Details about Christian Hennig

Access statistics for papers by Christian Hennig.

Last updated 2025-04-08. Update your information in the RePEc Author Service.

Short-id: phe840

Working Papers

2025

1. Inference for the proportional odds cumulative logit model with monotonicity constraints for ordinal predictors and ordinal response
   Papers, arXiv.org

Journal Articles

2024

1. Parameters not empirically identifiable or distinguishable, including correlation between Gaussian observations
   Statistical Papers, 2024, 65, (2), 771-794

2023

2. Clustering of football players based on performance data and aggregated clustering validity indexes
   Journal of Quantitative Analysis in Sports, 2023, 19, (2), 103-123 View citations (1)

2022

3. An empirical comparison and characterisation of nine popular clustering methods
   Advances in Data Analysis and Classification, 2022, 16, (1), 201-229 View citations (1)
4. Christian Hennig's contribution to the Discussion of ‘Assumption‐lean inference for generalised linear model parameters’ by Vansteelandt and Dukes
   Journal of the Royal Statistical Society Series B, 2022, 84, (3), 698-699

2021

5. Christian Hennig’s contribution to the Discussion of ‘Testing by betting: A strategy for statistical and scientific communication’ by Glenn Shafer
   Journal of the Royal Statistical Society Series A, 2021, 184, (2), 446-447
6. Clustering with the Average Silhouette Width
   Computational Statistics & Data Analysis, 2021, 158, (C) View citations (6)

2019

7. Exploration of the variability of variable selection based on distances between bootstrap sample results
   Advances in Data Analysis and Classification, 2019, 13, (4), 933-963 View citations (3)
8. Multiple Perspectives on Inference for Two Simple Statistical Scenarios
   The American Statistician, 2019, 73, (S1), 328-339 View citations (4)

2018

9. Using clustering of rankings to explain brand preferences with personality and socio-demographic variables
   Journal of Applied Statistics, 2018, 45, (6), 1009-1029 View citations (4)

2017

10. Beyond subjective and objective in statistics
    Journal of the Royal Statistical Society Series A, 2017, 180, (4), 967-1033 View citations (18)

2016

11. Quantile-based classifiers
    Biometrika, 2016, 103, (2), 435-446 View citations (2)
12. Robust Improper Maximum Likelihood: Tuning, Computation, and a Comparison With Other Methods for Robust Gaussian Clustering
    Journal of the American Statistical Association, 2016, 111, (516), 1648-1659 View citations (14)

2015

13. Effect of web page menu orientation on retrieving information by people with learning disabilities
    Journal of the Association for Information Science & Technology, 2015, 66, (4), 674-683

2013

14. Discussion of “Model-based clustering with non-normal mixture distributions” by S. X. Lee and G. J. McLachlan
    Statistical Methods & Applications, 2013, 22, (4), 455-458
15. How to find an appropriate clustering for mixed-type variables with application to socio-economic stratification
    Journal of the Royal Statistical Society Series C, 2013, 62, (3), 309-369 View citations (38)

2011

16. A smoothing principle for the Huber and other location M-estimators
    Computational Statistics & Data Analysis, 2011, 55, (1), 324-337 View citations (3)

2010

17. A simulation study to compare robust clustering methods based on mixtures
    Advances in Data Analysis and Classification, 2010, 4, (2), 111-135 View citations (9)
18. Methods for merging Gaussian mixture components
    Advances in Data Analysis and Classification, 2010, 4, (1), 3-34 View citations (39)

2008

19. Dissolution point and isolation robustness: Robustness criteria for general cluster analysis methods
    Journal of Multivariate Analysis, 2008, 99, (6), 1154-1176 View citations (11)

2007

20. Cluster-wise assessment of cluster stability
    Computational Statistics & Data Analysis, 2007, 52, (1), 258-271 View citations (35)

2004

21. Distance-based parametric bootstrap tests for clustering of species ranges
    Computational Statistics & Data Analysis, 2004, 45, (4), 875-895 View citations (2)

2003

22. Clusters, outliers, and regression: fixed point clusters
    Journal of Multivariate Analysis, 2003, 86, (1), 183-212 View citations (9)

2002

23. Validating visual clusters in large datasets: fixed point clusters of spectral features
    Computational Statistics & Data Analysis, 2002, 40, (4), 723-739 View citations (6)