[1] Balke, N. S., Fomby, T. B.:
Large shocks, small shocks, and economic fluctuations: outliers in macroeconomic time series. J. Appl. Econom. 9 (1994), 181-200.
DOI 10.1002/jae.3950090205
[3] Čížek, P.:
General trimmed estimation: robust approach to nonlinear and limited dependent variable models. CentER discussion paper. Econom. Theory (to appear).
MR 2456536
[4] Čížek, P.: Efficient robust estimation of regression models. CentER discussion paper Vol. 87. CentER Tilburg University Tilburg (2007).
[7] Mašíček, L.: Diagnostics and sensitivity of robust models. Unpublished Ph.D. Thesis Faculty of Mathematics and Physics, Charles University Prague (2004).
[9] Rousseeuw, P. J.:
Multivariate estimation with high breakdown point. Mathematical statistics and applications, Vol. B W. Grossman, G. Pflug, I. Vincze, W. Wertz Reidel Dordrecht (1985), 283-297.
MR 0851060 |
Zbl 0609.62054
[10] Rousseeuw, P. J., Leroy, A. M.:
Robust Regression and Outlier Detection. John Wiley & Sons New York (1987).
MR 0914792 |
Zbl 0711.62030
[11] Sakata, S., White, H.:
High breakdown point conditional dispersion estimation with application to S&P 500 daily returns volatility. Econometrica 66 (1998), 529-567.
DOI 10.2307/2998574
[14] Víšek, J. Á.:
The least weighted squares II. Consistency and asymptotic normality. Bulletin of the Czech Econom. Soc. 9 (2002), 1-28.
MR 2208518
[15] Víšek, J. Á.: Instrumental weighted variables. Austr. J. Stat. 35 (2006), 379-387.