I'm asking this question because I couldn't figure it out why nlxb fitting function does not work with the predict() function.
I have been looking around to solve this but so far no luck:(
I use dplyr to group data and use do to fit each group using nlxb from nlmrt package.
Here is my attempt
set.seed(12345)
set =rep(rep(c("1","2","3","4"),each=21),times=1)
time=rep(c(10,seq(100,900,100),seq(1000,10000,1000),20000),times=1)
value <- replicate(1,c(replicate(4,sort(10^runif(21,-6,-3),decreasing=FALSE))))
data_rep <- data.frame(time, value,set)
> head(data_rep)
    #    time        value set
    #1     10 1.007882e-06   1
    #2    100 1.269423e-06   1
    #3    200 2.864973e-06   1
    #4    300 3.155843e-06   1
    #5    400 3.442633e-06   1
    #6    500 9.446831e-06   1
    *      *       *         *  
library(dplyr)
library(nlmrt)
    d_step <- 1
    f <- 1e9
    d <- 32      
    formula = value~Ps*(1-exp(-2*f*time*exp(-d)))*1/(sqrt(2*pi*sigma))*exp(-(d-d_ave)^2/(2*sigma))*d_step
      dffit = data_rep %>% group_by(set) %>%
      do(fit = nlxb(formula ,
                    data = .,
                    start=c(d_ave=44,sigma=12,Ps=0.5),
                    control=nls.lm.control(maxiter = 100),
                    trace=TRUE))
--------------------------------------------------------
There are two points I would like to get finally,
1)First, how to get fitting coefficients of each group in continuation to dffitpipeline. 
2) Doing prediction of based on new x values.
for instance range <- data.frame(x=seq(1e-5,20000,length.out=10000))
predict(fit,data.frame(x=range)
Error in UseMethod("predict") : 
  no applicable method for 'predict' applied to an object of class "nlmrt"
Since nlxb is working smoothly compared to nls r-minpack-lmnls-lm-failed-with-good-results  I would prefer solutions with nlxb. But if you have a better solution please let us know.