similar to: Constructing a list using a function...

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'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

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

> 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)) >

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.

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

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)

R-Help community, I understand that data.frames can hold elements of type double, string etc but NOT objects (such as a matrix etc). This is not convenient for me in the following situation. I have a function that takes 2 inputs and returns a vector: testfun <- function (x,y) seq(x,y,1) I have a data.frame defined as follows: testframe<-data.frame(xvalues=c(2,3),yvalues=c(4,5)) I would

Dear all, I'd appreciate any help to rectify what must be a misconception of mine how environments work: ########################## myEnv <- new.env() myEnv$a.env <- 1 myEnv$symbols.env <- "a.env" a.global <- 2 symbols.global <- "a.global" myFun <- function(symbols){do.call("print", lapply(symbols, FUN=as.name))} do.call("myFun",

Hello R Community, I have the following design question. I have a data set that looks like this (shortened for the sake of example). Gender Age M 70 F 65 M 70 Each row represents a person with an age/gender combination. We could put this data into a data frame. Now, I would like to do some actuarial analysis on this data set. To do so, I need to create and store

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),

Apologees the novice question. Currently climbing up the learning curve of R. Suppose I have the following function and the data.frame: testfun<-function(x=1,y=2) x+y testframe=data.frame(col1=c(1,2),col2=c(3,4)) When evaluating testfun, I want to use the default value for y (which is 2) and for x, I want to feed (one by one) the values in col2 of testframe. How can I achieve this please?

Dear R community, My question is not a quick fix one but it would be helpful if you have any advice for me. I have a large data set of many locations in the US and all of these locations are expressed in coordinates (longitudes and latitudes). I need a tool which returns the state that each location is situated in. So the program should return me a vector of state names (eg. NY,CA,OH, etc).

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 =

Hi, I have a data.frame that is date ordered by row number - earliest date first and most current last. I want to create a couple of new columns that show the max and min values from other columns *so far* - not for the whole data.frame. It seems this sort of question is really coming from my lack of understanding about how R intends me to limit myself to portions of a data.frame. I get the

I'm having trouble with something that looks easy. (And I'm sure it will be easier within about 1 minute of receiving my first response.) Thanks in advance. I have a collection of data frames that I need to add columns, do some calculations and then fill in the new columns. Since I have a large number of similar data frames I want to do this with functions to make the code more readable

Hi, I need to keep a running count of events that have happened in my data.frame. I found a document called usingR that had an example of doing this for random coin flips and I tried to modify it. It seems to sort of work in the beginning, but then it stops and I don't understand why. I'm trying to duplicate essentially the Excel capability of =SUM($A$1:$A(Row number)) The example

Hello, I tried for about three hours now to solve this problem but I can't figure it out. I am sure someone knows how do it. At least I hope so. I have a data frame somewhat like this: myframe <- data.frame (ID=c("Ernie", "Ernie", "Bert", "Bert"), Timestamp=c("24.09.2012 09:00", "24.09.2012 09:00", "24.09.2012 10:00",

Dear everybody, I have the following challenge. I have a data set with 2 subgroups, dates (days), and corresponding values (see example code below). Within each subgroup: I need to aggregate (sum) the values by week - for weeks that start on a Monday (for example, 2008-12-29 was a Monday). I find it difficult because I have missing dates in my data - so that sometimes I don't even have the