All functions

ad_ksample()

Anderson--Darling K-Sample Test

anderson_darling_normal() anderson_darling_lognormal() anderson_darling_weibull()

Anderson--Darling test for goodness of fit

augment(<mnr>)

Augment data with information from an mnr object

basis_normal() basis_lognormal() basis_weibull() basis_pooled_cv() basis_pooled_sd() basis_hk_ext() basis_nonpara_large_sample() basis_anova()

Calculate basis values

calc_cv_star()

Calculate the modified CV from the CV

carbon.fabric carbon.fabric.2

Sample data for a generic carbon fabric

cv()

Calculate the coefficient of variation

equiv_change_mean()

Equivalency based on change in mean value

equiv_mean_extremum()

Test for decrease in mean or minimum individual

glance(<adk>)

Glance at a adk (Anderson--Darling k-Sample) object

glance(<anderson_darling>)

Glance at an anderson_darling object

glance(<basis>)

Glance at a basis object

glance(<equiv_change_mean>)

Glance at a equiv_change_mean object

glance(<equiv_mean_extremum>)

Glance at an equiv_mean_extremum object

glance(<levene>)

Glance at a levene object

glance(<mnr>)

Glance at a mnr (maximum normed residual) object

hk_ext_z() hk_ext_z_j_opt()

Calculate values related to Extended Hanson--Koopmans tolerance bounds

k_equiv()

k-factors for determining acceptance based on sample mean and an extremum

k_factor_normal()

Calculate k factor for basis values (\(kB\), \(kA\)) with normal distribution

levene_test()

Levene's Test for Equality of Variance

maximum_normed_residual()

Detect outliers using the maximum normed residual method

nested_data_plot()

Create a plot of nested sources of variation

nonpara_binomial_rank()

Rank for distribution-free tolerance bound

normalize_group_mean()

Normalize values to group means

normalize_ply_thickness()

Normalizes strength values to ply thickness

stat_esf()

Empirical Survival Function

stat_normal_surv_func()

Normal Survival Function

transform_mod_cv_ad() transform_mod_cv()

Transforms data according to the modified CV rule