TraMineR (version 2.2-10)

seqivolatility: Volatility of individual state sequences

Description

Returns Brzinsky-Fay's objective volatility of each sequence.

Usage

seqivolatility(seqdata, w=.5, with.missing=FALSE, adjust=TRUE)

Value

A numeric vector with the volatility of each sequence.

Author

Gilbert Ritschard

Arguments

seqdata

a state sequence object (stslist) as returned by seqdef.

adjust

Logical. Should the indicator be adjusted such that it can reach its bounds 0 and 1. Deafult is TRUE (see Details).

w

Real in the range [0, 1]. Default is 0.5. Weight given to the proportion of states visited (see Details).

with.missing

Logical: should non-void missing values be treated as a regular state? If FALSE (default) missing values are ignored.

Details

The (objective) volatility is the weighted average between the proportion \(pvisited\) of states visited and the frequency \(ftrans\) of transitions (state changes). Formally,

$$volatility = w \cdot pvisited + (1-w) \cdot ftrans$$

The proportion of states visited is computed as \((visited - 1)/(|a| - 1\)) when adjsut=TRUE and as \(visited / |a|\) when adjsut=FALSE. Here, \(visited\) is the number of states visited and \(|a|\) the size of the alphabet.

The frequency of transition is \(ftrans = \frac{transn}{max.transn}\) where \(transn\) is the number of transitions (state changes) within the sequence, and \(max.transn\) the maximum possible transitions in the sequence.

For the normative volatility, see seqipos. For alternative measures of sequence complexity see seqST, seqici, seqindic.

References

Brzinsky-Fay, C. Unused Resources: Sequence and Trajectory Indicators. International Symposium on Sequence Analysis and Related Methods, Monte Verita, TI, Switzerland, Oct 10-11, 2018

Ritschard, G. (2023), "Measuring the nature of individual sequences", Sociological Methods and Research, 52(4), 2016-2049. tools:::Rd_expr_doi("10.1177/00491241211036156").

See Also

seqintegr, seqipos, seqindic

Examples

data(ex1)
sx <- seqdef(ex1[,1:13], right="DEL")

seqivolatility(sx)
seqivolatility(sx, adjust=FALSE)
seqivolatility(sx, with.missing=TRUE)
seqivolatility(sx, w=.7, with.missing=TRUE)