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Intra Hamming distance of CRPs

Source: R/formulas.R
intra_hd.Rd

The intra Hamming distance of two sets of CRPs measures the numbers of CRPs that differ. N sets of CRPs are equal if their intra Hamming distances are 0.

A response is reliable if it does not change in time, thus, its intra Hamming distance is equal to 0.

If crps is a 2D matrix, it is assumed that each row corresponds to a sample and each column to a CRP. The ref_sample will dictate which row is the sample taken as reference. In the case of a 3D matrix, each row corresponds to a device, each column to a CRP and the 3rd dimension represents the different samples.

Usage

intra_hd(crps, ref = 1)

Arguments

crps

A binary vector, 2D matrix or 3D array.

ref

Numeric index for the reference sample: If crps is a vector, is the index of the reference sample; If crps is a 2D matrix, the row to use as reference; If crps is a 3D array, the row for all 3rd dimension matrix.

Value

If crps is a vector, the intra Hamming distance of the vector. If crps is a 2D matrix, the reliability of each column as a vector of size ncol(crps) - 1. If crps is a 3D array, a 2D matrix where each row contains the intra Hamming distance all samples.

TODO: Maybe return the list of comparison to calculate the mean and sd

Details

The order of the samples is calculated as setdiff(seq_len(nsamples), ref_sample) where nsamples corresponds to nrow(crps) in the case of a 2D matrix and dim(crps)[3] in the case of a 3D matrix.

See also

hamming_dist

Examples

## Bit values
v <- c(1, 0, 0, 1, 1)
intra_hd(v, 1)
#> [1] 0 0 1 1

## Set of CRPs
mat <- rbits(c(5, 10))
intra_hd(mat, 1)
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]    0    0    1    0    1    1    0    0    1     0
#> [2,]    1    1    1    1    1    1    1    0    0     1
#> [3,]    0    1    0    1    1    0    1    0    1     1
#> [4,]    1    0    1    1    1    1    0    0    0     0

## Set of devices with their respective samples
mat <- rbits(c(5, 10, 3))
intra_hd(mat)
#>      [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
#> [1,]  0.5  0.5  0.0  0.5  1.0  0.0  0.5  0.0  0.5   0.0
#> [2,]  0.5  0.0  0.5  0.0  0.5  0.5  0.5  1.0  1.0   0.5
#> [3,]  1.0  0.5  0.0  0.0  1.0  0.5  0.5  0.5  1.0   0.5
#> [4,]  0.0  1.0  0.5  1.0  0.0  0.5  1.0  1.0  0.0   1.0
#> [5,]  1.0  1.0  0.5  1.0  1.0  0.5  0.5  0.5  0.5   0.5