I have some data which I would model via standard multiple regression except:
- There is censoring (left-censored, fixed but varying censoring points which are known)
- The errors are assumed independent normal but of non-constant variance. Weights are available.
If it was constant variance, I would use the Tobit model and
survreg() function in R. Does anyone know of the/an approach when the variance is not constant (but weights for variances are available)?