# The three diagnostic diagrams

    library(logcumulant)
    data(reliability_datasets)
    yarn <- reliability_datasets$Yarn

The package provides three complementary moment-ratio diagrams. Each overlays the theoretical loci of the six reference families with a bootstrap cloud of the sample estimate and a 95% concentration ellipse.

## Log-cumulant diagram

Plots \(\kappa_3\) (log-skewness) against \(\kappa_2\) (log-variance). The vertical axis \(\kappa_3 = 0\) is where the symmetric-on-the-log-scale families (Log-Normal, Log-Logistic) lie.

    log_cumulant_diagram(yarn, "Yarn", B = 300)

## Kurtosis-skewness diagram

On the original scale: skewness \(\gamma_3\) versus excess kurtosis \(\gamma_4\), with the feasible-region boundary \(\gamma_4 = \gamma_3^2 - 2\).

    kurtosis_diagram(yarn, "Yarn", B = 300)

## Coefficient-of-variation diagram

Coefficient of variation \(\gamma_2\) versus skewness \(\gamma_3\), again on the original scale.

    cv_diagram(yarn, "Yarn", B = 300)

## All three at once

    three_diagrams(yarn, "Yarn", B = 300)

## Several datasets on one diagram

`multi_lc_diagram()` overlays bootstrap clouds for several datasets, distinguished by colour and plotting symbol.

    multi_lc_diagram(
      reliability_datasets[c("Airplane", "BallBearing", "Yarn")],
      B = 300
    )