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Compositional Mean of Data Subsets

Source: R/AllGenerics.R, R/condense.R
condense.Rd

Splits the data into subsets and computes compositional mean for each.

Usage

condense(x, ...)

# S4 method for CompositionMatrix
condense(x, by = get_samples(x), na.rm = FALSE)

Arguments

x

A CompositionMatrix object.

...

Currently not used.

by

A vector of grouping elements, as long as the variables in x.

na.rm

A logical scalar: should missing values be removed?

Value

A CompositionMatrix object.

See also

mean(), aggregate()

Other statistics: aggregate(), covariance(), dist, mahalanobis(), margin(), mean(), metric_var(), quantile(), scale(), variation()

Author

N. Frerebeau

Examples

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

## Coerce to a compositional matrix
coda <- as_composition(slides, sample = 2, group = 1)

## Compositional mean by sample
condense(coda, by = get_samples(coda))
#> <CompositionMatrix: 5 x 7>
#>                        quartz microcline plagioclass    biotite   muscovite
#> A_1:A_2:A_3:A_4:A_5 0.2591344  0.3553997   0.3335045 0.02654833 0.013683701
#> B_1:B_2:B_3:B_4:B_5 0.2703079  0.3526640   0.3239803 0.03482515 0.008977167
#> C_1:C_2:C_3:C_4:C_5 0.2772923  0.3535327   0.3149545 0.03107089 0.011128347
#> D_1:D_2:D_3:D_4:D_5 0.2757090  0.3548635   0.3138702 0.03298438 0.010338266
#> E_1:E_2:E_3:E_4:E_5 0.2794701  0.3474061   0.3231178 0.02962410 0.010892785
#>                         opaques  nonopaques
#> A_1:A_2:A_3:A_4:A_5 0.007173544 0.004555830
#> B_1:B_2:B_3:B_4:B_5 0.006667495 0.002578014
#> C_1:C_2:C_3:C_4:C_5 0.007732587 0.004288649
#> D_1:D_2:D_3:D_4:D_5 0.009093408 0.003141288
#> E_1:E_2:E_3:E_4:E_5 0.006494703 0.002994409

## Compositional mean by group
condense(coda, by = get_groups(coda))
#> <CompositionMatrix: 5 x 7>
#>                        quartz microcline plagioclass    biotite   muscovite
#> A_1:B_1:C_1:D_1:E_1 0.2680804  0.3506615   0.3267723 0.03302334 0.010447298
#> A_2:B_2:C_2:D_2:E_2 0.2831265  0.3509840   0.3161602 0.02767572 0.012826283
#> A_3:B_3:C_3:D_3:E_3 0.2633293  0.3574333   0.3199675 0.03984005 0.009170492
#> A_4:B_4:C_4:D_4:E_4 0.2725459  0.3590486   0.3181972 0.02652094 0.009552583
#> A_5:B_5:C_5:D_5:E_5 0.2741411  0.3450908   0.3273973 0.02900410 0.013085565
#>                         opaques  nonopaques
#> A_1:B_1:C_1:D_1:E_1 0.006724201 0.004290959
#> A_2:B_2:C_2:D_2:E_2 0.006955211 0.002272084
#> A_3:B_3:C_3:D_3:E_3 0.008472383 0.001786999
#> A_4:B_4:C_4:D_4:E_4 0.008424043 0.005710815
#> A_5:B_5:C_5:D_5:E_5 0.006529511 0.004751617