I am facing the following statistical problem:
I have a typical situation of multivariate linear regression analysis: several x-variables, one y-variable. The used numerical recipes code does its job perfectly. So far, so good.
The situation is not this simple. My basic data are measurement data, with known errors in both the x-variables and in the resulting y-variable. The errors are dependent on the respective variables.
I have been reading and googling for a while and have found some information about 'errors-in-variables-models'. As it seems to be a current mathematical R&D topic, I have found it hard to catch the state of the art.
What I'm looking for:
- information about best errors-in-variables-methods for my multivariate linear approach?
- Do you know about an appropriate coded algorithm / function like numerical recipes code?
Thank you very much!