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
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Working Papers
2025
- Inference for the proportional odds cumulative logit model with monotonicity constraints for ordinal predictors and ordinal response
Papers, arXiv.org
Journal Articles
2024
- Parameters not empirically identifiable or distinguishable, including correlation between Gaussian observations
Statistical Papers, 2024, 65, (2), 771-794
2023
- Clustering of football players based on performance data and aggregated clustering validity indexes
Journal of Quantitative Analysis in Sports, 2023, 19, (2), 103-123
2022
- An empirical comparison and characterisation of nine popular clustering methods
Advances in Data Analysis and Classification, 2022, 16, (1), 201-229 View citations (1)
- 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
- 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
- Clustering with the Average Silhouette Width
Computational Statistics & Data Analysis, 2021, 158, (C) View citations (6)
2019
- 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)
- Multiple Perspectives on Inference for Two Simple Statistical Scenarios
The American Statistician, 2019, 73, (S1), 328-339 View citations (4)
2018
- 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
- Beyond subjective and objective in statistics
Journal of the Royal Statistical Society Series A, 2017, 180, (4), 967-1033 View citations (18)
2016
- Quantile-based classifiers
Biometrika, 2016, 103, (2), 435-446 View citations (2)
- 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
- 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
- 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
- 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
- A smoothing principle for the Huber and other location M-estimators
Computational Statistics & Data Analysis, 2011, 55, (1), 324-337 View citations (3)
2010
- 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)
- Methods for merging Gaussian mixture components
Advances in Data Analysis and Classification, 2010, 4, (1), 3-34 View citations (39)
2008
- 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
- Cluster-wise assessment of cluster stability
Computational Statistics & Data Analysis, 2007, 52, (1), 258-271 View citations (35)
2004
- Distance-based parametric bootstrap tests for clustering of species ranges
Computational Statistics & Data Analysis, 2004, 45, (4), 875-895 View citations (2)
2003
- Clusters, outliers, and regression: fixed point clusters
Journal of Multivariate Analysis, 2003, 86, (1), 183-212 View citations (9)
2002
- Validating visual clusters in large datasets: fixed point clusters of spectral features
Computational Statistics & Data Analysis, 2002, 40, (4), 723-739 View citations (6)
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