Error: Results are not data frames at positions:

Question

I am trying to run a fitting function on a rather large data frame, grouped by a variable named "big_group" and 'small_group'. In particular, I am trying to get predictions and coefs values of every small_group inside of big_group.

That is, I'm trying to add these new columns to my new data.frame at the end of do({ function.

Some of the groups of this data cannot be fitted due to either lack of data points or "singular gradient matrix at initial parameter estimates" error.

So, I used tryCatch method from this post of how-do-i-ignore-errors-and-continue-processing-list-items and I used following answer of @Koshke

R : catching errors in `nls`

OTH, after solving this issue I come to encounter an error is saying

Error: Results are not data frames at positions: 3

There is some discussions about this error but I could not figure it how to implement to my problem.

Here is my reproducible example; (This example is similar to my real data that's why I built the example like this)

library(minpack.lm)
library(dplyr)


set.seed(100)

data.list <- lapply(1:2, function(big_group) {
  xx <- c(sort(runif(5,1,5)),sort(runif(5,-8,-2)), rep(5,2))  ##I intentionall added the last two 5 to get unfitted groups

  yy<- sort(runif(12,0,10))

  small_group <- rep(c('a','b','c'),times=c(5,5,2)) ##small groups in under the big_group

  df <- data.frame(xx,yy,small_group,big_group)

  df <- df%>%
    group_by(big_group,small_group)%>%

  do({
  #fitting part
    fit <- tryCatch(nlsLM(yy~k*xx/2+U, start=c(k=1,U=5), data = ., trace=T, 
                          control = nls.lm.control(maxiter=100)),error=function(e) NULL)

      if(!("NULL" %in% class(fit))){

    new.range<- data.frame(xx=seq(1,10,length.out=nrow(.)))
    predicted <- predict(fit, newdata =new.range)
    coefs <- data.frame(k=coef(fit)[1],U=coef(fit)[2])

    data.frame(., new.range,predicted,coefs,row.names=NULL) ##This is the part the error came from I guess!

}})
})

This is what the data looks like; @RomanLuštrik

data.list <- lapply(1:2, function(big_group) {
  xx <- c(sort(runif(5,1,5)),sort(runif(5,-8,-2)), rep(5,2))  ##I intentionall added the last two 5 to get unfitted groups
  yy<- sort(runif(12,0,10))
  small_group <- rep(c('a','b','c'),times=c(5,5,2)) ##small groups in under the big_group
  df <- data.frame(xx,yy,small_group,big_group)
})


df <- bind_rows(data.list)
 > df
          xx       yy small_group big_group
1   1.685681 1.302889           a         1
2   2.680406 1.804072           a         1
3   3.153395 3.306605           a         1
4   3.995889 3.486920           a         1
5   4.081206 6.293909           a         1
6  -6.333657 6.952741           b         1
7  -5.070164 7.775844           b         1
8  -4.705420 8.273034           b         1
9  -2.708278 8.651205           b         1
10 -2.428970 8.894535           b         1
11  5.000000 9.541577           c         1
12  5.000000 9.895641           c         1
13  1.830856 1.234872           a         2
14  2.964927 2.114086           a         2
15  3.413297 2.299059           a         2
16  4.121434 2.533907           a         2
17  4.536908 3.577738           a         2
18 -6.807926 4.451480           b         2
19 -6.585834 4.637012           b         2
20 -6.350680 5.913211           b         2
21 -6.157485 5.975753           b         2
22 -6.016821 6.471012           b         2
23  5.000000 6.763982           c         2
24  5.000000 9.605731           c         2

Error: Results are not data frames at positions:

1 Answers