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Robust covariance matrix estimation: sandwich 3.0-0, web page, JSS paper

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Version 3.0-0 of the R package 'sandwich' for robust covariance matrix estimation (HC, HAC, clustered, panel, and bootstrap) is now available from CRAN, accompanied by a new web page and a paper in the Journal of Statistical Software (JSS). Read more ›

Structural equation model trees with partykit and lavaan

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To capture heterogeneity in structural equation models (SEMs), the model-based recursive partitioning (MOB) algorithm from partykit can be coupled with SEM estimation from lavaan. Read more ›

lmSubsets: Exact variable-subset selection in linear regression

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The R package lmSubsets for flexible and fast exact variable-subset selection is introduced and illustrated in a weather forecasting case study. Read more ›

Circular regression trees and forests

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A flexible framework for probabilistic forecasting of circular data is introduced, using distributional regression trees and random forests based on the von Mises distribution. Read more ›

bamlss: A Lego toolbox for flexible Bayesian regression

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Modular R tools for Bayesian regression are provided by bamlss: From classic MCMC-based GLMs and GAMs to distributional models using the lasso or gradient boosting. Read more ›

Was Trump confused by rainbow color map?

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In the controversy over Hurricane Dorian, US President Donald Trump repeatedly claimed that early forecasts showed a high probability of Alabama being hit. We demonstrate that a potentially confusing rainbow color map in the official weather forecasts may have attributed to Trump overestimating the risk. Read more ›

colorspace @ useR! 2019

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Conference presentation about the colorspace toolbox for manipulating and assessing color palettes at useR! 2019 in Toulouse: Slides, video, replication materials, and working paper. Read more ›

Network model trees

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The effect of covariates on correlations in psychometric networks is assessed with either model-based recursive partitioning (MOB) or conditional inference trees (CTree). Read more ›

The power of unbiased recursive partitioning

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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). Read more ›

Hybrid machine learning forecasts for the 2019 FIFA Women's World Cup

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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. Read more ›