I have a dataset consisting of two columns X and Y.
| X | Y |
| ------- | ------- |
| 0 | 0 |
| 1 | 2207 |
| 2 | 2407 |
| 5 | 2570 |
| 7 | 2621 |
| 10 | 2723 |
| 20 | 2847 |
| 30 | 2909 |
| 40 | 2939 |
| 50 | 2963 |
The values in the second column Y are certain figures estimated from column X.
The problem comes back when I have to predict a new value not present in the column Y and that consequently I go back to the corresponding value in column X. To find the values within the range of the column Y written above I use interpolation.
I need that the regression function allow me to predict all the values I want which are greater than the values in column Y.
For now I have used a software (MyCurveFit) which gives me the values of the columns X and Y,creating a graph and a function.
The most similar function I think is Asymptotic Regression but I don't know how to develop it.
What I have tried:
So, I'd like to know what the equation was that, if you put a new value in the Y column, allow me to continue the line obtained by Asymptotic Regression and consequently predicting the X result.
| X | Y |
| ------- | ------- |
| ? | 2980 |
| ? | 2995 |
| ? | 2999 |
| ? | 3005 |
As a programming language I'm using Python. Thank you all!