[R] How to coerce a parameter in nls?

Gabor Grothendieck ggrothendieck at gmail.com
Tue Sep 22 14:45:10 CEST 2015


Or if you really can't bear to write out 20 terms have R do it for you:

# number of terms is the number of unique values in ref column
nterms <- length(unique(dproot$ref))

dproot2 <- do.call(data.frame, transform(dproot, ref =
outer(dproot$ref, seq(nterms),
"==") + 0))

# construct the formula as a string
terms <- paste( sprintf("Rm%d*ref.%d", 1:nterms, 1:nterms), collapse = "+")
fo <- sprintf("den ~ (%s)/(1+(depth/d50)^c)", terms)

library(nlmrt)
fm <- nlxb(fo, data = dproot2, masked = "Rm6",
         start = c(Rm1=1.01, Rm2=1.01, Rm3=1.01, Rm4=6.65, Rm5=1.01, Rm6=1,
d50=20, c=-1))


On Tue, Sep 22, 2015 at 7:04 AM, Gabor Grothendieck <ggrothendieck at gmail.com
> wrote:

> Just write out the 20 terms.
>
> On Mon, Sep 21, 2015 at 10:26 PM, Jianling Fan <fanjianling at gmail.com>
> wrote:
>
>> Hello, Gabor,
>>
>> Thanks again for your suggestion. And now I am trying to improve the
>> code by adding a function to replace the express "Rm1 * ref.1 + Rm2 *
>> ref.2 + Rm3 * ref.3 + Rm4 * ref.4 + Rm5 * ref.5 + Rm6 * ref.6" because
>> I have some other dataset need to fitted to the same model but with
>> more groups (>20).
>>
>> I tried to add the function as:
>>
>> denfun<-function(i){
>>                for(i in 1:6){
>>                  Rm<-sum(Rm[i]*ref.i)
>>                  return(Rm)}
>> }
>>
>> but I got another error when I incorporate this function into my
>> regression:
>>
>> >fitdp1<-nlxb(den ~ denfun(6)/(1+(depth/d50)^c),
>>                    data = dproot2,
>>                  start = c(Rm1=1.01, Rm2=1.01, Rm3=1.01, Rm4=6.65,
>> Rm5=1.01, Rm6=1, d50=20, c=-1),
>>                 masked = "Rm6")
>>
>> Error in deriv.default(parse(text = resexp), names(start)) :
>>   Function 'denfun' is not in the derivatives table
>>
>> I think there must be something wrong with my function. I tried some
>> times but am not sure how to improve it because I am quite new to R.
>>
>> Could anyone please give me some suggestion.
>>
>> Thanks a lot!
>>
>>
>> Jianling
>>
>>
>> On 22 September 2015 at 00:43, Gabor Grothendieck
>> <ggrothendieck at gmail.com> wrote:
>> > Express the formula in terms of simple operations like this:
>> >
>> > # add 0/1 columns ref.1, ref.2, ..., ref.6
>> > dproot2 <- do.call(data.frame, transform(dproot, ref = outer(dproot$ref,
>> > seq(6), "==") + 0))
>> >
>> > # now express the formula in terms of the new columns
>> > library(nlmrt)
>> > fitdp1<-nlxb(den ~ (Rm1 * ref.1 + Rm2 * ref.2 + Rm3 * ref.3 + Rm4 *
>> ref.4 +
>> > Rm5 * ref.5 + Rm6 * ref.6)/(1+(depth/d50)^c),
>> >          data = dproot2,
>> >          start = c(Rm1=1.01, Rm2=1.01, Rm3=1.01, Rm4=6.65, Rm5=1.01,
>> Rm6=1,
>> > d50=20, c=-1),
>> >          masked = "Rm6")
>> >
>> > where we used this input:
>> >
>> > Lines <- "   depth       den ref
>> > 1     20 0.5730000   1
>> > 2     40 0.7800000   1
>> > 3     60 0.9470000   1
>> > 4     80 0.9900000   1
>> > 5    100 1.0000000   1
>> > 6     10 0.6000000   2
>> > 7     20 0.8200000   2
>> > 8     30 0.9300000   2
>> > 9     40 1.0000000   2
>> > 10    20 0.4800000   3
>> > 11    40 0.7340000   3
>> > 12    60 0.9610000   3
>> > 13    80 0.9980000   3
>> > 14   100 1.0000000   3
>> > 15    20 3.2083491   4
>> > 16    40 4.9683383   4
>> > 17    60 6.2381133   4
>> > 18    80 6.5322348   4
>> > 19   100 6.5780660   4
>> > 20   120 6.6032064   4
>> > 21    20 0.6140000   5
>> > 22    40 0.8270000   5
>> > 23    60 0.9500000   5
>> > 24    80 0.9950000   5
>> > 25   100 1.0000000   5
>> > 26    20 0.4345774   6
>> > 27    40 0.6654726   6
>> > 28    60 0.8480684   6
>> > 29    80 0.9268951   6
>> > 30   100 0.9723207   6
>> > 31   120 0.9939966   6
>> > 32   140 0.9992400   6"
>> >
>> > dproot <- read.table(text = Lines, header = TRUE)
>> >
>> >
>> >
>> > On Mon, Sep 21, 2015 at 12:22 PM, Jianling Fan <fanjianling at gmail.com>
>> > wrote:
>> >>
>> >> Thanks Prof. Nash,
>> >>
>> >> Sorry for late reply. I am learning and trying to use your nlmrt
>> >> package since I got your email. It works good to mask a parameter in
>> >> regression but seems does work for my equation. I think the problem is
>> >> that the parameter I want to mask is a group-specific parameter and I
>> >> have a "[]" syntax in my equation. However, I don't have your 2014
>> >> book on hand and couldn't find it in our library. So I am wondering if
>> >> nlxb works for group data?
>> >> Thanks a lot!
>> >>
>> >> following is my code and I got a error form it.
>> >>
>> >> > fitdp1<-nlxb(den~Rm[ref]/(1+(depth/d50)^c),data=dproot,
>> >>                 + start =c(Rm1=1.01, Rm2=1.01, Rm3=1.01, Rm4=6.65,
>> >> Rm5=1.01, Rm6=1, d50=20, c=-1),
>> >>                 + masked=c("Rm6"))
>> >>
>> >> Error in deriv.default(parse(text = resexp), names(start)) :
>> >>   Function '`[`' is not in the derivatives table
>> >>
>> >>
>> >> Best regards,
>> >>
>> >> Jianling
>> >>
>> >>
>> >> On 20 September 2015 at 12:56, ProfJCNash <profjcnash at gmail.com>
>> wrote:
>> >> > I posted a suggestion to use nlmrt package (function nlxb to be
>> >> > precise),
>> >> > which has masked (fixed) parameters. Examples in my 2014 book on
>> >> > Nonlinear
>> >> > parameter optimization with R tools. However, I'm travelling just
>> now,
>> >> > or
>> >> > would consider giving this a try.
>> >> >
>> >> > JN
>> >> >
>> >> >
>> >> > On 15-09-20 01:19 PM, Jianling Fan wrote:
>> >> >>
>> >> >> no, I am doing a regression with 6 group data with 2 shared
>> parameters
>> >> >> and 1 different parameter for each group data. the parameter I want
>> to
>> >> >> coerce is for one group. I don't know how to do it. Any suggestion?
>> >> >>
>> >> >> Thanks!
>> >> >>
>> >> >> On 19 September 2015 at 13:33, Jeff Newmiller
>> >> >> <jdnewmil at dcn.davis.ca.us>
>> >> >> wrote:
>> >> >>>
>> >> >>> Why not rewrite the function so that value is not a parameter?
>> >> >>>
>> >> >>>
>> >> >>>
>> ---------------------------------------------------------------------------
>> >> >>> Jeff Newmiller                        The     .....       .....  Go
>> >> >>> Live...
>> >> >>> DCN:<jdnewmil at dcn.davis.ca.us>        Basics: ##.#.       ##.#.
>> Live
>> >> >>> Go...
>> >> >>>                                        Live:   OO#.. Dead: OO#..
>> >> >>> Playing
>> >> >>> Research Engineer (Solar/Batteries            O.O#.       #.O#.
>> with
>> >> >>> /Software/Embedded Controllers)               .OO#.       .OO#.
>> >> >>> rocks...1k
>> >> >>>
>> >> >>>
>> >> >>>
>> ---------------------------------------------------------------------------
>> >> >>> Sent from my phone. Please excuse my brevity.
>> >> >>>
>> >> >>> On September 18, 2015 9:54:54 PM PDT, Jianling Fan
>> >> >>> <fanjianling at gmail.com> wrote:
>> >> >>>>
>> >> >>>> Hello, everyone,
>> >> >>>>
>> >> >>>> I am using a nls regression with 6 groups data. I am trying to
>> coerce
>> >> >>>> a parameter to 1 by using a upper and lower statement. but I
>> always
>> >> >>>> get an error like below:
>> >> >>>>
>> >> >>>> Error in ifelse(internalPars < upper, 1, -1) :
>> >> >>>>   (list) object cannot be coerced to type 'double'
>> >> >>>>
>> >> >>>> does anyone know how to fix it?
>> >> >>>>
>> >> >>>> thanks in advance!
>> >> >>>>
>> >> >>>> My code is below:
>> >> >>>>
>> >> >>>>
>> >> >>>>
>> >> >>>>> dproot
>> >> >>>>
>> >> >>>>    depth       den ref
>> >> >>>> 1     20 0.5730000   1
>> >> >>>> 2     40 0.7800000   1
>> >> >>>> 3     60 0.9470000   1
>> >> >>>> 4     80 0.9900000   1
>> >> >>>> 5    100 1.0000000   1
>> >> >>>> 6     10 0.6000000   2
>> >> >>>> 7     20 0.8200000   2
>> >> >>>> 8     30 0.9300000   2
>> >> >>>> 9     40 1.0000000   2
>> >> >>>> 10    20 0.4800000   3
>> >> >>>> 11    40 0.7340000   3
>> >> >>>> 12    60 0.9610000   3
>> >> >>>> 13    80 0.9980000   3
>> >> >>>> 14   100 1.0000000   3
>> >> >>>> 15    20 3.2083491   4
>> >> >>>> 16    40 4.9683383   4
>> >> >>>> 17    60 6.2381133   4
>> >> >>>> 18    80 6.5322348   4
>> >> >>>> 19   100 6.5780660   4
>> >> >>>> 20   120 6.6032064   4
>> >> >>>> 21    20 0.6140000   5
>> >> >>>> 22    40 0.8270000   5
>> >> >>>> 23    60 0.9500000   5
>> >> >>>> 24    80 0.9950000   5
>> >> >>>> 25   100 1.0000000   5
>> >> >>>> 26    20 0.4345774   6
>> >> >>>> 27    40 0.6654726   6
>> >> >>>> 28    60 0.8480684   6
>> >> >>>> 29    80 0.9268951   6
>> >> >>>> 30   100 0.9723207   6
>> >> >>>> 31   120 0.9939966   6
>> >> >>>> 32   140 0.9992400   6
>> >> >>>>
>> >> >>>>> fitdp<-nls(den~Rm[ref]/(1+(depth/d50)^c),data=dproot,
>> >> >>>>
>> >> >>>> + start = list(Rm=c(1.01, 1.01, 1.01, 6.65,1.01,1), d50=20, c=-1))
>> >> >>>>>
>> >> >>>>> summary(fitdp)
>> >> >>>>
>> >> >>>>
>> >> >>>> Formula: den ~ Rm[ref]/(1 + (depth/d50)^c)
>> >> >>>>
>> >> >>>> Parameters:
>> >> >>>>     Estimate Std. Error t value Pr(>|t|)
>> >> >>>> Rm1  1.12560    0.07156   15.73 3.84e-14 ***
>> >> >>>> Rm2  1.57643    0.11722   13.45 1.14e-12 ***
>> >> >>>> Rm3  1.10697    0.07130   15.53 5.11e-14 ***
>> >> >>>> Rm4  7.23925    0.20788   34.83  < 2e-16 ***
>> >> >>>> Rm5  1.14516    0.07184   15.94 2.87e-14 ***
>> >> >>>> Rm6  1.03658    0.05664   18.30 1.33e-15 ***
>> >> >>>> d50 22.69426    1.03855   21.85  < 2e-16 ***
>> >> >>>> c   -1.59796    0.15589  -10.25 3.02e-10 ***
>> >> >>>> ---
>> >> >>>> Signif. codes:  0 ?**?0.001 ?*?0.01 ??0.05 ??0.1 ??1
>> >> >>>>
>> >> >>>> Residual standard error: 0.1094 on 24 degrees of freedom
>> >> >>>>
>> >> >>>> Number of iterations to convergence: 8
>> >> >>>> Achieved convergence tolerance: 9.374e-06
>> >> >>>>
>> >> >>>>> fitdp1<-nls(den~Rm[ref]/(1+(depth/d50)^c),data=dproot,
>> >> >>>>
>> >> >>>> algorithm="port",
>> >> >>>> + start = list(Rm=c(1.01, 1.01, 1.01, 6.65, 1.01, 1), d50=20,
>> c=-1),
>> >> >>>> + lower = list(Rm=c(1.01, 1.01, 1.01, 6.65, 1.01, 1), d50=20,
>> c=-1),
>> >> >>>> + upper = list(Rm=c(2.1, 2.2, 2.12, 12.5, 2.3, 1), d50=50, c=1))
>> >> >>>>
>> >> >>>> Error in ifelse(internalPars < upper, 1, -1) :
>> >> >>>>   (list) object cannot be coerced to type 'double'
>> >> >>>>
>> >> >>>> ______________________________________________
>> >> >>>> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >> >>>> https://stat.ethz.ch/mailman/listinfo/r-help
>> >> >>>> PLEASE do read the posting guide
>> >> >>>> http://www.R-project.org/posting-guide.html
>> >> >>>> and provide commented, minimal, self-contained, reproducible code.
>> >> >>>
>> >> >>>
>> >> >>
>> >> >>
>> >> >>
>> >> >
>> >> > ______________________________________________
>> >> > R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >> > https://stat.ethz.ch/mailman/listinfo/r-help
>> >> > PLEASE do read the posting guide
>> >> > http://www.R-project.org/posting-guide.html
>> >> > and provide commented, minimal, self-contained, reproducible code.
>> >>
>> >>
>> >>
>> >> --
>> >> Jianling Fan
>> >> 樊建凌
>> >>
>> >> ______________________________________________
>> >> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
>> >> https://stat.ethz.ch/mailman/listinfo/r-help
>> >> PLEASE do read the posting guide
>> >> http://www.R-project.org/posting-guide.html
>> >> and provide commented, minimal, self-contained, reproducible code.
>> >
>> >
>> >
>> >
>> > --
>> > Statistics & Software Consulting
>> > GKX Group, GKX Associates Inc.
>> > tel: 1-877-GKX-GROUP
>> > email: ggrothendieck at gmail.com
>>
>>
>>
>> --
>> Jianling Fan
>> 樊建凌
>>
>
>
>
> --
> Statistics & Software Consulting
> GKX Group, GKX Associates Inc.
> tel: 1-877-GKX-GROUP
> email: ggrothendieck at gmail.com
>



-- 
Statistics & Software Consulting
GKX Group, GKX Associates Inc.
tel: 1-877-GKX-GROUP
email: ggrothendieck at gmail.com

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