A nonparametric test for similarity of marginals -- with applications to the assessment of population bioequivalence
From MaRDI portal
Publication:866613
DOI10.1016/j.jspi.2006.06.003zbMath1111.62042OpenAlexW2127510889MaRDI QIDQ866613
Axel Munk, Claudia Czado, Gudrun Freitag
Publication date: 14 February 2007
Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jspi.2006.06.003
bioequivalencecross-over trialsHadamard derivativelimit lawmultivariate empirical processpre--post comparison
Nonparametric hypothesis testing (62G10) Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric statistical resampling methods (62G09)
Related Items
Minimax confidence intervals for the sliced Wasserstein distance, Limit laws of the empirical Wasserstein distance: Gaussian distributions, A central limit theorem for Wasserstein type distances between two distinct univariate distributions, The limit distribution of weighted \(L^2\)-goodness-of-fit statistics under fixed alternatives, with applications, Two-sample goodness-of-fit tests on the flat torus based on Wasserstein distance and their relevance to structural biology, Inference for Empirical Wasserstein Distances on Finite Spaces, Cramér-von Mises and characteristic function tests for the two and \(k\)-sample problems with dependent data, Tests for multivariate normality -- a critical review with emphasis on weighted $L^2$-statistics, Interpoint distance based two sample tests in high dimension, Equivalence tests for multinomial data based on \(\phi\)-divergences, Cramér–von Mises distance: probabilistic interpretation, confidence intervals, and neighbourhood-of-model validation
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- A characterization of random variables with minimum \(L^ 2\)-distance
- A class of asymptotically distribution-free tests for equality of marginals in multivariate populations
- Tests of goodness of fit based on the \(L_2\)-Wasserstein distance
- Contributions of empirical and quantile processes to the asymptotic theory of goodness-of-fit tests. (With comments)
- Bioequivalence trials, intersection-union tests and equivalence confidence sets. With comments and a rejoinder by the authors
- Central limit theorems for the Wasserstein distance between the empirical and the true distributions
- Weak convergence and empirical processes. With applications to statistics
- Bootstrap methods for the nonparametric assessment of population bioequivalence and similarity of distributions
- Exact Inference About the Within-Subject Variability in 2 × 2 Crossover Trials
- A note on Welch's approximate t-solution to bioequivalence assessment
- Nonparametric Validation of Similar Distributions and Assessment of Goodness of Fit
- Discussion of individual bioequivalence by M.-L. chen
- Moment-based criteria for determining bioequivalence
- Equivalence and Interval Testing for Lehmann's Alternative
- Optimal Unbiased Tests for Equivalence in Intrasubject Variability
- Consistency of the bootstrap procedure in individual bioequivalence
- A Class of Asymptotically Distribution-Free Test Procedures for Equality of Marginals Under Multivariate Dependence
- A New Approach to Equivalence Assessment in Standard Comparative Bioavailability Trials by Means of the Mann‐Whitney Statistic
- Assessment of Individual and Population Bioequivalence Using the Probability That Bioavailabilities are Similar
- Testing Equivalence Simultaneously for Location and Dispersion of two Normally Distributed Populations
- A Note on Asymptotic Joint Normality
- Prescribing a System of Random Variables by Conditional Distributions
- Convergence Criteria for Multiparameter Stochastic Processes and Some Applications
- Modified Large-Sample Confidence Intervals for Linear Combinations of Variance Components
- Bootstrapping rank statistics.