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otsfeatures (version 1.0.0)

index_ordinal_variation: 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)

Value

The estimated IOV.

Arguments

series

An OTS.

states

A numerical vector containing the corresponding states.

Author

Ángel López-Oriona, José A. Vilar

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 \(\overline{X}_t\).

References

weiss2019distanceotsfeatures

Examples

Run this code
estimated_iov <- index_ordinal_variation(series = AustrianWages$data[[100]],
states = 0 : 5) # Computing the estimate of the IOV
# for one series in dataset AustrianWages

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