[PDF] Top 20 Scheipl, Fabian (2011): Bayesian Regularization and Model Choice in Structured Additive Regression. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik

... linearen und glatten funktionalen Formen der Effekte unterschieden ...Implementierung und Validierung einer Erweiterung des Stochastic Search Variable Selection-Ansatzes (SSVS) um in strukturi- erten ... See full document

... variable selection is obtained. Especially the predictive performance improves in nearly all simulation settings. Further the accuracy of the predictor estimate change for the better in the Poisson and the binomial case. ... See full document

... popular choice (Anbeek et ...binary model needs to be estimated for each brain ...binary regression models can be ...the regression models jointly, for example using the framework of STAR ... See full document

... ridge regression estimate as posterior ...the regression coefficients β are ...full Bayesian version of the lasso by assuming an additional gamma prior for the squared shrinkage ...various ... See full document

... generalized additive regression models; and this was probably one of the key starting points for the growing popularity of boosting as a statistical learning ... See full document

... the Bayesian Information Criterion (BIC) and Minimum Descrip- tion Length (MDL) ...for model selection dur- ing clustering, and these approaches involve a lossless compression of the ...the model are ... See full document

... to regression modeling, support vec- tor machines and boosting might rather be seen as ‘meta-algorithms’ that provide rich frameworks and can be used to derive specialized ... See full document

... Boosting originates in machine learning and aims at combining many weak learners to form a single strong learner for classification (e.g., Friedman et al., 2000; Schapire and Freund, 2012). Weak learners are only weakly ... See full document

... wavelengths. Regression models are a versatile tool for data analysis and various models have been proposed for regression with functional variables; see Morris (2015) and Greven and Scheipl (2017) ... See full document

... specific choice for model ...with Bayesian model averaging, where these hyperparameters take on a fixed value a priori, however, additional indicator variables are introduced into the ... See full document

... the regression model have an influence on the response ...the regression model we have to carefully choose the covariates entering the model from all available ...the regression ... See full document

... Generalized additive models (GAM) for modeling nonlinear effects of contin- uous covariates are now well established tools for the applied ...develop Bayesian GAM’s and extensions to generalized ... See full document

... F¨ ur die Anregung zu dieser Dissertation danke ich meinem Betreuer Prof. H.-D. Donder. Außerdem danke ich ihm f¨ ur all die Unterst¨ utzung, die er mir gew¨ ahrt hat. Prof. W. H. Woodin danke ich f¨ ur die ... See full document

... apply it. Due to the restrictions imposed on the definite/goal formulas and to the fact that we need to limit ourselves to NA ω , special care had to be taken with respect to negations. This concerns on the one hand the ... See full document

... Position und Referenz-Position kann die Kalibrierung eines Positionierungssystems automatisiert angestoßen werden und so der ma- nuelle Aufwand minimiert ...schnell und effektiv ...sammeln und ... See full document

... Moderne Datenbankanwendungen werden vor allem durch zwei we- sentliche Aspekte charakterisiert. Dies ist zum einen die Verwen- dung komplexer Datentypen mit interner Struktur und zum anderen die Notwendigkeit ... See full document

... Risk measurement is a central component of the risk management process. It aims at quantifying the exposure towards different types of risk, such as market, credit, liquidity or operational risks. Typically, an ... See full document

... cluster model and applies the Independent Component Anal- ysis for determining the main directions inside a cluster as well as for finding split planes in a top-down clustering ... See full document

... As measure of the performance of the new method, martingale resid- uals were used. On this account, in every simulation cycle the basis functions found by the MARS approach were included as covariates in a Cox ... See full document

... waterfall model as disciplines that need to be carried out in all iterations of the project with different ...waterfall model (requirements, analysis and de- sign, implementation, test, deployment) in order ... See full document