In computationally demanding analysis projects,
  statisticians and data scientists asynchronously
  deploy long-running tasks to distributed systems,
  ranging from traditional clusters to cloud services.
  The 'crew.cluster' package extends the 'mirai'-powered
  'crew' package with worker launcher plugins for traditional
  high-performance computing systems.
  Inspiration also comes from packages 'mirai' by Gao (2023)
  <https://github.com/r-lib/mirai>,
  'future' by Bengtsson (2021) <doi:10.32614/RJ-2021-048>,
  'rrq' by FitzJohn and Ashton (2023) <https://github.com/mrc-ide/rrq>,
  'clustermq' by Schubert (2019) <doi:10.1093/bioinformatics/btz284>),
  and 'batchtools' by Lang, Bischl, and Surmann (2017).
  <doi:10.21105/joss.00135>.

Data on international and other major cricket matches from
  ESPNCricinfo <https://www.espncricinfo.com> and Cricsheet <https://cricsheet.org>.
  This package provides some functions to download the data into tibbles ready
  for analysis.

Tools for analyzing performances of cricketers based on stats in
    ESPN Cricinfo Statsguru. The toolset can  be used for analysis of Tests,ODIs 
    and Twenty20 matches of both batsmen and bowlers. The package can also be used to
    analyze team performances.

A finite mixture of Zero-Inflated Poisson (ZIP) models for analyzing criminal trajectories.

Gives convenient access to publicly available police-recorded open
    crime data from large cities in the United States that are included in the
    Crime Open Database <https://osf.io/zyaqn/>.

A comprehensive collection of datasets exclusively focused on crimes, criminal activities, and related topics. 
    This package serves as a valuable resource for researchers, analysts, and students interested in crime analysis, 
    criminology, social and economic studies related to criminal behavior. Datasets span global and local contexts, 
    with a mix of tabular and spatial data.

A collection of functions that make it easier to understand crime (or other)
    data, and assist others in understanding it. The package helps you read data 
    from various sources, clean it, fix column names, and graph the data.