Package index • bullseye

All functions

ace_cor(): Calculates ace based transformations and correlation, handling missing values and factors.

add_nobs_to_pairwise(): Adds number of observations column to pairwise tibble

as.matrix(<pairwise>): Converts a pairwise to a symmetric matrix. Uses the first entry for each (x,y) pair.

pair_ace(): Alternating conditional expectations correlation

pair_cancor(): Canonical correlation

pair_chi(): Pearson's Contingency Coefficient for association between factors.

pair_control(): Default scores calculated by pairwise_scores

pair_cor(): Pearson, Spearman or Kendall correlation

pair_dcor(): Distance correlation

pair_gkGamma(): Goodman Kruskal's Gamma for association between ordinal factors.

pair_gkTau(): Goodman Kruskal's Tau for association between ordinal factors.

pair_kendall(): Kendall's correlation

pair_methods: Pairwise score functions available in the package

pair_mine(): MINE family values

pair_nmi(): Normalized mutual information

pair_polychor(): Polychoric correlation

pair_polyserial(): Polyserial correlation

pair_scagnostics(): Graph-theoretic scagnostics values

pair_spearman(): Spearman correlation

pair_tauA(): Kendall's tau A for association between ordinal factors.

pair_tauB(): Kendall's tau B for association between ordinal factors.

pair_tauC(): Stuarts's tau C for association between ordinal factors.

pair_tauW(): Kendall's W for association between ordinal factors.

pair_uncertainty(): Uncertainty coefficient for association between factors.

pairwise() as.pairwise(): A generic function to create a data structure for summarising variable pairs in a dataset

pairwise_by(): Constructs a pairwise result for each level of a by variable.

pairwise_multi(): Calculates multiple scores

pairwise_scores(): Calculates scores or conditional scores for a dataset

plot(<pairwise>): Plot method for class pairwise.

plot_pairwise(): Pairwise plot in a matrix layout

plot_pairwise_linear(): Pairwise plot in a linear layout