Article
Open Access
Fully Nonparametric Methods for Multivariate Data in Factorial Designs. Asymptotics, Finite Sample Approximations, and Implementation in R
-
Maximilian Kiefel
and
Arne C. Bathke
Published/Copyright:
December 31, 2022
Received: 2022-02-16
Accepted: 2022-11-23
Published Online: 2022-12-31
Published in Print: 2022-01-01
© 2022 Maximilian Kiefel et al., published by De Gruyter
Articles in the same Issue
- Efficient Generalized Ridge Regression
- Clustered Autoencoded Variational Inverse Reinforcement Learning
- Initial data analysis: A new technology not yet ready to use
- On the boundary properties of Bernstein estimators on the simplex
- Fully Nonparametric Methods for Multivariate Data in Factorial Designs. Asymptotics, Finite Sample Approximations, and Implementation in R
Keywords for this article
Factorial designs;
Finite samples;
MANOVA;
Nonparametric model;
Nonnormality;
Rank statistics
Creative Commons
BY-NC-ND 3.0
Articles in the same Issue
- Efficient Generalized Ridge Regression
- Clustered Autoencoded Variational Inverse Reinforcement Learning
- Initial data analysis: A new technology not yet ready to use
- On the boundary properties of Bernstein estimators on the simplex
- Fully Nonparametric Methods for Multivariate Data in Factorial Designs. Asymptotics, Finite Sample Approximations, and Implementation in R
