Asymptotic theory for M-estimators of boundaries - Keith Knight (Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, 2003)
We consider some asymptotic distribution theory for M-estimators of the parameters of a linear model whose errors are non-negative; these estimators are the solutions of constrained optimization problems and their asymptotic theory is non-standard. Under weak conditions on the distribution of the errors and on the design, we show that a large class of estimators have the same asymptotic distributions in the case of i.i.d. errors; however, this invariance does not hold under non-i.i.d. errors.
urn:nbn:de:kobv:11-10050491
Keywords: 330; constrained optimization; epi-convergence; linear programming estimator; M-estimator; point processes; Schätztheorie; Mathematische Optimierung; Theorie