This special issue of the Austrian Journal of Statistics is devoted tothe memory of Friedrich "Fritz" Leisch who passed away after a seriousillness a year ago, in April 2024. The idea for the issue was developedby a group of collaborators and friends of Fritz, consisting of BettinaGrün, Kurt Hornik, Torsten Hothorn, Theresa Scharl, and AchimZeileis. Our aim was to compile contributions which honor Fritz' diversescientific contributions to statistical computing, literate programming,cluster analysis and mixture models, statistical graphics, and appliedstatistics. Contributions were by invitation only and issued to a numberof Fritz' co-authors. Bettina Grün and Theresa Scharl processed thespecial issue as Guest Editors. We would also like to thank the Editorof the Austria Journal of Statistics, Matthias Templ, and the CopyEditor, Klara Hruzova, for their support.

The special issue covers two contributions honoring Fritz' impact onreproducible research and literate programming by Roger Peng (Universityof Texas at Austin) and by Robert Gentleman (Dana Farber CancerInstitute), Antony Rossini (UCB and University of Washington), andVincent Carey (Harvard Medical School), respectively. A contribution byFritz Leisch and Torsten Hothorn (both at LMU Munich when drafting thisin 2011) on inference for mixture models is finally published. Inaddition, Torsten Hothorn (University of Zurich) reflects on thereproducibility of the ten-year-old simulation study included in thiswork.Three contributions extend clustering methodology developed by Fritz andare accompanied by new R packages, available from the Comprehensive RArchive Network (CRAN). Dominik Ernst, Lena Ortega Menjivar, TheresaScharl (all BOKU University), and Bettina Grün (WU Wien) discussdistance-based as well as model-based clustering methods for ordinaldata; Matthias Medl, Ursula Laa (both BOKU University), and Dianne Cook(Monash University Melbourne) provide interactive exploration andvisualization methods for market segmentation; and Lucas Sablica, KurtHornik, and Bettina Grün (all WU Wien) contribute to spherical andcircular clustering in text mining.Fritz' general interest in different areas of statistics, in particularwhen useful for applied work, including robust, educational, andenvironmental statistics is reflected by the remainingcontributions. Bernhard Spangl (BOKU University) investigates therobustification of the Kalman filter in a multivariate setting, AchimZeileis (University of Innsbruck) presents different approaches forassessing measurement invariance and for detecting differential itemfunctioning in the Rasch model along with their software implementationin R, and Gregor Laaha, Johannes Laimighofer, Nur Banu Özcelik (all BOKUUniversity), and Svenja Fischer (Wageningen University) provide fourcase studies where accounting for heterogeneity based on domainknowledge improves the statistical modeling approach.

Bettina Grün and Theresa Scharl (Guest Editors)