activity
20172021
most citedHypothesis tests for structured rank correlation matrices

6 citations · 6 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ME2021

Causal Inference for Quantile Treatment Effects

Shuo Sun, Erica E. M. Moodie, Johanna G. Nešlehová

Analyses of environmental phenomena often are concerned with understanding unlikely events such as floods, heatwaves, droughts or high concentrations of pollutants. Yet the majorit…

math.ST2020

On attainability of Kendall's tau matrices and concordance signatures

Alexander J. McNeil, Johanna G. Neslehova, Andrew D. Smith

Methods are developed for checking and completing systems of bivariate and multivariate Kendall's tau concordance measures in applications where only partial information about depe…

stat.ME2020★ 6 cited

Hypothesis tests for structured rank correlation matrices

Samuel Perreault, Johanna Neslehova, Thierry Duchesne

Joint modeling of a large number of variables often requires dimension reduction strategies that lead to structural assumptions of the underlying correlation matrix, such as equal…

math.ST2017

Detection of Block-Exchangeable Structure in Large-Scale Correlation Matrices

Samuel Perreault, Thierry Duchesne, Johanna G. Nešlehová

Correlation matrices are omnipresent in multivariate data analysis. When the number d of variables is large, the sample estimates of correlation matrices are typically noisy and co…

math.ST2017

Extremal attractors of Liouville copulas

Léo R. Belzile, Johanna G. Nešlehová

Liouville copulas, which were introduced in McNeil and Neslehova (2010), are asymmetric generalizations of the ubiquitous Archimedean copula class. They are the dependence structur…