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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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Scatterplot3d - an R package for visualizing multivariate data

TL;DR: Scatterplot3d is an R package for the visualization of multivariate data in a three dimensional space designed by exclusively making use of already existing functions of R and its graphics system and thus shows the extensibility of the R graphics system.
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Emacs Speaks Statistics: A Multiplatform, Multipackage Development Environment for Statistical Analysis

TL;DR: Essex Speaks Statistics (ESS) provides an intelligent and consistent interface between the user and statistics software that understands the syntax for numerous data analysis languages, provides consistent display and editing features across packages, and assists in the interactive or batch execution of statements by statistics packages.

Archimedean Copulas in High Dimensions: Estimators and Numerical Challenges Motivated by Financial Applications Titre: Implémentations stables et estimateurs de copules Archimédiennes en grandes dimensions pour les applications financières

TL;DR: In this paper, the performance of known and new parametric estimators for the parameters of Archimedean copulas is investigated and related numerical difficulties are addressed, in particular, method-of-moments-like estimators based on pairwise Kendall's tau, a multivariate extension of Blomqvist's beta, minimum distance estimators, the maximum likelihood estimator, a simulated maximum-likelihood estimator and a maximum likelihood estimation based on the copula diagonal.

Archimedean Copulas in High Dimensions: Estimators and Numerical Challenges Motivated by Financial Applications

TL;DR: The performance of known and new parametric estimators for the parameters of Archimedean copulas is investigated and related numerical difficulties are addressed and the numerical solutions developed extend to various asymmetric generalizations and important quantities such as distributions of radial parts or the Kendall distribution function.
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Variational solution of penalized likelihood problems and smooth curve estimation

TL;DR: In this article, the authors proposed a smoothed version of the maximum penalized likelihood (MPL) estimator with a novel roughness penalty, which penalizes a relative change of curvature.