Martin Mächler
ETH Zurich
37Publications
13H-index
19.6kCitations
Publications 37
Newest
Published on Jan 1, 2018
Marius Hofert13
Estimated H-index: 13
,
Ivan Kojadinovic21
Estimated H-index: 21
+ 1 AuthorsMartin Mächler13
Estimated H-index: 13
Source Cite
Published on Jan 1, 2017in R Journal 1.37
Mollie E. Brooks7
Estimated H-index: 7
(Technical University of Denmark),
Kasper Kristensen12
Estimated H-index: 12
(Technical University of Denmark)
+ 6 AuthorsBenjamin M. Bolker44
Estimated H-index: 44
(McMaster University)
Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inflated mixed models. The glmmTMB package fits many types of GLMMs and extensions, including models with continuously distributed responses, but here we...
44 Citations Source Cite
Published on May 1, 2017in bioRxiv
Mollie E. Brooks7
Estimated H-index: 7
(Technical University of Denmark),
Kasper Kristensen12
Estimated H-index: 12
(Technical University of Denmark)
+ 6 AuthorsBenjamin M. Bolker44
Estimated H-index: 44
(McMaster University)
Ecological phenomena are often measured in the form of count data. These data can be analyzed using generalized linear mixed models (GLMMs) when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the standard error distributions used in GLMMs, e.g., parasite counts may be exactly zero for hosts with effective immune defenses but vary according to a negative binomial distribution for non-r...
19 Citations Source Cite
Published on Feb 24, 2016in Journal of Statistical Software 22.74
Marius Hofert13
Estimated H-index: 13
,
Martin Mächler13
Estimated H-index: 13
It is shown how to set up, conduct, and analyze large simulation studies with the new R package simsalapar (= simulations simplified and launched parallel). A simulation study typically starts with determining a collection of input variables and their values on which the study depends. Computations are desired for all combinations of these variables. If conducting these computations sequentially is too time-consuming, parallel computing can be applied over all combinations of select variables. T...
2 Citations Source Cite
Published on Oct 7, 2015in Journal of Statistical Software 22.74
Douglas M. Bates26
Estimated H-index: 26
,
Martin Mächler13
Estimated H-index: 13
+ 1 AuthorsSteven C. Walker9
Estimated H-index: 9
Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evalua...
9,970 Citations Source Cite
Marius Hofert13
Estimated H-index: 13
(ETH Zurich),
Martin Mächler13
Estimated H-index: 13
(ETH Zurich)
This article introduces a graphical goodness-of-fit test for copulas in more than two dimensions. The test is based on pairs of variables and can thus be interpreted as a first-order approximation of the underlying dependence structure. The idea is to first transform pairs of data columns with the Rosenblatt transform to bivariate standard uniform distributions under the null hypothesis. This hypothesis can be graphically tested with a matrix of bivariate scatterplots, Q-Q plots, or other transf...
4 Citations Source Cite
Published on Jan 1, 2013in arXiv: Computation
Marius Hofert13
Estimated H-index: 13
,
Martin Mächler13
Estimated H-index: 13
(ETH Zurich),
Alexander J. McNeil22
Estimated H-index: 22
(Heriot-Watt University)
The performance of known and new parametric estimators for Archimedean copulas is investigated, with special focus on large dimensions and numerical diculties. 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 estimator based on the copula diagonal are studied. Their performance is compared ...
3 Citations
Published on Sep 1, 2012in Journal of Multivariate Analysis 1.01
Marius Hofert13
Estimated H-index: 13
(ETH Zurich),
Martin Mächler13
Estimated H-index: 13
(ETH Zurich),
Alexander J. McNeil22
Estimated H-index: 22
(Heriot-Watt University)
Explicit functional forms for the generator derivatives of well-known one-parameter Archimedean copulas are derived. These derivatives are essential for likelihood inference as they appear in the copula density, conditional distribution functions, and the Kendall distribution function. They are also required for several asymmetric extensions of Archimedean copulas such as Khoudraji-transformed Archimedean copulas. Availability of the generator derivatives in a form that permits fast and accurate...
72 Citations Source Cite
Published on May 17, 2012in Journal of Statistical Software 22.74
Markus Kalisch13
Estimated H-index: 13
,
Martin Mächler13
Estimated H-index: 13
+ 2 AuthorsPeter Bühlmann46
Estimated H-index: 46
The pcalg package for R can be used for the following two purposes: Causal structure learning and estimation of causal effects from observational data. In this document, we give a brief overview of the methodology, and demonstrate the package’s functionality in both toy examples and applications.
174 Citations Source Cite
Published on Jan 1, 2011in R Journal 1.37
Yohan Chalabi1
Estimated H-index: 1
,
Martin Mächler13
Estimated H-index: 13
,
Diethelm Würtz1
Estimated H-index: 1
The management of time and holidays can prove crucial in applications that rely on his- torical data. A typical example is the aggregation of a data set recorded in different time zones and under different daylight saving time rules. Be- sides the time zone conversion function, which is well supported by default classes in R, one might need functions to handle special days or holi- days. In this respect, the package timeDate en- hances default date-time classes in R and brings new functionalitie...
2 Citations Source Cite
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