@Software{KlinkeMMStat4,
  author   = {Sigbert Klinke},
  date     = {2023-03-04},
  year     = {2023},
  title    = {mmstat4: Access to Teaching Materials from a ZIP File or GitHub},
  type     = {software},
  howpublished= {CRAN},
  url      = {https://cran.r-project.org/package=mmstat4},
  version  = {0.1.3},
  abstract = {Teaching materials, e.g. R programs, Shiny apps, data and PDF/HTML documents, which are stored on the Internet in a ZIP file (e.g. as a GitHub repository) can be downloaded. They can be displayed or run locally. The content of the ZIP file is temporarily (or permanently) stored. The GitHub repository 'sigbertklinke/mmstat4.data' is used as the default repository. In addition, some auxiliary functions are implemented.
  
  Development version: https://github.com/sigbertklinke/mmstat},
  groups   = {R}
}

@Software{KlinkeAndrews,
  author   = {Sigbert Klinke and Jaroslav Myslivec},
  date     = {2023-01-08},
  year     = {2023},
  howpublished= {CRAN},
  title    = {andrews: Various Andrews Curves},
  type     = {software},
  url      = {https://cran.r-project.org/package=andrews},
  version  = {1.1.0},
  abstract = {Visualisation of multidimensional data through different Andrews curves.
  
  Development version: https://github.com/sigbertklinke/andrews},
  groups   = {R}
}

@Software{KlinkeHKRbook,
  author   = {Sigbert Klinke and Wolfgang Härdle and Bernd Rönz},
  date     = {2022-10-06},
  year     = {2022},
  title    = {HKRbook: Apps and Data for the Book "Introduction to Statistics"},
  type     = {software},
  howpublished= {CRAN},  
  url      = {https://cran.r-project.org/package=HKRbook},
  version  = {0.1.3},
  abstract = {Functions, Shiny apps and data for the book "Introduction to Statistics" by Wolfgang Karl Härdle, Sigbert Klinke, and Bernd Rönz (2015) .
  
  Development version: https://github.com/sigbertklinke/HKRbook},
  groups   = {R}
}

@Software{KlinkePlotMatrix,
  author   = {Sigbert Klinke},
  year     = {2023},
  title    = {plot.matrix: Visualizes a Matrix as Heatmap},
  url      = {https://CRAN.R-project.org/package=plot.matrix},
  howpublished= {CRAN},
  version  = {1.6.1},
  abstract = {Visualizes a matrix object plainly as heatmap. It provides S3 functions to plot simple matrices and loading matrices.

Development version: https://github.com/sigbertklinke/plot.matrix},
}

@Software{KlinkeIframe,
  author   = {Sigbert Klinke},
  date     = {2022-10-09},
  year     = {2022},
  title    = {MediaWiki Extension Iframe},
  url      = {https://www.mediawiki.org/wiki/Extension:Iframe},
  version  = {0.10},
  howpublished= {CRAN},  
  abstract = {The extension allows in a MediWiki the embedding of foreign web pages via an iframe.

Development version: https://github.com/sigbertklinke/Iframe/},
}

@Software{KlinkeAbbreviate,
  author   = {Sigbert Klinke},
  date     = {2021-12-14},
  year     = {2021},
  title    = {abbreviate: Readable String Abbreviation},
  url      = {https://CRAN.R-project.org/package=abbreviate},
  version  = {0.1},
  howpublished= {CRAN},  
  abstract = {Strings are abbreviated to at least "minlength" characters, such that they remain unique (if they were). The abbreviations should be recognisable.
  
  Development version: https://github.com/sigbertklinke/abbreviate},
  groups   = {R}
}

@Software{KlinkeSmvgraph,
  author   = {Sigbert Klinke},
  date     = {2021-11-08},
  year     = {2021},
  title    = {smvgraph: Various Multivariate Graphics with Variable Choice in Shiny Apps},
  url      = {https://CRAN.R-project.org/package=smvgraph},
  howpublished= {CRAN},  
  version  = {0.1.2},
  abstract = {Mosaic diagram, scatterplot matrix, Andrews curves, parallel coordinate diagram, radar diagram, and Chernoff plots as a Shiny app, which allow the order of variables to be changed interactively. The apps are intended as teaching examples.

  Development version: https://github.com/sigbertklinke/smvgraph},
  groups   = {R}
}

@Software{KlinkeRscc,
  author   = {Sigbert Klinke},
  date     = {2021-11-01},
  year     = {2021},
  title    = {rscc: R Source Code Similarity Evaluation by Similarity Coefficients},
  url      = {https://CRAN.R-project.org/package=rscc},
  version  = {0.2.0},
  howpublished= {CRAN},  
  abstract = {Evaluates R source codes by variable and/or functions names. Similar source codes should deliver similarity coefficients near one. Since neither the frequency nor the order of the used names is considered, a manual inspection of the R source code is required to check for similarity. Possible use cases include detection of code clones for improving software quality and of plagiarism amongst students' assignments.

  Development version: https://github.com/sigbertklinke/rscc},
  groups   = {R}
}

@Software{KlinkeRmdwc,
  author   = {Sigbert Klinke},
  date     = {2021-09-07},
  year     = {2021},
  title    = {rmdwc: Count Words, Chars and Non-Whitespace Chars in R Markdown Docs},
  url      = {https://CRAN.R-project.org/package=rmdwc},
  version  = {0.2.1},
  howpublished= {CRAN},  
  abstract = {If you are using R Markdown documents then you have sometimes restrictions about the size of the documents, e.g. number of words, number of characters or non-whitespace characters. rmdcount() computes these counts with and without code chunks and returns the result as data frame.

Development version: https://github.com/sigbertklinke/rmdwc},
  groups   = {R}
}

@Software{KlinkeListArray,
  author   = {Sigbert Klinke},
  date     = {2020-09-10},
  year     = {2020},
  title    = {listArray: Incomplete Array with Arbitrary R Objects as Indices},
  url      = {https://CRAN.R-project.org/package=listArray},
  version  = {0.1.1},
  howpublished= {CRAN},  
  abstract = {The aim of the package is to create data objects which allow for accesses like x["test"] and x["test","test"].

Development version: https://github.com/sigbertklinke/listArray},
}

@Article{FlippedClassroom2018,
  author = {F{\"{o}}rster, Manuel and Hei{\ss}, Florian and Klinke, Sigbert and Maur, Andreas and Schank, Thorsten and Weise, Constantin},
  title = {Die Implementation und Evaluation eines Flipped Classrooms in einer Gro{\ss}veranstaltung der Statistik},
  year = {2018},
  URL = {http://www.bzh.bayern.de/uploads/media/4\_2018\_Foerster\_Heiss\_Klinke\_Maur\_Schank\_Weiser.pdf},
  journal = {Beitr{\"{a}}ge zur Hochschulforschung},
  number = {4},
  pages = {50.67}
}

@Book{IntroductionStatistics2015,
  author = {H{\"{a}}rdle, Wolfgang Karl and Klinke, Sigbert and R{\"{o}}nz, Bernd},
  title = {Introduction to Statistics: Using Interactive MM*Stat Elements},
  year = {2015},
  URL = {https://www.amazon.com/Introduction-Statistics-Using-Interactive-Elements/dp/3319177036?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=3319177036},
  publisher = {Springer},
  isbn = {978-3-319-17703-8},
  doi = {10.1007/978-3-319-17704-5},
  isbn = {978-3-319-17703-8}
}

@Software{KlinkeRExtension,
  author   = {Sigbert Klinke},
  date     = {2014-08-22},
  title    = {MediaWiki Extension R},
  url      = {https://www.mediawiki.org/wiki/Extension:R},
  version  = {0.14\textunderscore1},
  howpublished= {CRAN},  
  abstract = {The R extension allows to integrate output (raw text, HTML and graphics) from R and Octave programs, which are free software environments for statistical computing and graphics, on wiki pages.},
}

@Inbook{Kompetenzforschung2013,
  author = {F{\"{o}}rster, Manuel and Klinke, Sigbert},
  title = {Pr{\"{u}}fung auf nicht-lineare Zusammenh{\"{a}}nge und deren Modellierung in der Kompetenzforschung - Ein Beispiel aus dem Projekt ILLEV},
  year = {2013},
  URL = {https://www.amazon.com/Kompetenzmodellierung-Kompetenzmessung-Studierenden-Wirtschaftswissenschaften-Ingenieurwissenschaften/dp/3944996003?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=3944996003},
  booktitle = {Kompetenzmodellierung und Kompetenzmessung bei Studierenden der Wirtschaftswissenschaften und Ingenieurswissenschaften},
  editor = {Olga Zlatkin-Troitschanskaia and Reinhold Nickolaus and Klaus Beck},
  publisher = {Verlag Empirische P{\"{a}}dagogik},
  chapter = {Pr{\"{u}}fung auf nicht-lineare Zusammenh{\"{a}}nge und deren Modellierung in der Kompetenzforschung - Ein Beispiel aus dem Projekt ILLEV},
  pages = {49-68},
  isbn = {978-3944996004},
  isbn = {978-3944996004}
}

@inbook{Klinke2012415,
  author = {Klinke, S},
  editor = {James E. Gentle and Wolfgang Karl Härdle and Yuichi Mori},
  title = {Handbook of Computational Statistic - Concepts and Methods},
  chapter = {Statistical user interfaces},
  year = {2012},
  publisher = {Springer Berlin Heidelberg},
  isbn = {783642215506},
  keywords = {User interfaces},
  doi = {10.1007/978-3-642-21551-3_14},
  isbn = {978-3-642-21550-6}
}

@Article{NetzwerkSchlerbefragung2010,
  author = {Wagner, Cornelia and Gr{\"{u}}tzmann, Joachim and Neumann, Uwe and Klinke, Sigbert},
  title = {Sch{\"{u}}ler/-innen evaluieren Unterricht. Ergebnisse aus dem "Netzwerk Sch{\"{u}}lerbefragung".},
  year = {2010},
  abstract = {Entwicklungsprozesse in Schule und Unterricht k{\"{o}}nnen durch interne Evaluation angesto{\ss}en, begleitet und gef{\"{o}}rdert werden. Eine M{\"{o}}glichkeit interner Evaluation ist die Sch{\"{u}}lerbefragung, mit der z.B. eine Bestandsaufnahme der Qualit{\"{a}}t des Unterrichts aus der Sch{\"{u}}lerperspektive durchgef{\"{u}}hrt werden kann. Die Autoren stellen Ergebnisse aus dem "Netzwerk Sch{\"{u}}lerbefragung zur Durchf{\"{u}}hrung und Auswertung von Sch{\"{u}}lerbefragungen vor. Das Netzwerk ist 2005 aus einem Projekt des Berliner Oberstufenzentrums f{\"{u}}r Druck- und Medientechnik entstanden.},
  journal = {Wirtschaft \& Erziehung},
  number = {7/8},
  pages = {228-233},
  issn = {0174-6170}
}

@Article{SchulprogrammeSchulprogrammarbeit2008,
  author = {Buer, J{\"{u}}rgen van and K{\"{o}}ller, Michela and Klinke, Sigbert},
  title = {Schulprogramme und Schulprogrammarbeit an beruflichen Schulen - Konstruktionsleistungen und Implementationserwartungen.},
  year = {2008},
  journal = {Zeitschrift f{\"{u}}r Berufs- und Wirtschaftsp{\"{a}}dagogik},
  volume = {104},
  number = {3},
  pages = {358-384}
}

@Article{Hrdle2007355,
  author = {H{\"{a}}rdle, W and Klinke, S and Ziegenhagen, U},
  title = {On the utility of E-learning in statistics},
  year = {2007},
  abstract = {Students of introductory courses consider statistics as particularly difficult, as the understanding of the underlying concepts may require more time and energy than for other disciplines. For decades statisticians have tried to enhance understanding with the help of technical solutions such as animation, video or interactive tools. However, it is not clear if the added value generated by these e-learning tools justifies the work invested. In this paper the experience with various e-learning solutions in terms of utility and the impact on teaching is discussed. {\textcopyright} 2007 International Statistical Institute.},
  journal = {International Statistical Review},
  volume = {75},
  number = {3},
  pages = {355-364},
  doi = {10.1111/j.1751-5823.2007.00026.x},
  issn = {03067734}
}

@Article{Klinke2007497,
  author = {Klinke, S},
  title = {Special issue: Workshop data and information visualisation 2006},
  year = {2007},
  journal = {Computational Statistics},
  volume = {22},
  number = {4},
  pages = {497},
  doi = {10.1007/s00180-007-0056-x},
  issn = {09434062}
}

@Article{projectionpursuit2005,
  author = {Lee, Eun-Kyung and Cook, Dianne and Klinke, Sigbert and Lumley, Thomas},
  title = {Projection Pursuit for Exploratory Supervised Classification},
  year = {2005},
  URL = {https://doi.org/10.1198/106186005X77702},
  abstract = {In high-dimensional data, one often seeks a few interesting low-dimensional projections that reveal important features of the data. Projection pursuit is a procedure for searching high-dimensional data for interesting low-dimensional projections via the optimization of a criterion function called the projection pursuit index. Very few projection pursuit indices incorporate class or group information in the calculation. Hence, they cannot be adequately applied in supervised classification problems to provide low-dimensional projections revealing class differences in the data. This article introduces new indices derived from linear discriminant analysis that can be used for exploratory supervised classification.},
  journal = {Journal of Computational and Graphical Statistics},
  volume = {14},
  number = {4},
  pages = {831-846},
  doi = {10.1198/106186005X77702}
}

@Misc{compstat2002,
  author = {Klinke, Sigbert and Ahrend, Patricia and Richter, Luise},
  title = {Proceedings of the Conference CompStat 2002 - Short Communications and Posters},
  year = {2002},
  howpublished = {CD}
}

@Misc{wistat4,
  author = {Schmerbach, Sibylle and Klinke, Sigbert},
  title = {4. Workshop Wirtschaftsstatistik: Inflationsmessung in Deutschland und Europa, Daten - Methoden - Entwicklungen},
  year = {2002},
  howpublished = {CD}
}

@Book{DataStructures2001,
  author = {Klinke, Sigbert},
  title = {Data Structures for Computational Statistics (Contributions to Statistics)},
  year = {2001},
  URL = {https://www.amazon.com/Data-Structures-Computational-Statistics-Contributions/dp/3790809829?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=3790809829},
  publisher = {Physica},
  doi = {10.1007/978-3-642-59242-3},
  isbn = {978-3-7908-0982-4},
  oisbn = {978-3-7908-0982-4}
}

@Book{XploReApplication2000,
  author = {H{\"{a}}rdle, W and Hlavka, Z and Klinke, S},
  title = {XploRe{\textregistered} - Application Guide},
  year = {2000},
  URL = {https://www.amazon.com/XploRe\%C2\%AE-Application-Guide-W-H\%C3\%A4rdle-ebook/dp/B000QCQW4A?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=B000QCQW4A},
  publisher = {Springer},
  isbn = {978-3-642-57292-0},
  doi = {10.1007/978-3-642-57292-0},
  isbn = {978-3-642-57292-0}
}

@Book{WHrdleSKlinkeMMller2000,
  author = {H{\"{a}}rdle, W and Klinke, S and M{\"{u}}ller, M},
  title = {XploRe Learning Guide},
  year = {2000},
  URL = {https://www.amazon.com/XploRe-Learning-Guide-W-H\%C3\%A4rdle/dp/3540662073?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=3540662073},
  publisher = {Springer},
  isbn = {978-3-540-66207-5},
  isbn = {978-3-540-66207-5}
}

@Article{Swayne1999,
  author = {Swayne, Deborah F and Klinke, Sigbert},
  title = {Introduction to the special issue on interactive graphical data analysis: What is interaction?},
  year = {1999},
  abstract = {In this introduction to the special issue of Computational Statistics on interactive graphical data analysis, we first briefly introduce the papers. They cover a lot of ground, from the updating of older statistical environments to the assessment of some of the newest, and there are several interesting examples of interactive graphics applied to data analysis problems. Afterwards, we describe a questionnaire we circulated in an effort to learn about the application of interactive graphical methods to data analysis in practice. We received too few responses to find the answers to our questions, but we did observe a few interesting things. In particular, we realized that conflicting uses of the term {\textquotedblleft}interactive{\textquotedblright} are currently in use, muddying our discussions of software design and data analysis practice. We'll discuss our observations in terms of the papers in this issue. We invite you to visit http://comst.wiwi.hu-berlin.de/issue0199.html for links to color versions of many of the graphics in the papers in this issue, as well as additional graphics provided by the authors.},
  journal = {Computational Statistics},
  volume = {14},
  number = {1},
  pages = {1-6},
  doi = {10.1007/PL00022700},
  issn = {0943-4062}
}

@Article{Klinke1997363,
  author = {Klinke, S and Cook, D},
  title = {Binning of Kernel-based projection pursuit indices in XGobi},
  year = {1997},
  abstract = {The software XGobi offers a selection of different index functions to be used in exploratory projection pursuit (EPP). EPP is a method for finding interesting low-dimensional (in this case two-dimensional) projections of highdimensional data. We discuss the inclusion of two additional index functions which make use of several standard techniques to improve the speed of the indices based on kernel density estimation. Unfortunately, the speed improvements do not apply to derivative calculations, but then are seldomly required in XGobi so speed does not matter much.},
  journal = {Computational Statistics and Data Analysis},
  volume = {25},
  number = {3},
  pages = {363-369},
  keywords = {Computer software;  Probability density function, Exploratory projection pursuit (EPP);  Kernel density estimation;  Software package XGobi, Data reduction},
  doi = {10.1016/S0167-9473(97)82604-7},
  issn = {01679473}
}

@Article{teachingwavelets1997,
  author = {Klinke, Sigbert and Golubev, Yuri and H{\"{a}}rdle, Wolfgang Karl and Neumann, Michael H},
  title = {Teaching Wavelets in XploRe},
  year = {1997},
  abstract = {Teachware is a set of computer software tools for computeraided interactive teaching of certain knowledge elements. The construction of teachware for statistical knowledge is a rather young field since it heavily depends on data structures and graphical interaction possibilities. In this paper we present a teachware module for XploRe - a statistical computing environment. We focus on the situation of teaching wavelets, a technique for adaptation of spatial inhomogeneity.},
  journal = {Computational Statistics},
  volume = {13},
  number = {2},
  pages = {141-151}
}

@Book{XploRe1995,
  author = {H{\"{a}}rdle, Wolfgang and Klinke, Sigbert and Turlach, Berwin A},
  title = {XploRe: An Interactive Statistical Computing Environment (Statistics and Computing)},
  year = {1995},
  URL = {https://www.amazon.com/XploRe-Interactive-Statistical-Environment-Statistics/dp/038794429X?SubscriptionId=AKIAIOBINVZYXZQZ2U3A\&tag=chimbori05-20\&linkCode=xm2\&camp=2025\&creative=165953\&creativeASIN=038794429X},
  publisher = {Springer},
  isbn = {978-0-387-94429-6},
  isbn = {978-0-387-94429-6}
}