Re: How to fit a Hill model using braidrm package?

Hi, 
Could you paste me the exact error message you’re getting when trying install.packages("drc")


> Le 25 sept. 2025 à 09:02, Luigi Marongiu <[email protected]> a écrit :
> 
> I got the same errors:
> ```
>> library(basicdrm)
>> findBestHill(Response~Dose, df)
> Error in findBestHill(Response ~ Dose, df) :
>  could not find function "findBestHill"
>> evalHillEqn(Response~Dose, df)
> Error in evalHillEqn(Response ~ Dose, df) :
>  could not find function "evalHillEqn"
> ```
> 
>> On Wed, Sep 24, 2025 at 1:47 PM peter dalgaard <[email protected]> wrote:
>> 
>> They're in basicdrm, not braidrm...
>> 
>> -pd
>> 
>>>> On 24 Sep 2025, at 11:52 , Luigi Marongiu <[email protected]> wrote:
>>> 
>>> Hello,
>>> I have a set of data coming from a dissociation experiment
>>> (protein/ligand). Since the data is required to calculate the constant
>>> of dissociation (Kd) of this pair, I am looking for a way of fitting a
>>> Hill function to the data.
>>> I have seen that the package braidrm
>>> (https://cran.r-project.org/web/packages/braidrm/index.html) provides
>>> this function, but when I launch the function `evalHillEqn`,
>>> `findBestHill` and so forth I get the error of function not found.
>>> Yet, the package is given as properly installed by the system.
>>> How can I run this package?
>>> Is there an alternative way to fit a Hill function to these 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)
>>> library(braidrm)
>>> evalHillEqn(Response~Dose, df)
>>> findBestHill(Response~Dose, df)
>>> ```
>>> 
>>> ______________________________________________
>>> [email protected] mailing list -- To UNSUBSCRIBE and more, see
>>> https://stat.ethz.ch/mailman/listinfo/r-help
>>> PLEASE do read the posting guide https://www.R-project.org/posting-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>> 
>> --
>> Peter Dalgaard, Professor,
>> Center for Statistics, Copenhagen Business School
>> Solbjerg Plads 3, 2000 Frederiksberg, Denmark
>> Phone: (+45)38153501
>> Office: A 4.23
>> Email: [email protected]  Priv: [email protected]
>> 
> 
> 
> --
> Best regards,
> Luigi
> 
> ______________________________________________
> [email protected] mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide https://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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