summary.micomp: Summary method for multiple comparisons of outputs

In fakenmc/micompr: Multivariate Independent Comparison of Observations

Summary method for multiple comparisons of outputs

Description

Summary method for objects of class micomp.

Usage

## S3 method for class 'micomp'
summary(object, ...)

Arguments

object	Object of class micomp.
...	Currently ignored.

Value

A list in which each component is associated with a distinct comparison. Each component contains a matrix, in which columns represent individual outputs and rows have information about the outputs. More specifically, each matrix has the following rows:

#PCs (ve=%)

Number of principal components required to explain the specified percentage of variance. There is one row of this kind for each percentage of variance specified when creating the micomp object.

MANOVA (ve=%)

P-value for the MANOVA test applied to the #PCs required to explain the specified percentage of variance. There is one row of this kind for each percentage of variance specified when creating the micomp object.

par.test

P-value for the parametric test (first principal component).

nonpar.test

P-value for the non-parametric test (first principal component).

par.test.adjust

P-value for the parametric test (first principal component), adjusted with the weighted Bonferroni procedure, percentage of explained variance used as weight.

nonpar.test.adjust

P-value for the non-parametric test (first principal component), adjusted with the weighted Bonferroni procedure, percentage of explained variance used as weight.

Examples

# A micomp object from package datasets (i.e. grpoutputs objects) directly

summary(micomp(5, 0.85,
               list(list(name = "CompEq", grpout = pphpc_ok),
                    list(name = "CompNoShuf", grpout = pphpc_noshuff),
                    list(name = "CompDiff", grpout = pphpc_diff))))

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