In the multivariate nonlinear regression model, parameter estimators and test statistics based on least squares and maximum likelihood methods are usually nonrobust. For this type of models, we introduce M-estimators and M-tests, which are robust to departures from normality. In addition, we study the asymptotic properties and consider a computational algorithm for these estimators.
|Number of pages||13|
|Journal||Pakistan Journal of Statistics|
|State||Published - 1 Jan 2010|
- Asymptotic normality
- Uniform asymptotic linearity