Publications by Achim Zeileis
Distributional regression forests on arXiv
Distributional regression trees and forests provide flexible data-driven probabilistic forecasts by blending distributional models (for location, scale, shape, and beyond) with regression trees and random forests. Accompanied by the R package disttree. Citation Lisa Schlosser, Torsten Hothorn, Reto Stauffer, Achim Zeileis (2018). “Distributiona...
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Probabilistic Forecasting for the 2018 FIFA World Cup
Using a consensus model based on quoted bookmakers’ odds winning probabilities for all competing teams in the FIFA World Cup are obtained: The favorite is Brazil, closely followed by the defending World Champion Germany. Football fans worldwide anticipate the 2018 FIFA World Cup that will take place in Russia from 14 June to 15 July 2018. 32...
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Sankey Diagram for the 2018 FIFA World Cup Forecast
The probabilistic forecast from the bookmaker consensus model for the 2018 FIFA World Cup is visualized in an interactive Sankey diagram, highlighting the teams’ most likely progress through the tournament. Bookmaker consensus model Two weeks ago we published our Probabilistic Forecast for the 2018 FIFA World Cup: By adjusting quoted bookmakers...
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Evaluation of the 2018 FIFA World Cup Forecast
A look back the 2018 FIFA World Cup in Russia to check whether our tournament forecast based on the bookmaker consensus model was any good… How surprising was the tournament? Last week France won the 2018 FIFA World Cup in a match against Croatia in Russia, thus delivering an entertaining final to a sportful tournament. Many perceived the cours...
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Clustered Covariances in sandwich 2.5-0
Version 2.5-0 of the R package ‘sandwich’ is available from CRAN now with enhanced object-oriented clustered covariances (for lm, glm, survreg, polr, hurdle, zeroinfl, betareg, …). The software and corresponding vignette have been improved considerably based on helpful and constructive reviewer feedback as well as various bug reports. Enhan...
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MPT trees published in BRM
Multinomial processing trees are recursively partitioned to capture heterogeneity in latent cognitive processing steps. Accompanied by the R function mpttree in the psychotree package, combining partykit::mob and psychotools::mpt. Citation Florian Wickelmaier, Achim Zeileis (2018). “Using Recursive Partitioning to Account for Parameter Heteroge...
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Thunderstorm forecasting with GAMs
Boosted binary generalized additive models (GAMs) with stability selection and corresponding MCMC-based credibility intervals are discussed in a new MWR paper as a probabilistic forecasting method for the occurrence of thunderstorms. Citation Thorsten Simon, Peter Fabsic, Georg J. Mayr, Nikolaus Umlauf, Achim Zeileis (2018). “Probabilistic Fore...
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Partially additive (generalized) linear model trees
The PALM tree algorithm for partially additive (generalized) linear model trees is introduced along with the R package palmtree. One potential application is modeling of treatment-subgroup interactions while adjusting for global additive effects. Citation Heidi Seibold, Torsten Hothorn, Achim Zeileis (2018). “Generalised Linear Model Trees with...
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Minimum CRPS vs. maximum likelihood
In a new paper in Monthly Weather Review, minimum CRPS and maximum likelihood estimation are compared for fitting heteroscedastic (or nonhomogenous) regression models under different response distributions. Minimum CRPS is more robust to distributional misspecification while maximum likelihood is slightly more efficient under correct specificatio...
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colorspace: New Tools for Colors and Palettes
A major update (version 1.4.0) of the R package colorspace has been released to CRAN, enhancing many of the package’s capabilities, e.g., more refined palettes, named palettes, ggplot2 color scales, visualizations for assessing palettes, shiny and Tcl/Tk apps, color vision deficiency emulation, and much more. Overview The colorspace package pro...
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