plot.assumptions_cmpoutput: Plot _p_-values for testing the assumptions of the parametric...

In fakenmc/micompr: Multivariate Independent Comparison of Observations

Plot p-values for testing the assumptions of the parametric tests used in output comparison

Description

Plot method for objects of class assumptions_cmpoutput containing p-values produced by testing the assumptions of the parametric tests used for comparing an output.

Usage

## S3 method for class 'assumptions_cmpoutput'
plot(x, ...)

Arguments

x	Objects of class assumptions_cmpoutput.
...	Extra options passed to plot.default.

Details

Several bar plots are presented, showing the p-values yielded by the Shapiro-Wilk (shapiro.test) and Royston tests (mvn) for univariate and multivariate normality, respectively, and for the Bartlett (bartlett.test) and Box's M (boxM) for testing homogeneity of variances and of covariance matrices, respectively. The following bar plots are shown:

• One bar plot for the p-values of the Bartlett test, one bar (p-value) per individual principal component.

• s bar plots for p-values of the Shapiro-Wilk test, where s is the number of groups being compared. Individual bars in each plot are associated with a principal component.

• t bar plot for the p-values of the Royston test with s bars each, where t is the number of unique MANOVA tests performed (one per requested explained variances) and s is the number of groups being compared. These plots will not show if there is only one principal component being considered.

• One plot for the p-values of the Box's M test, one bar (p-value) per unique MANOVA tests performed (one per requested explained variances).

Value

None.

Examples

# Create a cmpoutput object from the provided datasets
cmp <- cmpoutput("All", 0.9, pphpc_ok$data[["All"]], pphpc_ok$obs_lvls)

# Display a bar plot with the p-values of the assumptions for the parametric
# tests performed in cmp
plot(assumptions(cmp))

fakenmc/micompr documentation built on Aug. 6, 2024, 8:29 p.m.