[R] differing number of rows when running nls regression
Eric Berger
er|cjberger @end|ng |rom gm@||@com
Sat Sep 20 12:25:26 CEST 2025
I tried running your code. I did the following
i. I omitted the preview() statement because x_25_2024 was not provided
ii. I omitted the start=list(a=A,b=B) from the nls() statement.
iii. I ran the nls command using the form that you defined
> foo <- nls(form, data=df)
It ran with no errors.
> plot(foo)
worked.
FYI my sessionInfo()
> sessionInfo()
R version 4.5.1 (2025-06-13)
Platform: x86_64-pc-linux-gnu
Running under: Ubuntu 22.04.5 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so;
LAPACK version 3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
time zone: Asia/Jerusalem
tzcode source: system (glibc)
attached base packages:
[1] stats graphics grDevices datasets utils methods base
other attached packages:
[1] nlstools_2.1-0 nlme_3.1-166
loaded via a namespace (and not attached):
[1] compiler_4.5.1 tools_4.5.1 bspm_0.5.7 grid_4.5.1
lattice_0.22-6
HTH,
Eric
On Sat, Sep 20, 2025 at 9:02 AM Luigi Marongiu <marongiu.luigi using gmail.com>
wrote:
> I have some data (y=Response, x=Dose) that is distributed roughly as a
> curve. I am trying to fit a non-linear regression model on the data
> using negative logistic function (even if the data show a rise in the
> final part of the curve that the logistic won't accommodate for).
> I used a rough graphical approach to guess the starting values then
> the package `nlstools` for a better overview of the data. However, I
> get the error "differing number of rows".
> If I run `nls` directly, I get the error" "Error in 1 + exp :
> non-numeric argument to binary operator"
> Why is that happening?
> How can I set the model?
> Is there a better curve function to fit the data?
> Thank you
>
> ```
> df = data.frame(Response = c(890.72, 895.46, 895.63,
> 894.72, 895.49, 893.59,
> 892.53, 895.06, 897.21, 889.27, 876.05,
> 857.96, 862.02, 858.36,
> 890.94, 890.8, 887.22, 888.91, 890.83,
> 889.92, 891.76, 890.32,
> 886.35, 878.11, 866.57, 859.04, 863.64,
> 880.16, 884.15, 879.57,
> 878.89, 882.27, 881.59, 880.98, 881.45,
> 876.19, 868.32, 859.16,
> 850.53, 853.21, 859.34, 859.73, 861.19),
> Dose = c(0.0000000015, 0.000000003,
> 0.000000006, 0.000000012,
> 0.000000024, 0.000000048, 0.000000095,
> 0.00000018,
> 0.00000038, 0.00000078, 0.0000015,
> 0.000013, 0.000025,
> 0.00005, 0.0000000015, 0.000000003,
> 0.000000006,
> 0.000000012, 0.000000024, 0.000000048,
> 0.000000095,
> 0.00000018, 0.00000038, 0.00000078,
> 0.0000015, 0.000025,
> 0.00005, 0.0000000015, 0.000000003,
> 0.000000006,
> 0.000000012, 0.000000024, 0.000000048,
> 0.000000095,
> 0.00000018, 0.00000038, 0.00000078,
> 0.0000015, 0.000003,
> 0.000006, 0.000013, 0.000025, 0.00005)
> )
> plot(Response~log10(Dose), df)
> abline(a=500, b=-60)
> abline(v=log10(0.3e-6))
> A = 0.3e-6 # plateau
> B = -60 # slope
> library(nlstools) # NL regression
> form = as.formula(Response ~ ( (exp(a+b*Dose)) / (1+exp-(a+b*Dose)) ) )
> preview(form, data = x_25_2024, start=list(a=A, b=B))
> nls(Response ~ ( (exp(a+b*Dose)) / (1+exp-(a+b*Dose)) ),
> data=df, start=list(a=A, b=B))
> ```
>
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