M
Martin Mächler
Researcher at ETH Zurich
Publications - 27
Citations - 71291
Martin Mächler is an academic researcher from ETH Zurich. The author has contributed to research in topics: Graphics & Generalized linear mixed model. The author has an hindex of 15, co-authored 27 publications receiving 42993 citations. Previous affiliations of Martin Mächler include École Polytechnique Fédérale de Lausanne.
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Fitting Linear Mixed-Effects Models Using lme4
TL;DR: In this article, a model is described in an lmer call by a formula, in this case including both fixed-and random-effects terms, and the formula and data together determine a numerical representation of the model from which the profiled deviance or the profeatured REML criterion can be evaluated as a function of some of model parameters.
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Fitting Linear Mixed-Effects Models using lme4
TL;DR: In this article, a model is described in an lmer call by a formula, in this case including both fixed-and random-effects terms, and the formula and data together determine a numerical representation of the model from which the profiled deviance or the profeatured REML criterion can be evaluated as a function of some of model parameters.
Journal ArticleDOI
glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling
Mollie Elizabeth Brooks,Kasper Kristensen,Koen J. van Benthem,Arni Magnusson,Casper Willestofte Berg,Anders Nielsen,Hans J. Skaug,Martin Mächler,Benjamin M. Bolker +8 more
TL;DR: The glmmTMB package fits many types of GLMMs and extensions, including models with continuously distributed responses, but here the authors focus on count responses and its ability to estimate the Conway-Maxwell-Poisson distribution parameterized by the mean is unique.
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Causal Inference using Graphical Models with the R Package pcalg
TL;DR: The pcalg package for R can be used for the following two purposes: Causal structure learning and estimation of causal effects from observational data.
Journal ArticleDOI
scatterplot3d - An R Package for Visualizing Multivariate Data
Uwe Ligges,Martin Mächler +1 more
TL;DR: Scatterplot3d as discussed by the authors is an R package for the visualization of multivariate data in a 3D space, which is designed by exclusively making use of already existing functions of R and its graphics system.