[R] How to coerce a parameter in nls?
Jianling Fan
fanjianling at gmail.com
Tue Sep 22 18:46:13 CEST 2015
Hello Prof. Nash,
My regression works good now. But I found another problem when I using
nlxb. In the output, the SE, t-stat, and p-value are not available.
Furthermore, I can't extract AIC from the output. The output looks
like below:
Do you have any suggestion for this?
Thanks a lot!
Regards,
nlmrt class object: x
residual sumsquares = 0.29371 on 33 observations
after 9 Jacobian and 10 function evaluations
name coeff SE tstat pval
gradient JSingval
Rm1 1.1162 NA NA NA
-3.059e-13 2.745
Rm2 1.56072 NA NA NA
1.417e-13 1.76
Rm3 1.09775 NA NA NA
-3.179e-13 1.748
Rm4 7.18377 NA NA NA
-2.941e-12 1.748
Rm5 1.13562 NA NA NA
-3.305e-13 1.076
Rm6 1 M NA NA NA
0 0.603
d50 22.4803 NA NA NA
4.975e-13 0.117
c -1.64075 NA NA NA
4.12e-12 1.908e-17
On 21 September 2015 at 13:38, ProfJCNash <profjcnash at gmail.com> wrote:
> I've not used it for group data, and suspect that the code to generate
> derivatives cannot cope with the bracket syntax. If you can rewrite the
> equation without the brackets, you could get the derivatives and solve that
> way. This will probably mean having a "translation" routine to glue things
> together.
>
> JN
>
>
> On 15-09-21 12:22 PM, Jianling Fan 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
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