Journal of Data Science

In 2022 the American Statistical Association established the Riffenburgh Award, which recognizes exceptional innovation in extending statistical methods across diverse fields. Simultaneously, the Department of Statistics at the University of Connecticut proudly commemorated six decades of excellence, having evolved into a preeminent hub for academic, industrial, and governmental statistical grooming. To honor this legacy, a captivating virtual dialogue was conducted with the department’s visionary founder, Dr. Robert H. Riffenburgh, delving into his extraordinary career trajectory, profound insights into the statistical vocation, and heartfelt accounts from the faculty and students he personally nurtured. This multifaceted narrative documents the conversation with more detailed background information on each topic covered by the interview than what is presented in the video recording on YouTube.

This paper proposes a procedure to execute external source codes from a LATEX document and include the calculation outputs in the resulting Portable Document Format (pdf) file automatically. It integrates programming tools into the LATEX writing tool to facilitate the production of reproducible research. In our proposed approach to a LATEX-based scientific notebook the user can easily invoke any programming language or a command-line program when compiling the LATEX document, while using their favorite LATEX editor in the writing process. The required LATEX setup, a new Python package, and the defined preamble are discussed in detail, and working examples using R, Julia, and MatLab to reproduce existing research are provided to illustrate the proposed procedure. We also demonstrate how to include system setting information in a paper by invoking shell scripts when compiling the document.