[SciPy-user] Ols for np.arrays and masked arrays
Mon Jan 19 10:53:11 CST 2009
I do not want to sound overly critical as I would like to assist with this.
I am not sure of what your design goal is and what should the Regression
class actually contain and do. Do you want something like an R lm object?
But, I do not like that your _init_ function does so much work that
probably does not belong there. I would have thought that it would just
initialize certain important variables including the solutions (b). One
reasons is perhaps you just want to update the input arrays but this
design forces you to create a new object.
At what stage should you check for valid inputs and the correct
dimensions of x?
I would also prefer the object having the standard errors of the
solutions and eventually other 'useful' statistics like sum of squares,
R-squared. However, I do not know how to the standard errors using
linalg.lstsq (I vaguely recall there is another way that would work).
The others are easy to get probably on demand like R's summary function.
More information about the SciPy-user