β Scribed by David A. Belsley
No coin nor oath required. For personal study only.
The traditional three-step procedure for correcting for heteroskedasticity uses a consistent but biased estimator for the variances 2 t in enacting the second step. An estimator is developed here that is unbiased in the presence of heteroskedasticity. Its behavior is examined along with the traditional estimator and another known to be unbiased in the absence of heteroskedasticity. The behavior of these corrective methods is also examined when the form and arguments of the skedastic function are misspeciΓΏed. This is accomplished using Monte Carlo studies of several situations of interest. ?
π SIMILAR VOLUMES
Model updating is a very active research field, in which significant effort has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-c