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Mathematics

D-Index
48
Citations
12167
World Ranking
1191
National Ranking
62

Overview

Thomas Kneib is a researcher affiliated with the University of Göttingen in Germany. The primary field of study is Mathematics, with a focus on Statistics and Probability as a major subfield. Their work extends into related subfields such as Economics and Econometrics, Artificial Intelligence, Management Science and Operations Research, and Environmental Engineering.

The main research topics covered by their publications include:

  • Statistical Methods and Inference
  • Statistical Methods and Bayesian Inference
  • Spatial and Panel Data Analysis
  • Bayesian Methods and Mixture Models
  • Economic and Environmental Valuation
  • Advanced Statistical Methods and Models
  • Health Systems, Economic Evaluations, Quality of Life

Thomas Kneib has authored a number of influential papers, which include:

  • Rage Against the Mean - A Review of Distributional Regression Approaches (2021, Econometrics and Statistics)

While Kneib is the sole author listed on the paper above, their frequent coauthors include:

  • Nadja Klein
  • Benjamin Säfken
  • Christoph Weisser
  • Paul Wiemann
  • Anton Thielmann

Their research outputs have been published in various venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Statistical Modelling
  • SSRN Electronic Journal
  • Statistics and Computing
  • Biometrical Journal

Thomas Kneib has contributed to book literature as well. A recent publication is:

  • Generalized Additive Models for Location, Scale and Shape (2024, Cambridge University Press)

Best Publications

  • Conditional variable importance for random forests

    Carolin Strobl;Anne Laure Boulesteix;Thomas Kneib;Thomas Augustin

  • Regression: Models, Methods and Applications

    Ludwig Fahrmeir;Thomas Kneib;Stefan Lang;Brian Marx

  • PENALIZED STRUCTURED ADDITIVE REGRESSION FOR SPACE-TIME DATA: A BAYESIAN PERSPECTIVE

    Ludwig Fahrmeir;Thomas Kneib;Stefan Lang

  • On the behaviour of marginal and conditional AIC in linear mixed models

    Sonja Greven;Thomas Kneib

  • BayesX: analysing Bayesian structured additive regression models

    Andreas Brezger;Thomas Kneib;Stefan Lang

  • Generalized additive models for location, scale and shape for high dimensional data—a flexible approach based on boosting

    Andreas Mayr;Nora Fenske;Benjamin Hofner;Thomas Kneib

  • Regression - Modelle, Methoden und Anwendungen

    Ludwig Fahrmeir;Thomas Kneib;Stefan Lang

  • Identifying Risk Factors for Severe Childhood Malnutrition by Boosting Additive Quantile Regression

    Nora Fenske;Thomas Kneib;Torsten Hothorn

  • Model-based Boosting 2.0

    Torsten Hothorn;Peter Bühlmann;Thomas Kneib;Matthias Schmid

  • Beyond mean regression

    Thomas Kneib

  • Bayesian Generalized Additive Models for Location, Scale, and Shape for Zero-Inflated and Overdispersed Count Data

    Nadja Klein;Thomas Kneib;Stefan Lang

  • Variable Selection and Model Choice in Geoadditive Regression Models

    Thomas Kneib;Torsten Hothorn;Gerhard Tutz

  • Expectile and quantile regression—David and Goliath?

    Linda Schulze Waltrup;Fabian Sobotka;Thomas Kneib;Göran Kauermann

  • Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

    Ludwig Fahrmeir;Thomas Kneib

  • Geoadditive expectile regression

    Fabian Sobotka;Thomas Kneib

  • Bayesian structured additive distributional regression with an application to regional income inequality in Germany

    Nadja Klein;Thomas Kneib;Stefan Lang;Alexander Sohn

  • Structured Additive Regression Models: An R Interface to BayesX

    Nikolaus Umlauf;Daniel Adler;Thomas Kneib;Stefan Lang

  • A Mixed Model Approach for Geoadditive Hazard Regression

    Thomas Kneib;Ludwig Fahrmeir

  • Spike-and-Slab Priors for Function Selection in Structured Additive Regression Models

    Fabian Scheipl;Ludwig Fahrmeir;Thomas Kneib

  • Structured additive regression for categorical space-time data: a mixed model approach.

    Thomas Kneib;Ludwig Fahrmeir

  • Simultaneous Confidence Bands for Penalized Spline Estimators

    Tatyana Krivobokova;Thomas Kneib;Gerda Claeskens

Frequent Co-Authors

Ludwig Fahrmeir
Ludwig Fahrmeir Ludwig-Maximilians-Universität München
Stefan Lang
Stefan Lang University of Innsbruck
Gerhard Tutz
Gerhard Tutz Ludwig-Maximilians-Universität München
Johannes Kornhuber
Johannes Kornhuber University of Göttingen
Stephan Klasen
Stephan Klasen University of Göttingen
Achim Zeileis
Achim Zeileis University of Innsbruck
Christopher I. Amos
Christopher I. Amos Baylor College of Medicine
Robert Perneczky
Robert Perneczky Ludwig-Maximilians-Universität München
Ingo Grass
Ingo Grass University of Hohenheim

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