TY - RPRT A1 - Wellisch, Ulrich T1 - Erarbeitung von Prüfverfahren zur Vereinheitlichung der energetischen Bewertung von großformatigen, transparenten Bausystemen unter in situ Randbedingungen. Teilprojekt Hochschule Rosenheim: Analyseverfahren und Mitarbeit im IEA ECBCS Annex 58 „Reliable building performande characterisation and prediction based on full scale dynamic measurements“, Hochschule Rosenheim, 2016 KW - Bausysteme KW - Energetische Bewertung KW - in situ Randbedingungen Y1 - 2018 ER - TY - RPRT A1 - Sandor, V. A1 - Schalk, D. A1 - Sussmann, M. A1 - Wellisch, Ulrich T1 - Statistische Datenanalyse und Modellierung - Einsatzmöglichkeiten von Machine Learning Verfahren. Forschungsbericht 2016 Hochschule Rosenheim KW - Statistische Datenanalyse KW - Statistische Modellierung KW - Machine Learning Y1 - 2016 ER - TY - RPRT A1 - Sandor, V. A1 - Schalk, D. A1 - Sussmann, M. A1 - Wellisch, Ulrich T1 - Statistische Datenanalyse und Modellierung - Machine Learning in der Versicherung, Risikomodelle auf dem Prüfstand. Forschungsbericht 2016 Hochschule Rosenheim KW - Statistische Datenanalyse KW - Risikomodellierung KW - Machine Learning Y1 - 2016 ER - TY - RPRT A1 - Sebald, D. A1 - Sussmann, M. A1 - Sandor, V. A1 - Wellisch, Ulrich T1 - Statistische Datenanalyse und Modellierung - Risikomodellierung in der Krafthaftpflichtversicherung. Forschungsbericht Hochschule Rosenheim 2015 KW - Statistische Datenanalyse KW - Risikomodellierung KW - Kfz- Haftpflichtversicherung Y1 - 2015 ER - TY - RPRT A1 - Pruschka, H. A1 - Wellisch, Ulrich T1 - Asymptotic behaviour of estimation equations with functional nuisance or working parameter. N2 - We are concerned with the asymptotic theory of semiparametric estimation equations. We are dealing with estimation equations which have a parametric component of interest and a functional (nonparametric) nuisance component. We give sufficient conditions for the existence and the asymptotic normality of a consistent estimation equation estimator for the parameter of interest. These conditions concern the asymptotic distribution of the estimation function and of its derivative as well as the effect of the functional nuisance part in the estimation equation. In order to treat the nonparametric component we introduce a general differential calculus and a general mean value theorem. For the nonparametric part in the estimation equation we distinguish two cases: the situation of a (classical) nuisance parameter and the case of a so called working parameter. As a special case we get regularity conditions for estimation equations with finite dimensional nuisance or working parameter. As an example we present the semiparametric linear regression model. KW - Estimating equations KW - Asymptotic distribution KW - semiparametric linear regression model Y1 - 1997 ER - TY - RPRT A1 - Küchenhoff, H. A1 - Wellisch, Ulrich T1 - Asymptotics for generalized linear segmented regression models with an unknown breakpoint N2 - We consider asymptotic theory for the maximum likelihood estimator in the generalized linear model with an unknown breakpoint. A proof for the asymptotic normality is given. The methods are based on the work of Huber (1967). The main problem is the non--differentiability of the likelihood and the score function, which requires non--standard methods. An example from epidemiology is presented, where confidence intervals for the parameters are calculated with the asymptotic results. KW - Asymptotic theory KW - Linear segmentet regression models Y1 - 1997 ER - TY - RPRT A1 - Bauer, L. A1 - Feldmeier, F. A1 - Paulus, F. A1 - Schreyer, M. A1 - Wellisch, Ulrich T1 - In situ Prüfverfahren für transparente Bauteile KW - transparente Bauteile KW - in situ Prüfverfahren Y1 - 2014 ER -