similar to: S4: Multiple inheritance

I am using nls to fit a non linear function to some data. The non linear function is: y= 1- exp(-(k0+k1*p1+ .... + kn*pn)) I have chosen algorithm "port", with lower boundary is 0 for all of the ki parameters, and I have tried many start values for the parameters ki (including generating them at random). If I fit the non linear function to the same data using an external

Thank you very much for your useful suggestions. These are exactly what I was looking for. foo <- list(foo1, foo2, foo3) lapply(foo, function(x) matrix(unlist(x), nrow = length(x), byrow = TRUE)) or lapply(foo, function(x) do.call('rbind', x)) Best, Muhammad Subianto On 4/11/06, Muhammad Subianto <msubianto at gmail.com> wrote: > Dear all, > I have a result my experiment

Dear all, I have a result my experiment like this below (here my toy example): foo1 <- list() foo1[[1]] <- c(10, 20, 30) foo1[[2]] <- c(11, 21, 31) foo2 <- list() foo2[[1]] <- c(100, 200, 300) foo2[[2]] <- c(110, 210, 310) foo3 <- list() foo3[[1]] <- c(1000, 2000, 3000) foo3[[2]] <- c(1100, 2100, 3100) list(foo1,foo2,foo3) The result: > list(foo1,foo2,foo3) [[1]]

Dear List: In short, I am writing a number of functions as building blocks for other functions and have some questions about scoping and passing arguments. Suppose I have functions foo1, foo2, and foo3 such that: foo1<-function(a=1,b=TRUE,c=FALSE){#do stuff}; foo2<-function(x=1,y=FALSE,z=c(1,2,3,4)){#do stuff}; foo3<-function(lambda,...){lambda*foo1()*foo2()}; I want to be able to

Hi the list In the DESCRIPTION file of my package foo0, I have: Depends: foo1 Imports: foo2 Suggest: foo3 Enhence: foo4 If I understand correctly, to install foo0 on my computer, I need to already have foo1, foo2, foo3. foo4 is not necessary. I my R sesssion, when I will write: library(foo0), then the package foo1 will be attach. foo2, foo3 and foo4 will not. Is that correct? But what is

Hi all, For some reason, I would like to use functions bellow (see example code bellow), but instead I get the following error message: *Error in foo2(...) : unused argument(s) (arg3 = 3)* #--------------------- # example code #--------------------- foo1 <- function(arg1,...) { print(arg1) foo2(...) foo3(...) } foo2 <- function(arg2) { print(arg2) } foo3 <- function(arg3) {

Dear friends, what is this error message in gam???? I cannot understand what it means .... is it a bug? gam_bray_scot24_pc_0505<gam(bray~s(PC1,PC2,PC3,PC4,PC5, PC1.1,PC2.1,PC3.1,PC4.1,PC5.1),data=dist_scot24_vector_with_climate) Error in if (length(data) != vl) { : missing value where TRUE/FALSE needed Calls: gam ... smooth.construct -> smooth.construct.tp.smooth.spec -> array In

Hi to all Authors@R: c(person("fooa","foob", role = c("aut","cre"), email = "fooa.foob@fooc.de"), person("foo1","foo2", role = c("ctb"), email = "foo1.foo2@foo3.de")) Author: fooa foob, with contributions from foo1 foo2 using r CMD check --as-cran .. (R 3.1

Dear list, I have a strange requirement .... I have a vector, for example v<- c(0,0,0,0,1,2,4,6,8,8,8,8). I have a value,for example x<- 4.8. I would like to understand in which sub interval of v is x. In this case, v would be in the sub interval [4,6] that is in the subinterval starting from element j=7 to the element j+1=8. Can we do that with an R command? Regards -- Corrado Topi

I have a general style question about R coding. Suppose I'm writing a function (foo1) that calls other functions (foo2, foo3, ...) which have complicated argument lists (e.g. optim(), plot()), _and_ I may be calling several different functions in the body of foo1. Since foo2 and foo3 have different sets of arguments, I can't just use "..." ; I did write some code a while ago

Dear R-friends, How do you test the goodness of prediction of a model, when you predict on a set of data DIFFERENT from the training set? I explain myself: you train your model M (e.g. glm,gam,regression tree, brt) on a set of data A with a response variable Y. You then predict the value of that same response variable Y on a different set of data B (e.g. predict.glm, predict.gam and so on).

Dear friends, I am testing glm as at page 514/515 of THE R BOOK by M.Crawley, that is on proportion data. I use glm(y~x1+,family=binomial) y is a proportion in (0,1), and x is a real number. I get the error: In eval(expr, envir, enclos) : non-integer #successes in a binomial glm! But that is exactly what was suggested in the book, where there is no mention of a similar warning. Where am I

Dear friends, Do you know how to calculate the CONCAVE hull of a set of points (2- dimensional or n-dimensional)? is that possible in R? (With a "smoothing" parameter of course). Best, -- Corrado Topi Global Climate Change & Biodiversity Indicators Area 18,Department of Biology University of York, York, YO10 5YW, UK Phone: + 44 (0) 1904 328645, E-mail: ct529 at york.ac.uk

Dear R developers, Taking advantage of the yesterday discussion about the use of Depends/Import/Suggests/Enhances, I would like to add a related question. Let's assume, in the DESCRIPTION file of my package foo0, I have: Depends: foo1 Imports: foo2 while in the NAMESPACE file of my package I have importFrom("foo2", f2) and within my package I use the following two external

Hi everyone, Hi ggplot users in particular, ggplot makes it very easy to plot things given their names when you use it interactively (and therefore can provide the names of the columns). qplot(x,foo,data=A) where A has columns (x,y,foo,bar) for example but I would like to use this from inside a function to which the name of the column is given. I cannot find an elegant way to make this

Hi, I have several data structures (xts structures). I then have a list of the names of those objects. I'd like to access the object by name. For example: foo1 <- as.xts(....) foo2 <- as.xts(...) foo3 <- as.xts(...) structs <- c("foo1", "foo2", "foo3") for (thisOne in structs){ print(thisOne$colA) } The above fails. Clearly I'm missing a

My apologies for asking what is doubtless a dumb question, but I have scant experience in R. It would be very convenient in doing lots of plots to be able to do them in a loop that stepped through a vector of variable names. For example one could say x<-("mydates") y<-c("foo1","foo2","foo3") #where "foon" were vectors

Hi I have within a quite big function foo1, an internal function foo2. Now, in order to have a cleaner code, I wish to have the internal foo2 as "external". This foo2 was using arguments within the foo1 environment that were not declared as inputs of foo2, which works as long as foo2 is within foo1, but not anymore if foo2 is external, as is the case now. Now, I could add all those

Hi, I'm running postfix as SMTP-server and dovecot as IMAP-server. The server has multiple IPs, and postfix is configured that every domain is using a separate IPv4-address. Examle: foo1.com --> 11.22.33.44 foo2.com --> 22.33.44.55 foo3.com --> 33.44.55.66 bar.org --> 66.77.88.99 The hostname of the server is: mail.bar.org Now I have a request from one of my customers,

Let's say I have, for some reason, a bunch of scalars (i.e. single-valued variables) and I want to merge them all into a single vector of values. Can someone recommend a better function, or simpler way, to do so than the following? Suppose my scalars' names are foo1, foo2, foo3, foo1high, foo2high, foo3lo2, etc. Then I can do: >ls(pat='foo')->thels