Multichannel distances between sequences

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Description

Compute multichannel pairwise distances between sequences. Several metrics are available: optimal matching (OM), the longest common subsequence (LCS), the Hamming distance (HAM) and the Dynamic Hamming Distance (DHD).

Usage

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seqdistmc(channels, method, norm=FALSE, indel=1, sm=NULL,
     with.missing=FALSE, full.matrix=TRUE, link="sum", cval=2,
     miss.cost=2, cweight=NULL) 

Arguments

channels

A list of state sequence objects defined with the seqdef function, each state sequence object corresponding to a "channel".

method

a character string indicating the metric to be used. One of "OM" (Optimal Matching), "LCS" (Longest Common Subsequence), "HAM" (Hamming distance), "DHD" (Dynamic Hamming distance).

norm

if TRUE, the computed distances are normalized to account for differences in sequence lengths. Default is FALSE. See details.

indel

A vector with an insertion/deletion cost for each channel (OM method).

sm

A list with a substitution-cost matrix for each channel (OM, HAM and DHD method) or a list of method names for generating the substitution-costs (see seqsubm).

with.missing

Must be set to TRUE when sequences contain non deleted gaps (missing values) or when channels are of different length. See details.

full.matrix

If TRUE (default), the full distance matrix is returned. If FALSE, an object of class dist is returned.

link

One of "sum" or "mean". Method to compute the "link" between channels. Default is to sum the substitution costs.

cval

Substitution cost for "CONSTANT" matrix, see seqsubm.

miss.cost

Missing values substitution cost, see seqsubm.

cweight

A vector of channel weights. Default is 1 (same weight for each channel).

Details

The seqdistmc function returns a matrix of multichannel distances between sequences. The available metrics (see 'method' option) are optimal matching ("OM"), longest common subsequence ("LCS"), Hamming distance ("HAM") and Dynamic Hamming Distance ("DHD"). See seqdist for more information about distances between sequences. The seqdistmc function computes a multichannel distance in two steps following the strategy proposed by Pollock (2007). First it builds a new sequence object derived from the combination of the sequences of each channel. Second, it derives the substitution cost matrix by summing (or averaging) the costs of substitution across channels. It then calls seqdist to compute the final matrix. Normalization may be useful when dealing with sequences that are not all of the same length. For details on the applied normalization, see seqdist.

Value

A matrix of pairwise distances between sequences is returned.

Author(s)

Matthias Studer (with Gilbert Ritschard for the help page)

References

Pollock, Gary (2007) Holistic trajectories: a study of combined employment, housing and family careers by using multiple-sequence analysis. Journal of the Royal Statistical Society: Series A 170, Part 1, 167–183.

See Also

seqsubm, seqdef, seqdist.

Examples

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data(biofam)

## Building one channel per type of event left, children or married
bf <- as.matrix(biofam[, 10:25])
children <-  bf==4 | bf==5 | bf==6
married <- bf == 2 | bf== 3 | bf==6
left <- bf==1 | bf==3 | bf==5 | bf==6

## Building sequence objects
child.seq <- seqdef(children)
marr.seq <- seqdef(married)
left.seq <- seqdef(left)

## Using transition rates to compute substitution costs on each channel
mcdist <- seqdistmc(channels=list(child.seq, marr.seq, left.seq),
 	method="OM", sm =list("TRATE", "TRATE", "TRATE")) 	

## Using a weight of 2 for children channel and specifying substitution-cost
smatrix <- list()
smatrix[[1]] <- seqsubm(child.seq, method="CONSTANT")
smatrix[[2]] <- seqsubm(marr.seq, method="CONSTANT")
smatrix[[3]] <- seqsubm(left.seq, method="TRATE")
mcdist2 <- seqdistmc(channels=list(child.seq, marr.seq, left.seq),
	method="OM", sm =smatrix, cweight=c(2,1,1)) 

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