TY  - BOOK
A1  - Konakov, Valentin S.
A1  - Läuter, Henning
A1  - Liero, Hannelore
T1  - Nonparametric versus parametric goodness of fit
T3  - Discussion Paper / Humboldt-Universität zu Berlin, Institut für Mathematik, SFB 373
Y1  - 1995
VL  - 49
CY  - Berlin
ER  - 
TY  - BOOK
A1  - Konakov, Valentin S.
A1  - Läuter, Henning
A1  - Liero, Hannelore
T1  - Comparison of the asymptotic power of tests based on L2- and L-norms under non-standard local alternatives
T3  - Discussion Paper / Humboldt-Universität zu Berlin, Institut für Mathematik, SFB 373
Y1  - 1995
VL  - 10
CY  - Berlin
ER  - 
TY  - JOUR
A1  - Liero, Hannelore
A1  - Läuter, Henning
A1  - Konakov, V. D.
T1  - Nonparametric versus parametric goodness of fit
Y1  - 1998
SN  - 0323-3944
ER  - 
TY  - BOOK
A1  - Läuter, Henning
T1  - Estimation in partly parametric additive Cox models
T3  - Preprint / Universität Potsdam, Institut für Mathematik, Arbeitsgruppe Partiell
Y1  - 2003
SN  - 1437-739X
PB  - Univ.
CY  - Potsdam
ER  - 
TY  - JOUR
A1  - Läuter, Henning
T1  - Nonparametric versus parametric goodness of fit
Y1  - 1996
ER  - 
TY  - JOUR
A1  - Läuter, Henning
T1  - Nonlinear estimation problems
Y1  - 1999
ER  - 
TY  - INPR
A1  - Läuter, Henning
T1  - Empirical Minimax Linear Estimates
N2  - We give the explicit solution for the minimax linear estimate. For scale dependent models an empirical minimax linear estimates is de¯ned and we prove that these estimates are Stein's estimates.
T3  - Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint - 2008, 06 
Y1  - 2008
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-49483
ER  - 
TY  - BOOK
A1  - Läuter, Henning
A1  - Liero, Hannelore
T1  - Ill-posed inverse problems
T3  - Discussion Paper / Humboldt-Universität zu Berlin, Institut für Mathematik, SFB 373
Y1  - 1996
CY  - Berlin
ER  - 
TY  - BOOK
A1  - Läuter, Henning
A1  - Nikulin, Mikhail S.
T1  - Parametric versus nonparametric goodness of fit : another view
T3  - Discussion paper / Humboldt-Universität zu Berlin, SFB 373, Quantifikation und Simulatio
Y1  - 1999
PB  - Humboldt-Univ.
CY  - Berlin
ER  - 
TY  - INPR
A1  - Läuter, Henning
A1  - Ramadan, Ayad
T1  - Modeling and Scaling of Categorical Data
N2  - Estimation and testing of distributions in metric spaces are well known. R.A. Fisher, J. Neyman, W. Cochran and M. Bartlett achieved essential results on the statistical analysis of categorical data. In the last 40 years many other statisticians found important results in this field. Often data sets contain categorical data, e.g. levels of factors or names. There does not exist any ordering or any distance between these categories. At each level there are measured some metric or categorical values. We introduce a new method of scaling based on statistical decisions. For this we define empirical probabilities for the original observations and find a class of distributions in a metric space where these empirical probabilities can be found as approximations for equivalently defined probabilities. With this method we identify probabilities connected with the categorical data and probabilities in metric spaces. Here we get a mapping from the levels of factors or names into points of a metric space. This mapping yields the scale for the categorical data. From the statistical point of view we use multivariate statistical methods, we calculate maximum likelihood estimations and compare different approaches for scaling.
T3  - Mathematische Statistik und Wahrscheinlichkeitstheorie : Preprint - 2010, 03 
Y1  - 2010
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus-49572
ER  -