View source: R/seqivolatility.R
seqivolatility | R Documentation |
Returns Brzinsky-Fay's objective volatility of each sequence.
seqivolatility(seqdata, w=.5, with.missing=FALSE, adjust=TRUE)
seqdata |
a state sequence object ( |
adjust |
Logical. Should the indicator be adjusted such that it can reach its bounds 0 and 1. Deafult is |
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 |
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
.
A numeric vector with the volatility of each sequence.
Gilbert Ritschard
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. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/00491241211036156")}.
seqintegr
, seqipos
, seqindic
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)
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