Abstract
For the linear regression model, $y_i = \mathbf{x}_i\mathbf{\beta} + \varepsilon_i$ with fixed $\mathbf{x}_i s$, the asymptotic normality of $(\hat{\mathbf{\beta}}, \hat{\sigma})$ which minimizes the Huber-Dutter loss function, $\sum\sigma\rho\{(y_i - \mathbf{x}_i\mathbf{\beta})/\sigma\} + A_n\sigma$, is established under rather general conditions.

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