Martin Schlather

Martin Schlather

7 packages on CRAN

adoption

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The classical Bass (1969) <doi:10.1287/mnsc.15.5.215> model and the agent based models, such as that by Goldenberg, Libai and Muller (2010) <doi:10.1016/j.ijresmar.2009.06.006> have been two different approaches to model adoption processes in marketing. These two approaches can be unified by explicitly modelling the utility functions. This package provides a GUI that allows, in a unified way, the modelling of these two processes and other processes.

miraculix

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This is a collection of fast tools for application in quantitative genetics. For instance, the SNP matrix can be stored in a minimum of memory and the calculation of the genomic relationship matrix is based on a rapid algorithm. It also contains the window scanning approach by Kabluchko and Spodarev (2009), <doi:10.1239/aap/1240319575> to detect anomalous genomic areas <doi:10.1186/s12864-018-5009-y>. Furthermore, the package is used in the Modular Breeding Program Simulator (MoBPS, <https://github.com/tpook92/MoBPS>, <http://www.mobps.de/>). The tools are based on SIMD (Single Instruction Multiple Data, <https://en.wikipedia.org/wiki/SIMD>) and OMP (Open Multi-Processing, <https://de.wikipedia.org/wiki/OpenMP>).

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Methods for the inference on and the simulation of Gaussian fields are provided, as well as methods for the simulation of extreme value random fields.

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Various utilities are provided that might be used in spatial statistics and elsewhere. It delivers a method for solving linear equations that checks the sparsity of the matrix before any algorithm is used. Furthermore, it includes the Struve functions.

tsgui

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This gui shows realisations of times series, currently ARMA and GARCH processes. It might be helpful for teaching and studying.

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Given an univariate dataset, returns the best fitting parameter families, as defined in Shao (2003) <doi:10.1007/B97553>, including their parameter estimates via maximum likelihood.

geoR

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Geostatistical analysis including variogram-based, likelihood-based and Bayesian methods. Software companion for Diggle and Ribeiro (2007) <doi:10.1007/978-0-387-48536-2>.