Package index
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ace_cor() - Calculates ace based transformations and correlation, handling missing values and factors.
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as.matrix(<pairwise>) - Converts a pairwise to a symmetric matrix. Uses the first entry for each (x,y) pair.
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pair_ace() - Alternating conditional expectations correlation
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pair_cancor() - Canonical correlation
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pair_chi() - Pearson's Contingency Coefficient for association between factors.
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pair_control() - Default scores calculated by
pairwise_scores
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pair_cor() - Pearson, Spearman or Kendall correlation
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pair_dcor() - Distance correlation
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pair_gkGamma() - Goodman Kruskal's Gamma for association between ordinal factors.
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pair_gkTau() - Goodman Kruskal's Tau for association between ordinal factors.
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pair_methods - Pairwise score functions available in the package
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pair_mine() - MINE family values
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pair_nmi() - Normalized mutual information
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pair_polychor() - Polychoric correlation
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pair_polyserial() - Polyserial correlation
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pair_scagnostics() - Graph-theoretic scagnostics values
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pair_tauA() - Kendall's tau A for association between ordinal factors.
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pair_tauB() - Kendall's tau B for association between ordinal factors.
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pair_tauC() - Stuarts's tau C for association between ordinal factors.
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pair_tauW() - Kendall's W for association between ordinal factors.
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pair_uncertainty() - Uncertainty coefficient for association between factors.
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pairwise()as.pairwise() - A generic function to create a data structure for every variable pair in a dataset
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pairwise_by() - Constructs a pairwise result for each level of a by variable.
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pairwise_multi() - Calculates multiple scores
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pairwise_scores() - Calculates scores or conditional scores for a dataset
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plot(<pairwise>) - Plot method for class
pairwise.
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plot_pairwise() - Pairwise plot in a matrix layout
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plot_pairwise_linear() - Pairwise plot in a linear layout