similar to: do.call in "with" construction

Dear All, In R 3.6.3 (and earlier), method dispatch used to work for methods stored in local environments that are attached to the search path. For example: myfun <- function(y) { out <- list(y=y) class(out) <- "myclass" return(out) } print.myclass <- function(x, ...) print(formatC(x$y, format="f", digits=5)) myfun(1:4) # prints: [1]

Hi all, I ran into a strange error: I am trying to create a package skeleton for a new source package from within a function. Objects that are created in this function are to be included in my package, but for some reason, I get an error message saying that these objects cannot be found. Here is the code: ###### myfun <- function(pkgName,x){ myenv <- new.env() apply(x, 1,

Hi All I have a dataframe: myframe<-data.frame(ID=c("first","second"),x=c(1,2),y=c(3,4)) And I have a function myfun: myfun<-function(x,y) x+y I would like to write a function myfun2 that takes myframe and myfun as parameters and returns a list as below: mylist $first [1] 4 $second [2] 6 Could you please help me with this? Doesn't seem like the

Is there a way to call a function, and explicitly set an argument to 'not specified'? My situation is the following. I have a function which passes on most of its arguments to another function. The second function, myfun2, serializes all arguments and is out of my control. myfun <- function(...){ return(myfun2(...)); } now, the value for arguments of myfun are stored in variables.

Hello all, I'm trying to use the apply function on a data frame, by applying a function that takes a one row data.frame as argument . Here's the example : myfun = function(x) paste(x$f1 , x$f2) df = data.frame(f1 = c(1,4,10),f2 = "hello") apply(df,1,myfun) ==> Does not work (I get "character(0)" ) Though : myfun(df[1,]) works, and myfun(df) works as well. So if

I am not as expert as John, but I thought it worth pointing out that the variable substitution technique gives up one set of constraints for another (b=0 in this case). I also find that plots help me see what is going on, so here is my reproducible example (note inclusion of library calls for completeness). Note that NONE of the optimizers mentioned so far appear to be finding the true best

I ran the following script. I satisfied the constraint by making a*b a single parameter, which isn't always possible. I also ran nlxb() from nlsr package, and this gives singular values of the Jacobian. In the unconstrained case, the svs are pretty awful, and I wouldn't trust the results as a model, though the minimum is probably OK. The constrained result has a much larger sum of squares.

I am using nlsLM {minpack.lm} to find the values of parameters a and b of function myfun which give the best fit for the data set, mydata. mydata=data.frame(x=c(0,5,9,13,17,20),y = c(0,11,20,29,38,45)) myfun=function(a,b,r,t){ prd=a*b*(1-exp(-b*r*t)) return(prd)} and using nlsLM myfit=nlsLM(y~myfun(a,b,r=2,t=x),data=mydata,start=list(a=2000,b=0.05), lower = c(1000,0),

I've seen a number of problems like this over the years. The fact that the singular values of the Jacobian have a ration larger than the usual convergence tolerances can mean the codes stop well before the best fit. That is the "numerical analyst" view. David and Jeff have given geometric and statistical arguments. All views are useful, but it takes some time to sort them all out and

https://cran.r-project.org/web/views/Optimization.html (Cran's optimization task view -- as always, you should search before posting) In general, nonlinear optimization with nonlinear constraints is hard, and the strategy used here (multiplying by a*b < 1000) may not work -- it introduces a discontinuity into the objective function, so gradient based methods may in particular be

When trying out some variations with `[.data.frame` I noticed some (to me) odd behaviour, which I found out has nothing to do with `[.data.frame`, but rather with the way arguments are matched, when mixing named/unnamed and missing/non-missing arguments. Consider the following example: myfun <- function(x,y,z) { ? print(match.call()) ? cat('x=',if(missing(x)) 'missing'

> On Jun 18, 2017, at 6:24 AM, Manoranjan Muthusamy <ranjanmano167 at gmail.com> wrote: > > I am using nlsLM {minpack.lm} to find the values of parameters a and b of > function myfun which give the best fit for the data set, mydata. > > mydata=data.frame(x=c(0,5,9,13,17,20),y = c(0,11,20,29,38,45)) > > myfun=function(a,b,r,t){ > prd=a*b*(1-exp(-b*r*t)) >

Dear R experts. I might be missing something obvious. I have been trying to fix this problem for some weeks. Please help. #data ped <- c(rep(1, 4), rep(2, 3), rep(3, 3)) y <- rnorm(10, 8, 2) # variable set 1 M1a <- sample (c(1, 2,3), 10, replace= T) M1b <- sample (c(1, 2,3), 10, replace= T) M1aP1 <- sample (c(1, 2,3), 10, replace= T) M1bP2 <- sample (c(1, 2,3), 10, replace= T)

I am trying to write a function, which would allow to call various methods and would pass to them extra arbitrary parameters. My first attempt was to use call() as illustrated below, but apparently '...' cannot be used in such context. How can this be achieved ? Best regards, Ryszard > myfun <- function(method, x, ...) { + v <- eval(call(method, x, ...)) + } > method =

Dear Wolfgang, I think this new behaviour is related to the following R 4.0.0 NEWS item: > S3 method lookup now by default skips the elements of the search path between the global and base environments. Your environment "myenv" is attached at position 2 of the search() path and thus now skipped in S3 method lookup. I have just noticed that

Dear all, I just found that some of the packages are not able to load any more, after I installed R2.0.1 in my Mac, it even affects my old R1.8 installs. It gives me errors when I load packages that contains "myEnv" settings. such as: RMySQL, DBI, Rggobi, etc. But others that does not require "myENV" is all right, like tcltk that only calls the c functions. The errors

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi, how can I automatically access the functions that I loaded into a separate environment? > save(A,B,file="myfun.r") > load("myfun.r",envir=(ENV<-new.env())) > ls(ENV) [1] "A" "B" ?"[" turned up that I can access the functions via > ENV$A function () { } > ENV$A() NULL Now, how

Dear Developers, A lot has been changed in the R12.0 with respect to behavior of "environment" subclasses. Many thanks for that. One small irregularity, though; new.env does not allow the parent to be from S4 subclass. > setClass("myenv", contains="environment") [1] "myenv" > new.env(parent=new("myenv")) Error in new.env(parent =

the following returns an error in an 'exists' call on my machine MyEnv <- new.env() setClass("Numeric", "numeric", where=MyEnv) franklin parlamis > version _ platform powerpc-apple-darwin8.7.0 arch powerpc os darwin8.7.0 system powerpc, darwin8.7.0 status beta major 2 minor 4.0 year

Hi, suppose that I have the following data.frame: cnae4 cnpj 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 Y 24996 10020470 1 1 2 12 16 21 17 51 43 19 183 24996 10020470 69 91 79 92 91 77 90 96 98 108 891 36145 10020470 0 0 0 0 2 83 112 97 91 144 529 44444 10023333 5 20 60 0 0 0 0 5 20 1000 1110 I would like to create a new variable X that indicates which