A robust estimate of variance in a linear model

Standard statistical procedures for variance in Gaussian models are not robust against departures from normality. One of the possible reasons is that the variance of the variance estimate depens on kurtosis of the underlying distribution. In the paper, the most robust estimate of the variance in a class of quadratic forms is constructed.