| index_ordinal_variation {otsfeatures} | R Documentation |
Computes the estimated index of ordinal variation (IOV) of an ordinal time series
Description
index_ordinal_variation computes the estimated index of ordinal variation
of an ordinal time series
Usage
index_ordinal_variation(series, states)
Arguments
series |
An OTS. |
states |
A numerical vector containing the corresponding states. |
Details
Given an OTS of length T with range \mathcal{S}=\{s_0, s_1, s_2, \ldots, s_n\} (s_0 < s_1 < s_2 < \ldots < s_n),
\overline{X}_t=\{\overline{X}_1,\ldots, \overline{X}_T\}, the function computes the
estimated IOV given by \widehat{IOV}=\frac{4}{n}\sum_{k=1}^{n-1}\widehat{f}_k(1-\widehat{f}_k),
where \widehat{f}_k is the standard estimate of the cumulative marginal probability
for state s_k computed from the series \overline{X}_t.
Value
The estimated IOV.
Author(s)
Ángel López-Oriona, José A. Vilar
References
Weiß CH (2019). “Distance-based analysis of ordinal data and ordinal time series.” Journal of the American Statistical Association.
Examples
estimated_iov <- index_ordinal_variation(series = AustrianWages$data[[100]],
states = 0 : 5) # Computing the estimate of the IOV
# for one series in dataset AustrianWages