ordinal_location_2: Computes the estimated location of an ordinal time series...

In otsfeatures: Ordinal Time Series Analysis

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)

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.

Details

Given an OTS of length T with range \mathcal{S}=\{s_0, s_1, s_2, …, s_n\} (s_0 < s_1 < s_2 < … < s_n), \overline{X}_t=\{\overline{X}_1,…, \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}∑_{t=1}^Td\big(\overline{X}_t, s_0\big) is determined, where d(\cdot, \cdot) is a distance between ordinal states.

Value

The estimated location with respect to the lowest category.

Author(s)

Ángel López-Oriona, José A. Vilar

References

\insertRef

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

otsfeatures documentation built on March 7, 2023, 7:38 p.m.