caa a22 4500 47707667X CHVBK 20180405111440.0 cr unu---uuuuu 170330e19960401xx s 000 0 eng 10.1007/BF00046991 doi (NATIONALLICENCE)springer-10.1007/BF00046991 Knautz Henning Institute for Statistics and Econometrics, University of Hamburg, 20146, Hamburg, Germany aut Linear plus quadratic (LPQ) quasiminimax estimation in the linear regression model [Elektronische Daten] [Henning Knautz] If the errors in the linear regression model are assumed to be independent with nonvanishing third and finite fourth moments, then it is possible to improve all linear estimators by so-called linear plus quadratic (LPQ) estimators. These consist of linear and quadratic terms in the endogeneous variable and depend on the unknown moments of the errors which, in general, have to be estimated from the data. In this paper, we will use LPQ estimators for quasiminimax estimation and some related problems. Kluwer Academic Publishers, 1996 linear regression model nationallicence minimax estimation nationallicence linear plus quadratic estimator nationallicence Acta Applicandae Mathematica Kluwer Academic Publishers 43/1(1996-04-01), 97-111 0167-8019 43:1<97 1996 43 10440 https://doi.org/10.1007/BF00046991 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/BF00046991 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Knautz Henning Institute for Statistics and Econometrics, University of Hamburg, 20146, Hamburg, Germany aut NATIONALLICENCE 773 0- Acta Applicandae Mathematica Kluwer Academic Publishers 43/1(1996-04-01), 97-111 0167-8019 43:1<97 1996 43 10440 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer