7 citations · 9 across the 4 of their papers we have counts for
5 papers
A Formal Graphical Inference Framework for Combining Effect Size with Statistical Significance: Application to Multivariate and Functional Linear Models
Tomáš Mrkvička, Mikko Kuronen, Mari Myllymäki
To address the critical need for statistical methods that evaluate practical magnitude alongside statistical significance, we introduce a formal graphical inference framework that…
The power of visualizing distributional differences: Formal graphical -sample tests
Konstantinos Konstantinou, Tomáš Mrkvička, Mari Myllymäki
Classical tests are available for the two-sample test of correspondence of distribution functions. From these, the Kolmogorov-Smirnov test provides also the graphical interpretatio…
Global quantile regression
Tomáš Mrkvička, Konstantinos Konstantinou, Mikko Kuronen +1
Quantile regression is used to study effects of covariates on a particular quantile of the data distribution. Here we are interested in the question whether a covariate has any eff…
Nonparametric testing of the covariate significance for spatial point patterns under the presence of nuisance covariates
Jiří Dvořák, Tomáš Mrkvička
Determining the relevant spatial covariates is one of the most important problems in the analysis of point patterns. Parametric methods may lead to incorrect conclusions, especiall…
GET: Global envelopes in R
Mari Myllymäki, Tomáš Mrkvička
This work describes the R package GET that implements global envelopes for a general set of -dimensional vectors in various applications. A % global envelope is a…