otsfeatures (version 1.0.0)

ordinal_location_2: Computes the estimated location of an ordinal time series with respect to the lowest category

Description

ordinal_location_2 computes the estimated location of an ordinal time series with respect to the lowest category

Usage

ordinal_location_2(series, states, distance = "Block", normalize = FALSE)

Value

The estimated location with respect to the lowest category.

Arguments

series

An OTS.

states

A numerical vector containing the corresponding states.

distance

A function defining the underlying distance between states. The Hamming, block and Euclidean distances are already implemented by means of the arguments "Hamming", "Block" (default) and "Euclidean". Otherwise, a function taking as input two states must be provided.

normalize

Logical. If normalize = FALSE (default), the value of the standard estimated location is returned. Otherwise, the function returns the normalized standard estimated location.

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 location with respect to the lowest state, that is, the state \(s_j\) such that \(a_j=d(s_j, s_0)\) is the closest to \(\frac{1}{T}\sum_{t=1}^Td\big(\overline{X}_t, s_0\big)\) is determined, where \(d(\cdot, \cdot)\) is a distance between ordinal states.

References

weiss2019distanceotsfeatures

Examples

estimated_location <- ordinal_location_2(series = AustrianWages$data[[100]],
states = 0 : 5) # Computing the location estimate
# with respect to the lowest state for one series in dataset AustrianWages