Various tools and data sets that support the study of kanji, including their morphology, decomposition and concepts of distance and similarity between them.

One-way and two-way analysis of variance for replicated point
	patterns, grouped by one or two classification factors, on the
	basis of the corresponding K-functions.

Computes the Kantorovich distance between two probability
    measures on a finite set. The Kantorovich distance is also known as
    the Monge-Kantorovich distance or the first Wasserstein distance.

Sequences encoding by using the chaos game representation.
    Löchel et al. (2019) <doi:10.1093/bioinformatics/btz493>.

Tests the homogeneity of intraclass kappa statistics obtained from independent studies or a stratified study with binary results. It is desired to compare the kappa statistics obtained in multi-center studies or in a single stratified study to give a common or summary kappa using all available information. If the homogeneity test of these kappa statistics is not rejected, then it is possible to make inferences over a single kappa statistic that summarizes all the studies. Muammer Albayrak, Kemal Turhan, Yasemin Yavuz, Zeliha Aydin Kasap (2019) <doi:10.1080/03610918.2018.1538457> Jun-mo Nam (2003) <doi:10.1111/j.0006-341X.2003.00118.x> Jun-mo Nam (2005) <doi:10.1002/sim.2321>Mousumi Banerjee, Michelle Capozzoli, Laura McSweeney,Debajyoti Sinha (1999) <doi:10.2307/3315487> Allan Donner, Michael Eliasziw, Neil Klar (1996) <doi:10.2307/2533154>.

Estimate agreement of a group of raters with a gold standard rating
    on a nominal scale. For a single gold standard rater the average pairwise
    agreement of raters with this gold standard is provided. For a group of (gold
    standard) raters the approach of S. Vanbelle, A. Albert (2009)
    <doi:10.1007/s11336-009-9116-1> is implemented. Bias and standard error are
    estimated via delete-1 jackknife.

Offers a graphical user interface for the evaluation of inter-rater agreement with Cohen's and Fleiss' Kappa. The calculation of kappa statistics is done using the R package 'irr', so that 'KappaGUI' is essentially a Shiny front-end for 'irr'.