Grouping Metadata

Retrieve the (reference) groups to which the observations belong.

Usage

group_names(object)

group_levels(object)

group_factor(object, ...)

group_rows(object)

group_n(object)

group_size(object)

group_indices(object)

# S4 method for class 'ReferenceGroups'
group_levels(object)

# S4 method for class 'ReferenceGroups'
group_names(object)

# S4 method for class 'ReferenceGroups'
group_factor(object, exclude = NA)

# S4 method for class 'ReferenceGroups'
group_indices(object)

# S4 method for class 'ReferenceGroups'
group_rows(object)

# S4 method for class 'ReferenceGroups'
group_n(object)

# S4 method for class 'ReferenceGroups'
group_size(object)

Arguments

object

A grouped R object.

...

Currently not used.

exclude

A character vector of values to be excluded when forming the set of levels.

Value

• group_levels() returns a character vector giving the group names.

• group_size() returns an integer vector giving the size of each group.

• group_n() gives the total number of groups.

• group_names() returns a character vector giving the name of the group that each observation belongs to.

• group_factor() returns a factor vector giving the name of the group that each observation belongs to.

• group_indices() returns an integer vector giving the group that each value belongs to.

• group_rows() returns a list of integer vectors giving the observation that each group contains.

See also

Other grouping methods: group(), group_split(), group_subset(), is_assigned()

Author

N. Frerebeau

Examples

## Data from Aitchison 1986
data("slides")

## Coerce to compositional data
coda <- as_composition(slides, groups = 2)

## Grouping metadata
group_levels(coda)
#> [1] "A" "B" "C" "D" "E"

group_names(coda)
#>  [1] "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D" "E" "A" "B" "C" "D"
#> [20] "E" "A" "B" "C" "D" "E"

group_indices(coda)
#>  [1] 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5 1 2 3 4 5

group_rows(coda)
#> $A
#> [1]  1  6 11 16 21
#> 
#> $B
#> [1]  2  7 12 17 22
#> 
#> $C
#> [1]  3  8 13 18 23
#> 
#> $D
#> [1]  4  9 14 19 24
#> 
#> $E
#> [1]  5 10 15 20 25
#> 

group_n(coda)
#> [1] 5

group_size(coda)
#> A B C D E 
#> 5 5 5 5 5