Computes Fourier integrals of functions of one and two variables using the Fast Fourier transform. The Fourier transforms must be evaluated on a regular grid for fast evaluation.

Play or simulate games of "Four in a Row" in the R console. This 
    package is designed for educational purposes, encouraging users to write
    their own functions to play the game automatically. It contains a 
    collection of built-in functions that play the game at various skill levels,
    for users to test their own functions against.

A game for two players: Who gets first four in a row (horizontal, vertical or diagonal) wins. As board game published by Milton Bradley, designed by Howard Wexler and Ned Strongin.

Implements parsimonious hidden Markov models for four-way data via expectation-
    conditional maximization algorithm, as described in Tomarchio et al. (2020) <arXiv:2107.04330>.
    The matrix-variate normal distribution is used as emission distribution. For each hidden
    state, parsimony is reached via the eigen-decomposition of the covariance matrices of the
    emission distribution. This produces a family of 98 parsimonious hidden Markov models.

Provides functions for joining data frames based on inexact
    criteria, including string distance, Manhattan distance, Euclidean
    distance, and interval overlap. This API is designed as a modern,
    performance-oriented alternative to the 'fuzzyjoin' package (Robinson 2026)
    <doi:10.32614/CRAN.package.fuzzyjoin>. String distance functions utilizing
    'q-grams' are adapted with permission from the 'textdistance' 'Rust' crate
    (Orsinium 2024) <https://docs.rs/textdistance/latest/textdistance/>. Other
    string distance calculations rely on the 'rapidfuzz' 'Rust' crate (Bachmann
    2023) <https://docs.rs/rapidfuzz/0.5.0/rapidfuzz/>. Interval joins are
    backed by a Adelson-Velsky and Landis tree as implemented by the 'interavl'
    'Rust' crate <https://docs.rs/interavl/0.5.0/interavl/>.

Spatio-temporal Fixation Pattern Analysis (FPA) is a new method of analyzing eye 
  movement data, developed by Mr. Jinlu Cao under the supervision of Prof. Chen Hsuan-Chih at 
  The Chinese University of Hong Kong, and Prof. Wang Suiping at the South China Normal 
  Univeristy. The package "fpa" is a R implementation which makes FPA analysis much easier. 
  There are four major functions in the package: ft2fp(), get_pattern(), plot_pattern(), and 
  lineplot(). The function ft2fp() is the core function, which can complete all the preprocessing 
  within moments. The other three functions are supportive functions which visualize the eye 
  fixation patterns.