I'm new to Alteryx, and I'm trying to replicate something that takes me only a few seconds to do in Excel.
I'm try to fit a dataset to a model. In Excel, I do it this way.
This is the model (coefficients in bold): C = (Co-D) * e^(-k*t)
I set the starting values from the parameters
These are are my observations and my calculated C.
| Co | t | C - observed | C -calculated |
| 0 | 3 | 1.5 | 2 |
| 0.5 | 3 | 1.25 | 1.213 |
| 2 | 3 | 1.16 | 0.271 |
| 5 | 3 | 0.79 | 0.013 |
| 10 | 3 | 0.45 | 9E-05 |
| 30 | 3 | 0.02 | 2E-13 |
| 60 | 3 | 0.06 | 2E-26 |
I then calculate the sum square difference between the observed and calculated C values using the SUMXMY2 formula in Excel
Then I use the Solver to minimize the SSD by changing D and k. That literally takes seconds to do, and I get the best fit parameters for my dataset. How can this be done in Alteryx. I uploaded an example.
