How to fit a Hill model using braidrm package?

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)
```