[R] How to coerce a parameter in nls?
Gabor Grothendieck
ggrothendieck at gmail.com
Mon Sep 21 18:43:42 CEST 2015
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
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