I am a PhD candidate within the GIScience group at the Department of Geography. I focus on the application of statistical- and machine learning techniques to address research questions related to environmental issues.
Besides the scientific part my interests lie in the development of programming solutions to simplify todays data science challenges. I am working in a reproducible manner and actively working on promoting the idea of reproducible research in science. I like to write about the Linux world, the R programming world and other technical topics that I find interesting.
M.Sc. in Geoinformatics, 2016
B.Sc. in Geography, 2014
Gillespie C. & Lovelace R. (2016): Efficient R Programming. O`Reilly. https://csgillespie.github.io/efficientR/
Xie Y. (2016): bookdown: Authoring Books and Technical Documents with R Markdown. Chapman & Hall. https://bookdown.org/yihui/bookdown/
De Veaux R. et al. (2015): Stats: Data and Models (4th ed.). Pearson. Link
James R. et al. (2015) An Introduction to Statistical Learning. Springer. Link
Zuur A.F. et al. (2008): Mixed Effects Models and Extensions in Ecology with R. Springer. http://www.springer.com/de/book/9780387874579
Mixed Models in R: http://m-clark.github.io/docs/mixedModels/mixedModels.html
Intro to Spatial Analysis in R: https://jafflerbach.github.io/spatial-analysis-R/intro_spatial_data_R.html#introduction
Generalized Additive Models (GAMs) in R: https://m-clark.github.io/generalized-additive-models/preface.html
More statistic related posts from Michael Clark: http://m-clark.github.io/documents/
I worked as a teaching assistant in the following courses at University of Jena: