The PDE (Pdf Data Extractor) allows the extraction of 
    information and tables optionally based on search words from 
    PDF (Portable Document Format) files and enables the visualization 
    of the results, both by providing a convenient user-interface.

Provides a nonparametric, multicore-capable plausible naive Bayes classifier based on Pareto density estimation (PDE). It addresses low-evidence cases through a plausibility correction. To enhance the interpretability of the flexible naive Bayes classifier by revealing its posterior structure and feature-wise, class-specific evidence, posterior probabilities can be visualized as class-wise line plots for one-dimensional data or color-coded Voronoi diagrams for pairwise feature projections, and class-conditional PDE likelihoods as overlaid, mirrored density profiles resembling violin plots. Methodological details are provided by Stier, Q., Hoffmann, J. and Thrun, M. C. (2026) "Classifying with the Fine Structure of Distributions: Leveraging Distributional Information for Robust and Plausible Naive Bayes" <DOI:10.3390/make8010013>. For multicore computations, the implementation applies the general memory-sharing approach described by Thrun, M. C. and Märte, J. (2026) "memshare: Memory Sharing for Multicore Computation in R with an Application to Feature Selection by Mutual Information using PDE" <DOI:10.32614/RJ-2025-043>.

Data sets for the Panel Data Econometrics with R <doi:10.1002/9781119504641> book.

Cluster analysis via nonparametric density 
   estimation is performed. Operationally, the kernel method is used throughout to estimate
   the density. Diagnostics methods for evaluating the quality of the clustering 
   are available. The package includes also a routine to estimate the 
   probability density function obtained by the kernel method, given a set of
   data with arbitrary dimensions.

A 'shiny' app that supports merging of PDF and/or image files with page selection, removal, or rotation options.
    It is a fast, free, and secure alternative to commercial software or various online websites which require users to sign-up, and it avoids any potential risks associated with uploading files elsewhere.