Tag: regression

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 ›

Personalized treatment effects with model4you

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Personalized treatment effects can be estimated easily with model-based trees and model-based random forests using the R package model4you. Read more ›

Spatial lag model trees

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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. Read more ›

Minimum CRPS vs. maximum likelihood

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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 specification. An R implementation is available in the crch package. Read more ›

Partially additive (generalized) linear model trees

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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. Read more ›

Thunderstorm forecasting with GAMs

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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. Read more ›

MPT trees published in BRM

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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. Read more ›

Clustered Covariances in sandwich 2.5-0

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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. Read more ›

Distributional regression forests on arXiv

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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. Read more ›