R how to use borders and the "port" algorithm in nlslist?

Question

I would like to fit the curves on a number of data sets grouped by processing. This works very well with nlslist, but now I would like to introduce upper bounds for my parameters.

Bounding works very well when I put each group separately using nls, but apparently not when I want to speed up my work (I have many other datasets) with nlslist.

Can someone help me here with any idea how to solve this?

An example of my dataset:

DF1<-data.frame(treatment = rep(c("mineral","residues"),4),
            N_level = c(0,0,100,100,200,200,300,300),
            yield = c(8,8.5,10,10.5,11,9.8,9.5,9.7))

Df1

    treatment N_level yield
1   mineral       0   8.0
2  residues       0   8.5
3   mineral     100  10.0
4  residues     100  10.5
5   mineral     200  11.0
6  residues     200   9.8
7   mineral     300   9.5
8  residues     300   9.7

Trying to fit this dataset with nls only works well:

fit_mineral <- nls(formula = yield ~ a + b*0.99^N_level +c*N_level, 
                data=subset(DF1, subset = treatment == "mineral"), 
                algorithm = "port", start = list(a = 12, b = -8, c= -0.01), 
                upper = list(a=1000, b=-0.000001, c=-0.000001))

fit_mineral

Nonlinear regression model
model: yield ~ a + b * 0.99^N_level + c * N_level
data: subset(DF1, subset = treatment == "mineral")
    a       b       c 
13.7882 -5.8685 -0.0126 
residual sum-of-squares: 0.4679

But as soon as I try to combine things in nlslist, it does not work:

fit_mineral_and_residues <- nlsList(model = yield ~ a + b*0.99^N_level +c*N_level 
                      | treatment, data=DF1, 
                      algorithm = "port", start = list(a = 12, b = -8, c= -0.01), 
                      upper = list(a=1000, b=-0.000001, c=-0.000001))

error message:

Error in nlsList(model = yield ~ a + b * 0.99^N_level + c * N_level |  : 
unused arguments (algorithm = "port", upper = list(a = 1000, b = -1e-06, c = -1e-06))

Answer 1

- , , ​​ !

nlsList , -

library(nlme)
DF1=data.frame(treatment = rep(c("mineral","residues"),4),
               N_level = c(0,0,100,100,200,200,300,300),
               yield = c(8,8.5,10,10.5,11,9.8,9.5,9.7))
nlslist=lapply(unique(DF1$treatment),function(i) {datasubs=DF1[DF1$treatment==i,];
                                                             nls(yield ~ a + b*0.99^N_level +c*N_level, 
                                                                 data=datasubs, 
                                                                 start = list(a = 12, b = -8, c= -0.01), 
                                                                 upper = list(a=1000, b=-0.000001, c=-0.000001), 
                                                                 algorithm="port", 
                                                                 control=list(maxit=100000,tol=1e-10,warnOnly=T,minFactor=1e-10) )
                                                  })
names(nlslist)=unique(DF1$treatment)
attr(nlslist, "dims")=list(N = nrow(DF1), M = length(nlslist))
attr(nlslist, "call")=NA # this line is not correct - should be fixed
attr(nlslist,"groups")=names(nlslist)
attr(nlslist, "origOrder")=1:length(unique(DF1$treatment))
attr(nlslist, "pool")=TRUE
attr(nlslist, "groupsForm")=formula(~treatment)
class(nlslist)=c("nlsList", "lmList")

, , , "call" ( nlsList match.call() - , , ,

, , , .

test=nlsList(uptake ~ SSasympOff(conc, Asym, lrc, c0),
               data = CO2, start = c(Asym = 30, lrc = -4.5, c0 = 52))
class(test)=NULL
test

Answer 2

Tom , :

DF2 <- lapply(unique(DF1$treatment),function(i) {datasubs=DF1[DF1$treatment==i,];
                                              coef(nls(yield ~ a + b*0.99^N_level +c*N_level, 
                                                  data=datasubs, 
                                                  start = list(a = 12, b = -8, c= -0.01), 
                                                  upper = list(a=1000, b=-0.000001, c=-0.000001), 
                                                  algorithm="port", 
                                                  control=list(maxit=100000,tol=1e-10,warnOnly=T,minFactor=1e-10)))
})

DF2 <- data.frame(DF2)
names(DF2) <- levels(DF1$treatment)
DF2 <- t(DF2)
DF2

:

                a         b           c
mineral  13.78825 -5.868506 -0.01260393
residues 12.76157 -4.201832 -0.01006236

, .