Fit latent space network cluster models using an expectation-maximization algorithm. Enables flexible modeling of unweighted or weighted network data (with or without noise edges), supporting both directed and undirected networks (with or without degree and strength heterogeneity). Designed to handle large networks efficiently, it allows users to explore network structure through latent space representations, identify clusters (i.e., community detection) within network data, and simulate networks with varying clustering, connectivity patterns, and noise edges. Methodology for the implementation is described in Arakkal and Sewell (2025) <doi:10.1016/j.csda.2025.108228>.

Full texts for Jane Austen's 6 completed novels, ready for
    text analysis. These novels are "Sense and Sensibility", "Pride and
    Prejudice", "Mansfield Park", "Emma", "Northanger Abbey", and
    "Persuasion".

The main janitor functions can: perfectly format data.frame column
    names; provide quick counts of variable combinations (i.e., frequency
    tables and crosstabs); and explore duplicate records. Other janitor functions
    nicely format the tabulation results. These tabulate-and-report functions
    approximate popular features of SPSS and Microsoft Excel. This package
    follows the principles of the "tidyverse" and works well with the pipe function
    %>%. janitor was built with beginning-to-intermediate R users in mind and is
    optimized for user-friendliness.

Proposes a coarse-to-fine optimization of a recommending system based on deep-neural networks using 'tensorflow'.

Provides functions to access data from public RESTful APIs including 
    'Nager.Date', 'World Bank API', and 'REST Countries API', retrieving real-time or historical 
    data related to Japan, such as holidays, economic indicators, and international 
    demographic and geopolitical indicators. Additionally, the package includes one of the largest 
    curated collections of open datasets focused on Japan, covering topics such as natural disasters, 
    economic production, vehicle industry, air quality, demographics, and administrative divisions. 
    The package supports reproducible research and teaching by integrating reliable international 
    APIs and structured datasets from public, academic, and government sources.
    For more information on the APIs, see: 
    'Nager.Date' <https://date.nager.at/Api>, 
    'World Bank API' <https://datahelpdesk.worldbank.org/knowledgebase/articles/889392>, 
    and 'REST Countries API' <https://restcountries.com/>.