Publications by Achim Zeileis

Circular regression trees and forests

19.02.2020

A flexible framework for probabilistic forecasting of circular data is introduced, using distributional regression trees and random forests based on the von Mises distribution. Citation Lang MN, Schlosser L, Hothorn T, Mayr GJ, Stauffer R, Zeileis A (2020). “Circular Regression Trees and Forests with an Application to Probabilistic Wind Directi...

5718 sym R (264 sym/1 pcs) 6 img

Circular regression trees and forests

19.02.2020

A flexible framework for probabilistic forecasting of circular data is introduced, using distributional regression trees and random forests based on the von Mises distribution. Citation Lang MN, Schlosser L, Hothorn T, Mayr GJ, Stauffer R, Zeileis A (2020). “Circular Regression Trees and Forests with an Application to Probabilistic Wind Directi...

5718 sym R (264 sym/1 pcs) 6 img

Circular regression trees and forests

19.02.2020

A flexible framework for probabilistic forecasting of circular data is introduced, using distributional regression trees and random forests based on the von Mises distribution. Citation Lang MN, Schlosser L, Hothorn T, Mayr GJ, Stauffer R, Zeileis A (2020). “Circular Regression Trees and Forests with an Application to Probabilistic Wind Directi...

5718 sym R (264 sym/1 pcs) 6 img

lmSubsets: Exact variable-subset selection in linear regression

28.04.2020

The R package lmSubsets for flexible and fast exact variable-subset selection is introduced and illustrated in a weather forecasting case study. Citation Hofmann M, Gatu C, Kontoghiorghes EJ, Colubi A, Zeileis A (2020). “lmSubsets: Exact Variable-Subset Selection in Linear Regression for R.” Journal of Statistical Software, 93(3), 1-21. doi:1...

5707 sym R (467 sym/4 pcs) 4 img 1 tbl

lmSubsets: Exact variable-subset selection in linear regression

28.04.2020

The R package lmSubsets for flexible and fast exact variable-subset selection is introduced and illustrated in a weather forecasting case study. Citation Hofmann M, Gatu C, Kontoghiorghes EJ, Colubi A, Zeileis A (2020). “lmSubsets: Exact Variable-Subset Selection in Linear Regression for R.” Journal of Statistical Software, 93(3), 1-21. doi:1...

5707 sym R (467 sym/4 pcs) 4 img 1 tbl

lmSubsets: Exact variable-subset selection in linear regression

28.04.2020

The R package lmSubsets for flexible and fast exact variable-subset selection is introduced and illustrated in a weather forecasting case study. Citation Hofmann M, Gatu C, Kontoghiorghes EJ, Colubi A, Zeileis A (2020). “lmSubsets: Exact Variable-Subset Selection in Linear Regression for R.” Journal of Statistical Software, 93(3), 1-21. doi:1...

5707 sym R (467 sym/4 pcs) 4 img 1 tbl

Structural equation model trees with partykit and lavaan

06.09.2020

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. Motivation Structural equation models (SEMs) are a popular class of models, especially in the social sciences, to model correlations and dependencies in multivariate da...

8729 sym R (3095 sym/8 pcs) 6 img

Structural equation model trees with partykit and lavaan

06.09.2020

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. Motivation Structural equation models (SEMs) are a popular class of models, especially in the social sciences, to model correlations and dependencies in multivariate da...

8729 sym R (3094 sym/8 pcs) 6 img

Structural equation model trees with partykit and lavaan

06.09.2020

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. Motivation Structural equation models (SEMs) are a popular class of models, especially in the social sciences, to model correlations and dependencies in multivariate da...

8729 sym R (3094 sym/8 pcs) 6 img

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

07.10.2020

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). CRAN release of version 3.0-0 The sandwich package provides model-robust covariance matrix estimators f...

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