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HomeVitaForschungVorlesungen & SeminarePublikationen

(1) Predicting missing values in spatio-temporal satellite data

  • predictions are obtained with selecting subsets, sorting procedures, and quantile regression
  • the workload can be distributed to several computers
  • the method is available in the R package gapfill
Software:
https://cran.r-project.org/package=gapfill

Manuscripts:
F. Gerber, R. Furrer, G. Schaepman-Strub, R. de Jong, M. E. Schaepman.
Predicting Missing Values in Spatio-Temporal Satellite Data. arXiv, 2017


(2) 64-bit sparse matrices with the R package spam

  • spam and spam64 enables matrices with more than 2^31 non-zero elements
  • dotCall64 is an enhanced interface to link R with compiled code
  • spam64 was tested with a non-stationary spatial model
Software:
https://cran.r-project.org/package=spam
https://cran.r-project.org/package=spam64
https://cran.r-project.org/package=dotCall64

Manuscripts:
F. Gerber, K. Mösinger, R. Furrer. Extending R Packages to Support 64-bit Compiled Code: An Illustration with spam64 and GIMMS NDVI3g Data. Comput. Geosci., 2016

F. Gerber, K. Mösinger, R. Furrer. dotCall64: An Efficient Interface to Compiled C/C++ and Fortran Code Supporting Long Vectors. arXiv, 2017





(3) Bayesian inference and medical applications

  • assessment of inference methods for Bayesian hierarchical models
  • spatial models for areal count data
  • operating characteristics for Bayesian clinical trial designs
Software:
https://cran.r-project.org/package=gsbDesign

Manuscripts:
F. Gerber, R. Furrer. Pitfalls in the Implementation of Bayesian Hierarchical Modeling of Areal Count Data: An Illustration Using BYM and Leroux Models. J. Stat. Soft., 2015

T. Gsponer, F. Gerber, B. Bornkamp, D. Ohlssen, M. Vandemeulebroecke, H. Schmidli. Bayesian Group Sequential Designs for Clinical Trials and their Operating Characteristics. Pharmaceut. Statist., 2014

F. Gerber, T. Gsponer. gsbDesign: An R Package for Evaluating the Operating Characteristics of a Group Sequential Bayesian Design. J. Stat. Soft., 2016





More research projects of the Applied Statistics Group of Prof. Dr. R. Furrer