Dear all,
I use the GLM package to compute a simple OLS regression with simulated data inside a loop. In some cases, the simulated data is such that OLS cannot be computed because PosDefException: matrix is not positive definite; Cholesky factorization failed.. That’s completely fine. However, it stops my loop. I would like to (pseudo-code):
if ols_is_feasible
return lm(@formula(y ~ x), df)
else
return Inf
end
Any idea how to easily do that?
Thank you.
I think you are looking for a try/catch statement: Control Flow · The Julia Language
The documentation is not good for lm. But you can estimate a model with perfect multi-colinearity
julia> t = (y = rand(100), x1 = 1:100, x2 = 1:100);
julia> lm(@formula(y ~ x1 + x2), t, true); # a positional argument `true` here
That’s brilliant, thank you.
Interesting. Is one of the variables ignored here?
Yeah I guess x2 is ignored.
The true tells GLM to use a pivoted cholesky:
and the interface:
Additionally, I’ve filed an issue a while ago to make this more clear by making allowrankdeficient a keyword argument here.
It would be a good first issue for someone who wants to get involved in linear estimation in Julia.
PR here.