anova.hpp File Reference

#include <memory_resource>
#include <nk/value/value.hpp>
#include <tuple>

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Enumerations
enum class	nk::stats::McCorrection { Bonferroni , LSD }
	Multiple-comparison correction methods for multcompare. More...

Functions
std::tuple< double, double, double, double, double, double >	nk::stats::anova1 (const Value &y, const Value &group, std::pmr::memory_resource *mr=nullptr)
	One-way ANOVA ([p, F, df_b, df_w, ss_b, ss_w] = anova1(y, group)).
std::tuple< Value, Value, Value, Value >	nk::stats::kruskalwallis (const Value &y, const Value &group, std::pmr::memory_resource *mr=nullptr)
	Kruskal–Wallis non-parametric one-way ANOVA ([p, H, df, ssRanks] = kruskalwallis(y, group)).
std::tuple< Value, Value, Value >	nk::stats::friedman (const Value &x, int reps=1, std::pmr::memory_resource *mr=nullptr)
	Friedman non-parametric two-way ANOVA by ranks ([p, Q, df] = friedman(x, reps)).
Value	nk::stats::dummyvar (const Value &group, std::pmr::memory_resource *mr=nullptr)
	Convert categorical labels to indicator columns (X = dummyvar(group)).
Value	nk::stats::multcompare (const Value &stats, double alpha=0.05, McCorrection ctype=McCorrection::Bonferroni, std::pmr::memory_resource *mr=nullptr)
	Pairwise post-hoc comparisons after one-way ANOVA (c = multcompare(stats [, alpha [, ctype]])).