In regression models for ordinal response, each covariate can be equipped with either a simple, global effect or a more flexible and complex effect which is specific to the response categories. Instead of a priori assuming one of these effect

A General Framework for the Selection of Effect Type in Ordinal Regression 1/2

Jan 18th, 2016

Identifiability in penalized function-on-function regression models

Jan 1st, 2016

Regression models with functional responses and covariates constitute a powerful and increasingly important model class. However, regression with functional data poses well known and challenging problems of non-identifiability. This non-identi

Identifiability in penalized function-on-function regression models

Jun 11th, 2015

Regression models with functional covariates for functional responses constitute a powerfuland increasingly important model class. However, regression with functional data poses challenging problems of non-identifiability. We describe these

What can the Real World do for simulation studies? A comparison of exploratory methods

Apr 14th, 2015

For simulation studies on the exploratory factor analysis (EFA), usually rather simple population models are used without model errors. In the present study, real data characteristics are used for Monte Carlo simulation studies. Real large data

Evaluation of a new k-means approach for exploratory clustering of items

Apr 14th, 2015

Evaluation of a new k-means approach for exploratory clustering of items

Sensitivity Analyses for Informative Censoring in Time-to-Event Clinical Trials

Jan 1st, 2015

Analysis of Network DataA Statistical Analysis of the International Arms Trade Network from 1950-2013

Jan 1st, 2015

Expektile Regression

Jan 1st, 2015

Simulationsstudie zum Gütevergleich ausgewählter Hypothesentests unter potentiell problematischen Datensituationen-Betrachtung von Wilcoxon-Vorzeichen-Rang-, Vorzeichen- und t-Test im Einstichprobenfall

Jan 1st, 2015

Cronbachs α im Kontext des Grundmodells der klassischen Testtheorie und darüber hinaus

Jan 1st, 2015

Beeinflussen Interviewereffekte die Einkommensangabe in Befragungen?Eine Analyse mithilfe administrativer Daten

Jan 1st, 2015

Vergleich verschiedener Verfahren zur Datenimputation

Jan 1st, 2015

Decision making under partial information using precise and imprecise probabilistic models

Jan 1st, 2015

Benfordabweichung - ein geeignetes statistisches Mittel um unvollkommenen Wettbewerb amwestaustralischen Benzinmarkt nachzuweisen?

Jan 1st, 2015

Investigations on MCP-Mod Designs

Jan 1st, 2015

Imputation of missing data via penalization techniques

Jan 1st, 2015

Benchmarking of Classical and Machine-Learning Algorithms (with special emphasis on Bagging and Boosting Approaches) for Time Series Forecasting

Jan 1st, 2015

Räumliche Modelle (Spatial Models)

Jan 1st, 2015

Estimating individual treatment effects fromresponses and a predictive biomarker in aparallel group RCT

Dec 24th, 2014

When being interested in administering the best of two treatments to an individualpatient i, it is necessary to know the individual treatment effects (ITEs) of theconsidered subjects and the correlation between the possible responses (PRs) fo

Minimization and estimation of the variance of prediction errors for cross-validation designs 2/2

Nov 1st, 2014

We consider the mean prediction error of a classification or regression procedure as well as its cross-validation estimates, and investigate the variance of this estimate as a function of an arbitrary cross-validation design. We decompose this

A variance decomposition and a Central Limit Theorem for empirical losses associated with resampling designs

Nov 1st, 2014

The mean prediction error of a classification or regression procedure can be estimated using resampling designs such as the cross-validation design. We decompose the variance of such an estimator associated with an arbitrary resampling procedur

Minimization and estimation of the variance of prediction errors for cross-validation designs 1/2

Nov 1st, 2014

Possibilities and Limitations of Spatially Explicit Site Index Modelling for Spruce Based on National Forest Inventory Data and Digital Maps of Soil and Climate in Bavaria (SE Germany)

Nov 1st, 2014

Combining national forest inventory (NFI) data with digital site maps of high resolution enables spatially explicit predictions of site productivity. The aim of this study is to explore the possibilities and limitations of this database to anal

Modeling Clustered Heterogeneity: Fixed Effects, Random Effects and Mixtures

Oct 30th, 2014

Although each statistical unit on which measurements are taken is unique, typically there is not enough information available to account totally for its uniqueness. Therefore heterogeneity among units has to be limited by structural assumptions