GmAMisc

Contains many functions useful for univariate outlier detection, permutation-based t-test, permutation-based chi-square test, visualization of residuals, and bootstrap 'Cramer V', plotting of the results of the 'Mann-Whitney' and 'Kruskal-Wallis' test, calculation of 'Brainerd-Robinson' similarity coefficient and subsequent clustering, validation of logistic regression models, optimism-corrected AUC, robust 'Bland-Altman' plot, calculation of posterior probability for different chronological relationships between two Bayesian radiocarbon phases, point pattern analysis, clustering of spatial features.