Hi,
I'm hoping that someone with a bit more maths knowledge than I have can help
me with my current problem. I've got a data set that contains the daily
closing price for a number of different stocks. What I want to do is find an
equation that fits those points and then use it to predict the future price.
In the past I've written an application that did a simple least squares
linear regression (what is handled by the SimpleRegression class I believe)
e.g. finding a line of best fit with the formula y = mx + c. What I need now
is something that can give me a formula of y = ax^n + bx^n1 .... mx + c
where I can choose n, the number of terms.
I think this can be handled by general least squares but the simple case I
implemented in the past was already pushing my understanding of maths. Is
this what the GLSMultipleLinearRegression class does? If so what do I need
to read up on to understand it?
Many thanks,
Graham
