Publications by Achim Zeileis

Spatial lag model trees

20.01.2019

Economic growth models are recursively partitioned to assess heterogeneity in growth and convergence across EU regions while adjusting for spatial dependencies. Accompanied by R package lagsarlmtree, combining partykit::mob and spdep::lagsarlm. Citation Martin Wagner, Achim Zeileis (2019). “Heterogeneity and Spatial Dependence of Regional Growt...

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Online color apps at hclwizard.org

14.02.2019

The hclwizard.org web page has been relaunched, hosting three online color apps based on the HCL (Hue-Chroma-Luminance) color model: a palette constructor, a color vision deficiency emulator, and a color picker. HCL wizard: Somewhere over the rainbow The web page http://hclwizard.org/ had originally been started to accompany the manuscript: “So...

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At the end of the rainbow

06.03.2019

Fully saturated RGB rainbow colors are still widely used in scientific visualizations despite their widely-recognized disadvantages. A recent wild-caught example is presented, showing its limitations along with a better HCL-based alternative palette. #endrainbow The go-to palette in many software packages is – or used to be until rather recentl...

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Personalized treatment effects with model4you

15.05.2019

Personalized treatment effects can be estimated easily with model-based trees and model-based random forests using the R package model4you. Citation Heidi Seibold, Achim Zeileis, Torsten Hothorn (2019). “model4you: An R Package for Personalised Treatment Effect Estimation.” Journal of Open Research Software, 7(17), 1-6. doi:10.5334/jors.219 A...

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Hybrid Machine Learning Forecasts for the 2019 FIFA Women’s World Cup

04.06.2019

Using a random forest ensemble learner we obtain probabilistic forecasts for the FIFA Women’s World Cup in France: The clear favorite is defending champion USA followed, with some margin, by host France, England, and Germany. The 2019 FIFA Women’s World Cup will take place in France from 7 June to 7 July 2019. 24 of the best teams from 6 c...

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The power of unbiased recursive partitioning

30.06.2019

The significance tests underlying the unbiased tree algorithms CTree, MOB, and GUIDE are embedded into a unifying framework. This allows to assess relative strengths and weaknesses in a variety of setups, highlighting the advantages of score-based tests (as in CTree/MOB) vs. residual-based tests (as in GUIDE). Citation Schlosser L, Hothorn T, Ze...

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The power of unbiased recursive partitioning

30.06.2019

The significance tests underlying the unbiased tree algorithms CTree, MOB, and GUIDE are embedded into a unifying framework. This allows to assess relative strengths and weaknesses in a variety of setups, highlighting the advantages of score-based tests (as in CTree/MOB) vs. residual-based tests (as in GUIDE). Citation Schlosser L, Hothorn T, Ze...

9593 sym 4 img 2 tbl

The power of unbiased recursive partitioning

30.06.2019

The significance tests underlying the unbiased tree algorithms CTree, MOB, and GUIDE are embedded into a unifying framework. This allows to assess relative strengths and weaknesses in a variety of setups, highlighting the advantages of score-based tests (as in CTree/MOB) vs. residual-based tests (as in GUIDE). Citation Schlosser L, Hothorn T, Ze...

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Network model trees

30.07.2019

The effect of covariates on correlations in psychometric networks is assessed with either model-based recursive partitioning (MOB) or conditional inference trees (CTree). Citation Jones PJ, Mair P, Simon T, Zeileis A (2019). “Network Model Trees”, OSF ha4cw, OSF Preprints. doi:10.31219/osf.io/ha4cw Abstract In many areas of psychology, correl...

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Network model trees

30.07.2019

The effect of covariates on correlations in psychometric networks is assessed with either model-based recursive partitioning (MOB) or conditional inference trees (CTree). Citation Jones PJ, Mair P, Simon T, Zeileis A (2019). “Network Model Trees”, OSF ha4cw, OSF Preprints. doi:10.31219/osf.io/ha4cw Abstract In many areas of psychology, correl...

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