similar to: logical 'or' on list of vectors

Is there a conventional way to test for nested factors? I.e., if 'a' and 'b' are lists of same-length factors, does each level specified by 'a' correspond to exactly one level specified by 'b'? The function below seems to suffice, but I'd be happy to know of a more succinct solution, if it already exists. Thanks, Tim. --- "%nested.in%" <-

Dear all, I am trying to gain some experience with the function gnls from the nlme package. I tried to model the Theophyline data by trying to model the presumed dependency of the clearance on the body weight. This is my function call of gnls: gnls(conc~SSfol(Dose,Time,lKe,lKa,lCl),data=Theoph, params=list(lKe~1,lKa~1,lCl~Wt),start=c(-2.4,0.46,-3.22,0.01)) That's been the result: Error

Hi. I'm trying to find a systematic way to prevent assignment to names of existing functions. I've tried reassigning to the assignment operator, with mixed results. The function definition for "<-" below works as hoped for the demonstrated assignments to a and c. However, for the assignment based on the test function, it appears that the formal argument is not

Suppose I want to delete everything in my working directory that is not a function. It seems that sapply(ls(),is.function) always returns FALSE, because ls() returns objects of mode character. How do I evaluate is.function(), not on a character string, but on the object that character string represents? Thanks, Tim

Hi. I frequently convert date and time data to and from character representations. I'm frustrated with chron, because 'seconds' are required to create a time object (my input data never has seconds). More importantly, I cannot make chron print the format 12/30/2006 (which my output data requires). I really like the format flexibility of strftime() and strptime(), but of course

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'm maintaining a package that creates an object that is essentially a classed version of numeric. I updated recently from 2.7.1 to 2.9.0, and merges involving my class suddenly took a huge performance hit. I've traced the problem to something near rank(). From NEWS, it seems rank() etc. changed in 2.8.0. Methods for xtfrm() are supposed to help, but I've had no success. There

I see in the archives significant discussion about SAS, CDISC formats etc. for FDA, but no direct suggestion of adding a write.xport method to the foreign package. Are there significant barriers to doing so? [[alternative HTML version deleted]]

Hi. I have a vector of quantiles and a vector of probabilites that, when plotted, look very like the gamma cumulative distribution function. I can guess some shape and scale parameters that give a similar result, but I'd rather let the parameters be estimated. Is there a direct way to do this in R? Thanks, Tim. week <- c(0,5,6,7,9,11,14,19,39) fraction <-

Dear all, This question was asked a few years ago. Back then, the answer was NO. Just wonder if the package has been updated to make it possible. An example (Theoph is a dataset coming with R) ggplot(data=Theoph, aes(x=Time, y=conc)) + geom_point() + facet_wrap(~Subject) gives me all 12 subjects on one page. Can I break it down to several pages? say 2x2 on each page? Thanks. Jun

Dear all I have a problem when I make a trellis plot - I would like to reduce the white margin surrounding the plot. I used S some years age, as I remember it was possible to use the "par" and "oma" to control margin size even on a trelllis plot (see the plot below). However, it does not seem to work in R. All suggestions will be highly appreciated. Br Henrik

Hi, everyone, Try the following command to see if you get TRUE or FALSE. I get FALSE on a unix platform but TRUE on Windows. Any comment? all(paste(Theoph[1],Theoph[2])==paste(Theoph[[1]],Theoph[[2]])) -- Jun Shen PhD PK/PD Scientist BioPharma Services Millipore Corporation 15 Research Park Dr. St Charles, MO 63304 Direct: 636-720-1589 [[alternative HTML version deleted]]

r-devel, In a development version of the CRAN package metrumrg, I write ... require(reshape) setGeneric('cast') setOldClass(c('keyed','data.frame')) setMethod('cast','keyed', function ...) The result is satisfactory when sourcing the code directly, but when checking the package (which has 'reshape' as a dependency in the DESCRIPTION file) I get

Hallo Everybody How do you specify arguments for a function used within another function? Here is my problem: I am reconstructing a calculator for the burden of disease due to air pollution from publications and tools published by the WHO. The calculations make use of published dose-response relationships for particular health end-points. This is then applied to populations with known or

All, I have been able to successfully use the optim( ) function with "L-BFGS-B" to find reasonable parameters for a one-compartment open pharmacokinetic model. My loss function in this case was squared error, and I made no assumptions about the distribution of the plasma values. The model appeared to fit pretty well. Out of curiosity, I decided to try to use nlminb( ) applied to a

Dear R users: I encountered difficulties in michaelis-menten equation. I found that when I use right model definiens, I got wrong Km vlaue, and I got right Km value when i use wrong model definiens. The value of Vd and Vmax are correct in these two models. #-----right model definiens-------- PKindex<-data.frame(time=c(0,1,2,4,6,8,10,12,16,20,24),

Dear all, I can use the very nice drc package (multdrc()) to model and plot a dataframe containing dose and response values. I can also use predict.drc() to yield response values given a dose. I need to do the opposite, estimate a dose given the response. The general predict documentation seems to say that this is possible, but it does not appear that predict.drc has that capability.

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

Dear listers, I am trying to fit a model using nlsList() using alternately a SSfol() selfstart function or its developped equivalent formulae. This preliminary trial works well mydata<-groupedData(Conc~Tps|Organ,data=mydata) mymod1<-nls(Conc~SSfol(Dose,Tps,lKe,lKa,lCl),data=mydata) as well as a developped form: mymod2<-nls(Conc~Dose * exp(lKe+lKa-lCl) *

Dear All,   I could use a bit of help here, this function is hard to figure out (for me at least) I have the following so far:   PKindex<-data.frame(Subject=c(1),time=c(1,2,3,4,6,10,12),conc=c(32,28,25,22,18,14,11)) Dose<-200 Tinf <-0.5   defun<- function(time, y, parms) {  dCpdt <- -parms["kel"] * y[1]  list(dCpdt)  } modfun <- function(time,kel, Vd) {   out <-