activity
20132026
most citedGlobal envelope tests for spatial processes

221 citations · 327 across the 15 of their papers we have counts for

collaborators

16 papers

stat.ME2026

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…

stat.ME2026

Mark distance correlation functions: from moment-based to distributional mark summary characteristics in spatial point processes

Matthias Eckardt, Mari Myllymäki, Aila Särkkä

With the rapid advancement in data collection devices and storage capacities, we have access to increasing amount of spatial point pattern data where each event location is augment…

stat.ME2024★ 2 cited

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…

stat.ME2023★ 1 cited

What you see is not what is there: Mechanisms, models, and methods for point pattern deviations

Peter Guttorp, Janine Illian, Joel Kostensalo +4

Many natural systems are observed as point patterns in time, space, or space and time. Examples include plant and cellular systems, animal colonies, earthquakes, and wildfires. In…

stat.ME2023

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…

math.ST2023★ 1 cited

Spatio-temporal determinantal point processes

Nafiseh Vafaei, Mohammad Ghorbani, Masoud Ganji +1

Determinantal point processes are models for regular spatial point patterns, with appealing probabilistic properties. We present their spatio-temporal counterparts and give example…

stat.ME2020★ 1 cited

Testing the first-order separability hypothesis for spatio-temporal point patterns

Mohammad Ghorbani, Nafiseh Vafaei, Jiří Dvořák +1

First-order separability of a spatio-temporal point process plays a fundamental role in the analysis of spatio-temporal point pattern data. While it is often a convenient assumptio…

stat.ME2020★ 10 cited

False discovery rate envelopes

Tomáš Mrkvička, Mari Myllymäki

False discovery rate (FDR) is a common way to control the number of false discoveries in multiple testing. There are a number of approaches available for controlling FDR. However,…

stat.ME2020★ 7 cited

Point process models for sweat gland activation observed with noise

Mikko Kuronen, Mari Myllymäki, Adam Loavenbruck +1

The aim of the paper is to construct spatial models for the activation of sweat glands for healthy subjects and subjects suffering from peripheral neuropathy by using videos of swe…

stat.ME2020★ 1 cited

Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests

Mikko Kuronen, Aila Särkkä, Matti Vihola +1

We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to invest…

stat.ME2019★ 7 cited

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…

stat.ME2019★ 19 cited

New methods for multiple testing in permutation inference for the general linear model

Tomas Mrkvicka, Mari Myllymaki, Mikko Kuronen +1

Permutation methods are commonly used to test significance of regressors of interest in general linear models (GLMs) for functional (image) data sets, in particular for neuroimagin…

stat.AP2018★ 1 cited

Spatial analysis of airborne laser scanning point clouds for predicting forest variables

Henrike Häbel, András Balázs, Mari Myllymäki

With recent developments in remote sensing technologies, plot-level forest resources can be predicted utilizing airborne laser scanning (ALS). The prediction is often assisted by m…

stat.ME2016★ 27 cited

A one-way ANOVA test for functional data with graphical interpretation

Tomas Mrkvicka, Mari Myllymaki, Milan Jilek +1

A new functional ANOVA test, with a graphical interpretation of the result, is presented. The test is an extension of the global envelope test introduced by Myllymaki et al. (2017,…

stat.ME2013★ 221 cited

Global envelope tests for spatial processes

Mari Myllymäki, Tomás Mrkvicka, Pavel Grabarnik +2

Envelope tests are a popular tool in spatial statistics, where they are used in goodness-of-fit testing. These tests graphically compare an empirical function with its simul…

stat.ME2013★ 29 cited

Deviation test construction and power comparison for marked spatial point patterns

Mari Myllymäki, Pavel Grabarnik, Henri Seijo +1

The deviation test belong to core tools in point process statistics, where hypotheses are typically tested considering differences between an empirical summary function and its exp…