I have attached my code for reference.
Essentially, I have two datasets: ch and cm; the former has an additional datapoint (a 12th day).
There are two unknown parameters, beta1 and beta2.
Essentially I want to fit my model to these datasets simultaneously, where I use the least-squares difference method to calculate the error [line 85-95].
When fitting to a single dataset, I understand the aim is to minimise the error. However, in this case I (maybe naively) have just computed a total error by adding these two together.
The code runs perfectly fine, I just wanted to make sure I was doing things correctly.