the input parameters. I am searching for the fastest way to select and execute the selected functions and return their results in a list. The number of possible functions is 10, however usually only 2 are selected (although sometimes more, even all). For examples, if I have function

Dear R-users, I am in the process of creating new custom functions and am quite puzzled by some discrepancies in execution time when I run some R scripts that call those new functions. So here is the situation: - let's assume I have created two custom functions, called myg and myf; - myg is mostly a plotting function, which makes a heavy use of grid and lattice functions; - myf is a function

Sebastian: This is somewhat arcane, perhaps even a bug (correction on this welcomed). The problem is that the "expr" argument to curve() must be an actual expression, not a call to parse that evaluates to an expression. If you look at the code of curve() you'll see why (substitute() does not evaluate expr in the code). Another simple workaround other than sticking in the eval()

I am trying to avoid that dotplot sorts my x-values. They are in the correct order in the data.frame and the connections between the x-y values follows this order, but the placement of the x-values on the x-axis is re-ordered. In the following example, the order should be "d1", "d8" and "d15". However, this script places "d8" at the highest x position. Any

Dear all, I tried to create a groupedData object, where the grouping factor is not ordered. Here ist the code: library(nlme) test<-groupedData(conc~Time|Subject,order.groups=F,data=as.data.frame(Theoph)) > getGroups(test) Levels: 6 < 7 < 8 < 11 < 3 < 2 < 4 < 9 < 12 < 10 < 1 < 5 I still get an ordered factor. As always thanks for your help peter

HI. I make this code: getdata<-function('a','b','c' ,'d','e','f'){ drv <- dbDriver("SQLite") con<-dbConnect(drv, "sqlite.db") lt<-dbListTables(con) myf<-data.frame(NULL) for (i in 1:length(lt)) { myfile<-dbReadTable(con,lt[i]) myfile1<-myfile[-c(14:44)] myfile1$MODEL<-gsub(" ",

Typo: should be NULL not NUL of course An alternative approach closer to your original attempt is to use do.call() to explicitly evaluate the expr argument: w <- "1 + x^2" do.call(curve, list(expr = parse(text = w), ylab ="y")) Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus

Hi, Down a cascade of function calls, I want to use the curve function with an expression that is a variable. For various reason, this variable must be a character object and cannot be an expression as required by the curve function. How do I convert my variable into a expression that is accepted by curve? Thanks in advance for your help. ## The following attempts do not work myf <-

Hi, Infinite recursion in S3 methods seem to crash R on Windows 2000 (R terminating with the ("Rgui.exe has generated errors...") message, rather than throwing an error. This happens with both Rgui and Rterm. The following toy example triggers this: myf <- function(x, ...) UseMethod("myf") myf.default <- function(x, ...) myf(x) myf(1) ...R crashes... Which I

Dear R-users, I would like to have some advises about a problem illustrated by the following snippet. Within myf, I need to evaluate a piece of R code that is passed as a character argument and then return the objects that are created by this code. The difficulty comes from the fact that the content of the code is variable and unknown to me (obviously not in this illustration!). With the

Dear Experts, I need to include the repeated structure in our data set object, recall.sums.df, before using gls function. Thus I used groupedData. But I encountered error messages which may mean '*' is not not meaningful factor. Please let me know what I have to do. Thanks, Jeong > recall.sums.df[0:10, ] recall.values recall.ind subj replication hemi region group 1 17.515

Suppose I have f1 <- function(x) x f2 <- function(x) x^2 funlist <- list(f1,f2) Then I would like to evaluate funlist such that when x is 10 I should get a list with 10 and 100. A naive way of doint this is myf <- funlist[[1]] do.call(paste(quote(myf)), list(x=10)) myf <- funlist[[2]] do.call(paste(quote(myf)), list(x=10)) - but there has to be much

sapply() stems from S / S+ times and hence has a long tradition. In spite of that I think that it should be enhanced... As the subject mentions, sapply() produces a matrix in cases where the list components of the lapply(.) results are of the same length (and ...). However, it unfortunately "stops there". E.g., if you *nest* two sapply() calls where the inner one produces a matrix, very

Hi all, ########################################## dof=c(1,2,4,8,16,32) Q5=matrix(rt(100,dof),100,6,T,dimnames=list(NULL,dof)) par(mfrow=c(2,6)) apply(Q5,2,hist) myf=function(x){ qqnorm(x);qqline(x) } apply(Q5,2,myf) ########################################## These looks ok. However, I would like to achieve more. Apart from using a loop, is there are fast way to 'add' the titles to be

Developers: I hope this is the appropriate place to post this request. I am getting a core dump in an application of sapply. A simplified example is the following. Because simplify=TRUE is the default for sapply and tapply, the following works x <- 1:5; sapply(x,list) but the following dumps core with an access violation x <- 1:5; myf <- function(x) list(x,x); sapply(x,myf)

Why does > curve(function(y) y^2, from=0,to=1) not work, whereas > myf <- function(y) y^2 > curve(myf, from=0,to=1) work? For the former, I get the error message Error in curve(function(y) y^2, from = 0, to = 1) : 'expr' must be a function or an expression containing 'x' I'm using R1.7.0 under Windows XP. Damon Wischik.